EMA bands + leledc + bollinger bands trend following strategy v2The basics:
In its simplest form, this strategy is a positional trend following strategy which enters long when price breaks out above "middle" EMA bands and closes or flips short when price breaks down below "middle" EMA bands. The top and bottom of the middle EMA bands are calculated from the EMA of candle highs and lows, respectively.
The idea is that entering trades on breakouts of the high EMAs and low EMAs rather than the typical EMA based on candle closes gives a bit more confirmation of trend strength and minimizes getting chopped up. To further reduce getting chopped up, the strategy defaults to close on crossing the opposite EMA band (ie. long on break above high EMA middle band and close below low EMA middle band).
This strategy works on all markets on all timeframes, but as a trend following strategy it works best on markets prone to trending such as crypto and tech stocks. On lower timeframes, longer EMAs tend to work best (I've found good results on EMA lengths even has high up to 1000), while 4H charts and above tend to work better with EMA lengths 21 and below.
As an added filter to confirm the trend, a second EMA can be used. Inputting a slower EMA filter can ensure trades are entered in accordance with longer term trends, inputting a faster EMA filter can act as confirmation of breakout strength.
Bar coloring can be enabled to quickly visually identify a trend's direction for confluence with other indicators or strategies.
The goods:
Waiting for the trend to flip before closing a trade (especially when a longer base EMA is used) often leaves money on the table. This script combines a number of ways to identify when a trend is exhausted for backtesting the best early exits.
"Delayed bars inside middle bands" - When a number of candle's in a row open and close between the middle EMA bands, it could be a sign the trend is weak, or that the breakout was not the start of a new trend. Selecting this will close out positions after a number of bars has passed
"Leledc bars" - Originally introduced by glaz, this is a price action indicator that highlights a candle after a number of bars in a row close the same direction and result in greatest high/low over a period. It often triggers when a strong trend has paused before further continuation, or it marks the end of a trend. To mitigate closing on false Leledc signals, this strategy has two options: 1. Introducing requirement for increased volume on the Leledc bars can help filter out Leledc signals that happen mid trend. 2. Closing after a number of Leledc bars appear after position opens. These two options work great in isolation but don't perform well together in my testing.
"Bollinger Bands exhaustion bars" - These bars are highlighted when price closes back inside the Bollinger Bands and RSI is within specified overbought/sold zones. The idea is that a trend is overextended when price trades beyond the Bollinger Bands. When price closes back inside the bands it's likely due for mean reversion back to the base EMA in which this strategy will ideally re-enter a position. Since the added RSI requirements often make this indicator too strict to trigger a large enough sample size to backtest, I've found it best to use "non-standard" settings for both the bands and the RSI as seen in the default settings.
"Buy/Sell zones" - Similar to the idea behind using Bollinger Bands exhaustion bars as a closing signal. Instead of calculating off of standard deviations, the Buy/Sell zones are calculated off multiples of the middle EMA bands. When trading beyond these zones and subsequently failing back inside, price may be due for mean reversion back to the base EMA. No RSI filter is used for Buy/Sell zones.
If any early close conditions are selected, it's often worth enabling trade re-entry on "middle EMA band bounce". Instead of waiting for a candle to close back inside the middle EMA bands, this feature will re-enter position on only a wick back into the middle bands as will sometimes happen when the trend is strong.
Any and all of the early close conditions can be combined. Experimenting with these, I've found can result in less net profit but higher win-rates and sharpe ratios as less time is spent in trades.
The deadly:
The trend is your friend. But wouldn't it be nice to catch the trends early? In ranging markets (or when using slower base EMAs in this strategy), waiting for confirmation of a breakout of the EMA bands at best will cause you to miss half the move, at worst will result in getting consistently chopped up. Enabling "counter-trend" trades on this strategy will allow the strategy to enter positions on the opposite side of the EMA bands on either a Leledc bar or Bollinger Bands exhaustion bar. There is a filter requiring either a high/low (for Leledc) or open (for BB bars) outside the selected inner or outer Buy/Sell zone. There are also a number of different close conditions for the counter-trend trades to experiment with and backtest.
There are two ways I've found best to use counter-trend trades
1. Mean reverting scalp trades when a trend is clearly overextended. Selecting from the first 5 counter-trend closing conditions on the dropdown list will usually close the trades out quickly, with less profit but less risk.
2. Trying to catch trends early. Selecting any of the close conditions below the first 5 can cause the strategy to behave as if it's entering into a new trend (from the wrong side).
This feature can be deadly effective in profiting from every move price makes, or deadly to the strategy's PnL if not set correctly. Since counter-trend trades open opposite the middle bands, a stop-loss is recommended to reduce risk. If stop-losses for counter-trend trades are disabled, the strategy will hold a position open often until liquidation in a trending market if th trade is offsides. Note that using a slower base EMA makes counter-trend stop-losses even more necessary as it can reduce the effectiveness of the Buy/Sell zone filter for opening the trades as price can spend a long time trending outside the zones. If faster EMAs (34 and below) are used with "Inner" Buy/Zone filter selected, the first few closing conditions will often trigger almost immediately closing the trade at a loss.
The niche:
I've added a feature to default into longs or shorts. Enabling these with other features (aside from the basic long/short on EMA middle band breakout) tends to break the strategy one way or another. Enabling default long works to simulate trying to acquire more of the asset rather than the base currency. Enabling default short can have positive results for those high FDV, high inflation coins that go down-only for months at a time. Otherwise, I use default short as a hedge for coins that I hold and stake spot. I gain the utility and APR of staking while reducing the risk of holding the underlying asset by maintaining a net neutral position *most* of the time.
Disclaimer:
This script is intended for experimenting and backtesting different strategies around EMA bands. Use this script for your live trading at your own risk. I am a rookie coder, as such there may be errors in the code that cause the strategy to behave not as intended. As far as I can tell it doesn't repaint, but I cannot guarantee that it does not. That being said if there's any question, improvements, or errors you've found, drop a comment below!
Search in scripts for "stop loss"
Stochastic Moving AverageHi all,
This Strategy script combines the power of EMAs along with the Stochastic Oscillator in a trend following / continuation manner, along with some cool functionalities.
I designed this script especially for trading altcoins, but it works just as good on Bitcoin itself and on some Forex pairs.
______ SIGNALS ______
The script has 4 mandatory conditions to unlock a trading signal. Find these conditions for a long trade below (works the exact other way round for shorts)
- Fast EMA must be higher than Slow EMA
- Stochastic K% line must be in oversold territory
- Stochastic K% line must cross over Stochastic D% line
- Price as to close between slow EMA and fast EMA
Once all the conditions are true, a trade will start at the opening of the next
______ SETTINGS ______
- Trade Setup:
Here you can choose to trade only longs or shorts and change your Risk:Reward.
You can also decide to adjust your volume per position according to your risk tolerance. With “% of Equity” your stop loss will always be equal to a fixed percentage of your initial capital (will “compound” overtime) and with “$ Amount” your stop loss will always be 'x' amount of the base currency (ex: USD, will not compound)
Stop Loss:
The ATR is used to create a stop loss that matches current volatility. The multiplier corresponds to how many times the ATR stop losses and take profits will be away from closing price.
- Stochastic:
Here you can find the usual K% & D% length and overbought (OB) and oversold (OS) levels.
The “Stochastic OB/OS lookback” increase the tolerance towards OB/OS territories. It allows to look 'x' bars back for a value of the Stochastic K line to be overbought or oversold when detecting an entry signal.
The “All must be OB/OS” refers to the previous “Stochastic OB/OS lookback” parameter. If this option is ticked, instead of needing only 1 OB/OS value within the lookback period to get a valid signal, now, all bars looked back must be OB/OS.
The color gradient drawn between the fast and slow EMAs is a representation of the Stochastic K% line position. With default setting colors, when fast EMA > slow EMA, gradient will become solid blue when Stochastic is oversold and when slow EMA > fast EMA, gradient will become solid blue when Stochastic is overbought
- EMAs:
Just pick your favorite ones
- Reference Market:
An additional filter to be certain to stay aligned with the current a market index trend (in our case: Bitcoin). If selected reference market (and timeframe) is trading above selected EMA, this strategy will only take long trades (vice-versa for shorts) Because, let’s face it… even if this filter isn’t bulletproof, you know for sure that when Bitcoin tanks, there won’t be many Alts going north simultaneously. Once again, this is a trend following strategy.
A few tips for increased performance: fast EMA and D% Line can be real fast… 😉
As always, my scripts evolve greatly with your ideas and suggestions, keep them coming! I will gladly incorporate more functionalities as I go.
All my script are tradable when published but remain work in progress, looking for further improvements.
Hope you like it!
3 Candle Strike SPY Option StrategyImportant notes:
1. This strategy is designed for same day SPY option scalping. All profit shown in back testing report is based on Profit/Loss (P/L) estimates from trading options with approximately 7.5 weeks of data. By default, it is set to 10 option contracts. By default the initial capital is set to $5000.
2. This strategy also takes into account of extended market data, so turn it on for it to work as intended.
3. This strategy is mainly developed for SPY trading on 1 min chart, it probably will not work with other tickers without tweaking all the parameters first.
4. At the time of publish, the market is experiencing high volatility. Keep that in mind as market conditions changes constantly.
How it works:
Basic idea of this strategy is to look for 3 candle reversal pattern within trending market structure. The 3 candle reversal pattern consist of 3 consecutive bullish or bearish candles, followed by an engulfing candle in the opposite direction. This pattern usually signals a reversal of short term trend (a.k.a pullbacks). This strategy uses multiple moving averages to filter long or short entries. For example, if the 21 smoothed moving average is above the 50, only look for long (bullish) entries, and vise versa. There are settings to change these moving average periods to suit your needs. Linear Regression to determine whether the market is trending. The 3 candle pattern is more successful under trending market.
This strategy aims for approximately 1:3 risk to reward ratio. Stop losses are calculated using the closest low or high values for long or short entries, respectively, with an offset using a percentage of the daily ATR value. This allows some price fluctuation without being stopped out prematurely. Price target is calculated by multiplying the difference between the entry price and the stop loss by a factor of 3. When price target is reach, this strategy will set stop loss at the price target and wait for exit conditions to maximize potential profit.
By default, the strategy signals a trade in the opposite direction if the previous one had resulted in a loss. Often times, this opposite trade results in profit.
This strategy automatically signal to close all trades at 3:50 pm EST at the end of the day.
Enjoy~!!! Let's all make $$$
[Joy] Aladdin Long Trading Strategy 1.0.0 AlphaAladdin's Long trading strategy is to test out Aladdin for long trades only
This strategy is mainly used to test whether Aladdin is suitable for a coin/stocks/futures or for any trading. The profitability, average drawdown, average profits, etc are used by me to decide whether to use it for trading.
What is Aladdin and what does it do?
Using the volume and gradual flow of non-interrupted data (wicks and body of the candles), it tries to detect the macro condition of the market so that one may know in which direction the market is flowing.
* Bearish / Sell sign: On the candle's close, I open a short position
* Bullish sign: On the candle's close, I open a long position
* I take at least 50% profit when the indicator indicates to do so. One can configure that value as desired from the configuration depending on one's risk/money management. I might even convert some portion of the position into stable coins.
FAQ
Q: Does it use some EMA /MA/etc.? Does it use any indicator with tweaked settings?
Answer: No.
Q: What does it mostly depend on?
Answer: Volume and gradual flow of non-interrupted data. The logic depends purely on volume , price bars and the wicks.
Q: Does it work with all coins, stocks, futures, instruments?
Answer: I prefer to use the exchange with the best possible data. Then backtest out to find the best possible timeframe, stop loss and target all derived from this script data.
Q: Can you make it free or make it open source?
Answer: There is no free lunch in this world. I will never reveal or share the source code!
Q: Do you provide ongoing support for the indicator?
Answer: Yes, as long as I can, I will continue updating the indicator
Q: Are the bullish /buy & the bearish/sell markers automatic?
Answer: I have no control over the markers. It is driven purely by logic from the script.
Q: Is this financial advice?
Answer: This is not financial advice. I do not guarantee any profit or loss. I am not responsible for any of your losses or profits. My indicators do not assure profit or loss. It also does not auto-open or auto-close a trade.
Assumptions:
Only long trades are opened and closed. No short trades.
Starting Capital: $20,000
Order Size: 20% of Capital
Data used: Whatever data is available from 2011 till today on Trading view
Findings:
INDEX: BTCUSD 83% profitability using 2day tf
54 closed trades
Profit factor: 16
Sortino Ratio: 5.2
Average Winning Trade: 30%
Average Losing Trade: 9.12%
Largest Winning Trade: 1218%
Largest Losing Trade: 20.25%
Below are the profitability rate for the timeframe and the coins listed as found by running the trading strategy over the following as of today (Aug 1st 2021 12:40 pm Sydney Time).
⚜️ INDEX:BTCUSD 83% using 2day tf
⚜️INDEX:ETHUSD 80% using 1day tf
⚜️FTTUSD 81% using 2day tf
⚜️SRMUSD 71% using 1day tf
⚜️ADAUSDT 81% using 2day tf
⚜️ALGOUSD > 90% using 2day tf
⚜️ALTPERP 81% using 2day tf
⚜️AVAXUSDT 75% using 1day tf
⚜️BANDUSD > 90% using 2day tf
⚜️BCHUSD 82% using 2day tf
⚜️BNBUSD 79% using 1day tf
⚜️BNBUSD 85% using 2day tf
⚜️CHZUSD 71% using 1day tf
⚜️COMPUSD 81% using 1day tf
⚜️DOGEUSD 77% using 1day tf
⚜️EXCHPERP 83% using 1day tf
⚜️FILUSD > 90% using 1day tf
⚜️FTMUSD 70% using 2day tf
⚜️HTUSDT 75% using 2day tf
⚜️KINUSD >90% using 2day tf
⚜️LINKPERP 85% using 2day tf
⚜️LTCUSD 80% using 2day tf
⚜️MATICUSD 77% using 2day tf
⚜️NEOUSD 80% using 1day tf
⚜️NEXOUSD > 90% using 1day tf
⚜️OKBUSD 71% using 1day tf
⚜️OMGUSD 75% using 1day tf
⚜️RSRUSD 87% using 1day tf
⚜️RUNEUSD > 90% using 1day tf
⚜️SHITPERP > 90% using 1day tf
⚜️SOLUSD 84% using 1day tf
⚜️SUSHIUSD 71% using 1day tf
⚜️THETAUSD > 90% using 2day tf
⚜️UNIPERP 83% using 1day tf
⚜️VERTPERP > 90% using 1day tf
⚜️XAUUSD 63% using 2day tf
⚜️XTZUSD 83% using 2day tf
⚜️ZECUSD 72% using 2day tf
Disclaimer:
No one knows what will happen in the future. DYOR and decide on your own conditions. Do realize that neither I nor my indicator can guarantee any profit or loss. And there is no assurance that any trade will ever result in any profit. It is not financial advice.
Breakout Trend Trading Strategy - V1Strategy in nutshell:
This strategy is made to be used in daily time-frames. Works better on trending instruments where volume is available. Hence, this is more suitable for trending shares rather than currencies, commodities and indexes where volume data is either not present or not reliable.
Breakout signifies the continuation of trend. Hence, trade in the direction of breakouts. Breakouts are calculated based on high volume and price movement in a day. This will be combined with few other conditions to generate buy and sell signals along with stop and compound targets. Supertrend is used for trend bias. Our buy and sell targets do not directly depend on the bias. But, entry criteria in opposite trend is made much difficult than that of trend direction. Further explanation of method and input parameters are explained below.
Backtesting parameters :
Capital and position sizing : Capital and position sizing parameters are set to test investing 2000 wholly on certain stock without compounding.
Initial Capital : 2000
Order Size : 100% of equity
Pyramiding : 1
ExitOnSignal : If unchecked exit is triggered solely on trailing stop
Trade Direction : Long, Short or All. Short condition is riskier than long conditions and often results in losses as per my observation. On most of the stocks trending up, strategy will not generate any short signals. This is achieved by comparing yearly high lows to previous two years to decide whether to allow short or long entries.
allowImmediateCompound : Applicable only if compounding/pyramiding is enabled in trade. If checked allows to place compounding orders immediately. If unchecked, it waits for stopline to cross order price before placing next compound.
Display Mode :
Targets : Whenever breakout happens, show marker for upTarget and downTarget
TargetChannel : Show up target and downtarget as a channel
Target With Stop : Along with targets, show also stop levels for breakouts
Up Channel : Channel created from UpTarget and respective stops
Down Channel : Channel created from DownTarget and respective stops
ShowTrailingStop : Shows trailing stop and compound lines when there is a trading position.
ShowTargetLevels : Shows Buy Sell target levels along with stop and compound lines. Trades are done as market orders. Hence, target levels are displayed after strategy makes the trade. Since only one order allowed per side without compounding, target, stop and compound levels are shown sometimes even without trade being made. These can be considered as entry levels if there is no existing position.
ShowPreviousLevels : Shows previous buy/sell target levels. When enabled, layout can look messy.
StopMultiplyer: To Set trailing stop loss.
BacktestYears: Number of years to include in backtest
So far my test cases are:
Positive : AAPL, AMZN, TSLA, RUN, VRT, ASX:APT
Negative Test Cases: WPL, WHC, NHC, WOW, COL, NAB (All ASX stocks)
Special test case: WDI
Negative test cases still show losses in backtesting. I have attempted including many conditions to eliminate or reduce the loss. But, further efforts has resulted in reduction in profits in positive cases as well. Still experimenting. Will update whenever I find improvements. Comments and suggestions welcome :)
Grid Like StrategyIt is possible to use progressive position sizing in order to recover from past losses, a well-known position sizing system being the "martingale", which consists of doubling your position size after a loss, this allows you to recover any previous losses in a losing streak + winning an extra. This system has seen a lot of attention from the trading community (mostly from beginners), and many strategies have been designed around the martingale, one of them being "grid trading strategies".
While such strategies often shows promising results on paper, they are often subjects to many frictions during live trading that makes them totally unusable and dangerous to the trader. The motivations behind posting such a strategy isn't to glorify such systems, but rather to present the problems behind them, many users come to me with their ideas and glorious ways to make money, sometimes they present strategies using the martingale, and it is important to present the flaws of this methodology rather than blindly saying "you shouldn't use it".
Strategy Settings
Point determines the "grid" size and should be adjusted accordingly to the scale of the symbol you are applying the strategy to. Higher value would require larger price movements in order to trigger a trade, as such higher values will generate fewer trades.
The order size determines the number of contracts/shares to purchase.
The martingale multiplier determines the factor by which the position size is multiplied after a loss, using values higher to 2 will "squarify" your balance, while a value of 1 would use a constant position sizing.
Finally, the anti-martingale parameter determines whether the strategy uses a reverse martingale or not, if set to true then the position size is multiplied after any wins.
The Grid
Grid strategies are commons and do not present huge problems until we use certain position sizing methods such as the martingale. A martingale is extremely sensitive to any kind of friction (frictional costs, slippage...etc), the grid strategy aims to provide a stable and simple environment where a martingale might possibly behave well.
The goal of a simple grid strategy is to go long once the price crossover a certain level, a take profit is set at the level above the current one and stop loss is placed at the level below the current one, in a winning scenario the price reach the take profit, the position is closed and a new one is opened with the same setup. In a losing scenario, the price reaches the stop loss level, the position is closed and a short one is opened, the take profit is set at the level below the current one, and a stop loss is set at the level above the current one. Note that all levels are equally spaced.
It follows from this strategy that wins and losses should be constant over time, as such our balance would evolve in a linear fashion. This is a great setup for a martingale, as we are theoretically assured to recover all the looses in a losing streak.
Martingale - Exponential Decays - Risk/Reward
By using a martingale we double our position size (exposure) each time we lose a trade, if we look at our balance when using a martingale we see significant drawdowns, with our balance peaking down significantly. The martingale sequence is subject to exponential growth, as such using a martingale makes our balance exposed to exponential decays, that's really bad, we could basically lose all the initially invested capital in a short amount of time, it follows from this that the theoretical success of a martingale is determined by what is the maximum losing streak you can endure
Now consider how a martingale affects our risk-reward ratio, assuming unity position sizing our martingale sequence can be described by 2^(x-1) , using this formula we would get the amount of shares/contracts we need to purchase at the x trade of a losing streak, we would need to purchase 256 contracts in order to recover from a losing streak of size 9, this is enormous when you take into account that your wins are way smaller, the risk-reward ratio is totally unfair.
Of course, some users might think that a losing streak of size 9 is pretty unlikely, if the probability of winning and losing are both equal to 0.5, then the probability of 9 consecutive losses is equal to 0.5^9 , there are approximately 0.2% of chance of having such large losing streak, note however that under a ranging market such case scenario could happen, but we will see later that the length of a losing streak is not the only problem.
Other Problems
Having a capital large enough to tank 9any number of consecutive losses is not the only thing one should focus on, as we have to take into account market prices and trading dynamics, that's where the ugly part start.
Our first problem is frictional costs, one example being the spread, but this is a common problem for any strategy, however here a martingale is extra sensitive to it, if the strategy does not account for it then we will still double our positions costs but we might not recover all the losses of a losing streak, instead we would be recovering only a proportion of it, under such scenario you would be certain to lose over time.
Another problem are gaps, market price might open under a stop-loss without triggering it, and this is a big no-no.
Equity of the strategy on AMD, in a desired scenario the equity at the second arrow should have been at a higher position than the equity at the first arrow.
In order for the strategy to be more effective, we would need to trade a market that does not close, such as the cryptocurrency market. Finally, we might be affected by slippage, altho only extreme values might drastically affect our balance.
The Anti Martingale
The strategy lets you use an anti-martingale, which double the position size after a win instead of a loss, the goal here is not to recover from a losing strike but instead to profit from a potential winning streak.
Here we are exposing your balance to exponential gross but you might also lose a trade at the end a winning streak, you will generally want to reinitialize your position size after a few wins instead of waiting for the end of a streak.
Alternative
You can use other-kind of progressions for position sizing, such as a linear one, increasing your position size by a constant number each time you lose. More gentle progressions will recover a proportion of your losses in a losing streak.
You can also simulate the effect of a martingale without doubling your position size by doubling your target profit, if for example you have a 10$ profit-target/stop-loss and lose a trade, you can use a 20$ profit target to recover from the lost trade + gain a profit of 10$. While this approach does not introduce exponential decay in your balance, you are betting on the market reaching your take profits, considering the fact that you are doubling their size you are expecting market volatility to increase drastically over time, as such this approach would not be extremely effective for high losing streak.
Conclusion
You will see a lot of auto-trading strategies that are based on a grid approach, they might even use a martingale. While the backtests will look appealing, you should think twice before using such kind of strategy, remember that frictional costs will be a huge challenge for the strategy, and that it assumes that the trader has an important initial capital. We have also seen that the risk/reward ratio is theoretically the worst you can have on a strategy, having a low reward and a high risk. This does not mean that progressive position sizing is bad, but it should not be pushed to the extreme.
It is nice to note that the martingale is originally a betting system designed for casino games, which unlike trading are not subject to frictional costs, but even casino players don't use it, so why would you?
Thx for reading
Moving Average + Candle LeverageWhat if you could extract more value from each trade based on your stop loss and entry, increasing your leverage safely? Could your winning trades be even more profitable?
This indicator uses a single selectable moving average (SMA, EMA, WMA, HMA, or VWMA) to calculate safe leverage per candle, allowing traders to maximize each trade within a defined stop loss. Actual profit remains variable depending on market movement and applied leverage.
How signals appear and how leverage is determined
L (green): signals that price crossed above the moving average (potential long entry).
S (red): signals that price crossed below the moving average (potential short entry).
Each crossover shows a label with “x”, indicating the theoretical safe leverage for that candle.
How safe leverage is calculated:
Long: close ÷ (close − candle low)
Short: close ÷ (candle high − close)
How leverage is applied:
Identify the signal candle and record close, high, and low.
Calculate the difference between the close price and the stop price (low for Long, high for Short).
The percentage difference between these prices is our safe leverage: the smaller the difference, the higher the leverage possible, always respecting the stop loss.
The “x” label shows this maximum leverage, protecting the position balance using the candle’s stop loss.
Actual profit will still depend on market movement, but the stop loss is already defined and secure.
Main benefits:
Maximize trade potential with known stop loss
Plan entries and position sizing safely
Clearly visualize safe leverage per candle
Simple, efficient, and educational
Disclaimer:
The indicator does not execute trades automatically and is not a full trading system. It is intended solely for educational purposes and safe leverage management.
DynamicQuant Lite Strategy v1.1.1🚀 DynamicQuant Pro - Adaptive Channel-Based Trading Strategy
📊 Strategy Overview
DynamicQuant Pro is an adaptive trading strategy based on price channel breakouts. It offers both trend-following and mean-reversion modes to adapt to various market conditions.
⚡ Core Features
🎯 Entry System
- Channel Breakout Based: Uses upper/lower band breakouts as entry signals
- Multi-Layer Filtering: Triple-filter system combining volume, momentum, and volatility indicators to eliminate false signals
- Smart Entry Control: Entry restriction zones and minimum bar spacing to prevent excessive positions
- Multi-Stage Position Building: Up to 5-stage scaling to optimize average entry price
🔄 Exit System (4 Modes)
- Band Mode: Exit based on channel centerline
- Split Mode: Individual exit per entry price
- Trailing Mode: Dynamic trailing exit
- Position Mode: Unified exit based on average price
🛡️ Risk Management
- Advanced Stop Loss: Intelligent exit system with recovery failure detection and time-based stops
- Multi-Level Take Profit: Flexible exit strategies including weighted partial exits and ladder profits
- Profit Protection: Safety mechanism preventing exits at loss levels
- Leverage-Based Margin Management: Margin calculation matching real exchange systems
✨ Key Strengths
⚡ Real-Time Exits: Tick-by-tick monitoring for immediate exits when targets are reached (no waiting for bar close)
📈 Detailed Visualization: Real-time PnL, entry prices, targets, stops - all displayed on chart
📊 Backtest Performance Table: Detailed statistics including win rate, profit factor, Long/Short performance
🎛️ Flexible Configuration: 30+ parameters to customize to your trading style
👥 Ideal For
✅ Traders seeking systematic risk management
✅ Traders looking for adaptable strategies across market conditions
✅ Traders preferring backtest-based strategy optimization
✅ Traders interested in scaling entry/exit strategies
⚠️ Disclaimer
This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss. Always conduct your own research and risk assessment before trading with real capital.
EMA 12-26-100 Momentum Strategy# Triple EMA Multi-Signal Momentum Strategy
## 📊 Overview
**Triple EMA Multi-Signal** is a comprehensive trend-following momentum strategy designed specifically for cryptocurrency markets. It combines multiple technical indicators and signal types to identify high-probability trading opportunities while maintaining strict risk management protocols.
The strategy excels in trending markets and uses adaptive position sizing with trailing stops to maximize profits during strong trends while protecting capital during choppy conditions.
## 🎯 Core Algorithm
### Triple EMA System
The strategy employs a three-layer EMA system to identify trend direction and strength:
- **Fast EMA (12)**: Quick response to price changes
- **Slow EMA (26)**: Confirmation of trend direction
- **Trend EMA (100)**: Overall market bias filter
Trades are only taken when all three EMAs align in the same direction, ensuring we trade with the dominant trend.
### Multi-Signal Confirmation (8 Signal Types)
The strategy requires at least 1-2 confirmed signals from multiple independent sources before entering a position:
1. **EMA Crossover** - Fast EMA crossing Slow EMA (primary signal)
2. **MACD Cross** - MACD line crossing signal line (momentum confirmation)
3. **RSI Reversal** - RSI bouncing from oversold/overbought zones
4. **Price Action** - Strong bullish/bearish candles (>60% of range)
5. **Volume Spike** - Above-average volume confirmation
6. **Breakout** - Price breaking 20-period high/low with volume
7. **Pullback to EMA** - Trend continuation after healthy retracement
8. **Bollinger Bounce** - Price bouncing from BB bands
This multi-signal approach significantly reduces false signals and improves win rate.
## 💰 Risk Management
### Position Sizing
- Default: 20-25% of equity per trade
- Adjustable based on risk tolerance
- Smaller positions recommended for leveraged trading
### Stop Loss & Take Profit
- **Stop Loss**: 2.0% (tight control of risk)
- **Take Profit**: 5.5% (2.75:1 reward-to-risk ratio)
- Both levels are fixed at entry to avoid emotional decisions
### Trailing Stop System
- Activates after 1.8% profit
- Trails at 1.3% below current price
- Locks in profits during extended trends
- Automatically adjusts as price moves in your favor
### Maximum Hold Time
- 36-48 hours maximum (configurable)
- Designed to minimize funding rate costs on futures
- Forces position closure to avoid excessive exposure
- Helps maintain capital velocity
## 📈 Key Features
### Trend Filters
- **ADX Filter**: Ensures sufficient trend strength (threshold: 20)
- **EMA Alignment**: All three EMAs must confirm trend direction
- **RSI Boundaries**: Avoids extreme overbought/oversold entries
### Volume Analysis
- Volume must exceed 20-period moving average
- Configurable multiplier (default: 1.0x)
- Helps identify institutional participation
### Automatic Exit Conditions
1. Take Profit target reached
2. Stop Loss triggered
3. Trailing stop activated
4. Trend reversal (EMA cross in opposite direction)
5. Maximum hold time exceeded
## 🎮 Recommended Settings
### For Spot Trading (Conservative)
```
Position Size: 15-20%
Stop Loss: 2.5%
Take Profit: 6.0%
Max Hold: 72 hours
Leverage: 1x
```
### For Futures 3-5x Leverage (Balanced)
```
Position Size: 12-15%
Stop Loss: 2.0%
Take Profit: 5.5%
Max Hold: 36 hours
Trailing: Active
```
### For Aggressive Trading 5-10x (High Risk)
```
Position Size: 8-12%
Stop Loss: 1.5%
Take Profit: 4.5%
Max Hold: 24 hours
ADX Filter: Disabled
```
## 📊 Performance Metrics
### Backtested Results (BTC/USDT 1H, 2 years)
- **Total Return**: ~19% (spot) / ~75% (5x leverage)*
- **Total Trades**: 240-300
- **Win Rate**: 49-52%
- **Profit Factor**: 1.25-1.50
- **Max Drawdown**: ~18-22%
- **Average Trade**: 0.5-3 days
*Leverage results exclude funding rates and real-world slippage
### Optimal Timeframes
- **1 Hour**: Best for active trading (recommended)
- **4 Hour**: More stable, fewer signals
- **15 Min**: High frequency (requires monitoring)
### Best Performing Assets
- BTC/USDT (most tested)
- ETH/USDT
- Major altcoins with good liquidity
- Not recommended for low-cap or illiquid pairs
## ⚙️ How to Use
1. **Add to Chart**: Apply strategy to 1H BTC/USDT chart
2. **Adjust Settings**: Configure risk parameters based on your preference
3. **Review Signals**: Green = Long, Red = Short, labels show signal count
4. **Monitor Performance**: Check strategy tester for detailed statistics
5. **Optimize**: Use strategy optimization to find best parameters for your market
## 🎨 Visual Indicators
The strategy provides clear visual feedback:
- **EMA Lines**: Blue (Fast), Red (Slow), Orange (Trend)
- **BUY/SELL Labels**: Show entry points with signal count
- **Stop/Target Lines**: Red (SL), Green (TP) displayed during active trades
- **Background Color**: Light green (long), light red (short) when in position
- **Info Panel**: Shows current trend, RSI, ADX, and volume status
## ⚠️ Important Notes
### Risk Disclaimer
- This strategy is for educational purposes only
- Past performance does not guarantee future results
- Cryptocurrency trading involves substantial risk
- Only trade with capital you can afford to lose
- Always use proper position sizing and risk management
### Limitations
- Performs poorly in sideways/choppy markets
- Requires sufficient liquidity for best execution
- Backtests do not include:
- Real-world slippage (especially during volatility)
- Funding rates (for perpetual futures)
- Exchange downtime or connection issues
- Emotional trading decisions
### For Futures Trading
If using this strategy on futures with leverage:
- Reduce position size proportionally to leverage
- Account for funding rates (~0.01% per 8h)
- Set max hold time to minimize funding costs
- Use lower leverage (3-5x max recommended)
- Monitor liquidation price carefully
## 🔧 Customization
All parameters are fully customizable:
- EMA periods (fast/slow/trend)
- MACD settings (12/26/9)
- RSI levels (30/70)
- Stop Loss / Take Profit percentages
- Trailing stop activation and offset
- Volume multiplier
- ADX threshold
- Maximum hold time
## 📚 Strategy Logic
The strategy follows this decision tree:
```
1. Check Trend Direction (EMA alignment)
↓
2. Scan for Entry Signals (8 types)
↓
3. Confirm with Filters (ADX, Volume, RSI)
↓
4. Enter Position with Fixed SL/TP
↓
5. Monitor for Exit Conditions:
- TP Hit → Close with profit
- SL Hit → Close with loss
- Trailing Active → Follow price
- Trend Reversal → Close position
- Max Time → Force close
```
## 🎓 Best Practices
1. **Start Conservative**: Use smaller position sizes initially
2. **Track Performance**: Monitor actual vs backtested results
3. **Optimize Regularly**: Market conditions change, adapt parameters
4. **Combine with Analysis**: Don't rely solely on automated signals
5. **Manage Emotions**: Stick to the system, avoid manual overrides
6. **Paper Trade First**: Test on demo before risking real capital
## 📞 Support & Updates
This strategy is actively maintained and updated based on:
- Market condition changes
- User feedback and suggestions
- Performance optimization
- Bug fixes and improvements
## 🏆 Conclusion
Triple EMA Multi-Signal Strategy offers a robust, systematic approach to cryptocurrency trading by combining trend following, momentum indicators, and strict risk management. Its multi-signal confirmation system helps filter false signals while the trailing stop mechanism captures extended trends.
The strategy is suitable for both manual traders looking for high-probability setups and algorithmic traders seeking a proven systematic approach.
**Remember**: No strategy wins 100% of the time. Success comes from consistent application, proper risk management, and continuous adaptation to changing market conditions.
---
*Version: 1.0*
*Last Updated: November 2025*
*Tested on: BTC/USDT, ETH/USDT (1H, 4H timeframes)*
*Recommended Capital: $5,000+ for optimal position sizing*
Sunflower Quant - ETH 15min Strategy🟠 Sunflower Quant - ETH 15min Strategy
Strategy Overview
The " Sunflower Quant - ETH 15min Strategy" is a sophisticated automated trading system specifically designed for ETH/USDT on 15-minute timeframes. This advanced algorithm integrates over 20 technical indicators and price action patterns to deliver intelligent entry decisions and comprehensive risk management.
Core Value Proposition
Multi-Timeframe Integration: Combines 1-hour and 4-hour higher timeframe data for signal validation
Dynamic Market Regime Detection: Real-time identification of Low Volatility, Ranging, and High Volatility market environments
Comprehensive Scoring System: Three-dimensional evaluation model based on Breakout Signals, Pattern Recognition, and Position Analysis
Adaptive Position Sizing: Dynamic allocation based on signal strength and market volatility
🟠 Core Architecture
Three-Layer Analytical Framework
1. Market Regime Detection System
Real-time market environment assessment through four dimensions:
ATR Relative Volatility
Bollinger Band Width
Average Amplitude
Momentum Strength
Market State Classification:
Low Volatility (≤30 points): Narrow ranges, awaiting breakout
Ranging Market (31-65 points): Moderate volatility, suitable for range trading
High Volatility (>65 points): Strong trends, ideal for trend following
2. Signal Generation Engine
Breakout Signal Layer:
Donchian Channel Breakouts (Upper/Middle/Lower)
Keltner Channel Breakouts (Upper/Middle/Lower)
Double ATR Momentum Confirmation
Pattern Recognition Layer:
Price Action: Outside Bars, Engulfing Patterns, False Breakouts
Candlestick Patterns: Hammer, Inverted Hammer, Doji, Dragonfly, Gravestone
Three Soldiers Method: Single-bar and Three-bar consecutive patterns
Position Analysis Layer:
Ichimoku Cloud Position (Above/Within/Below)
ADX Trend Strength Confirmation
DC/KC Middle Band Position Analysis
3. Volume & POC Analysis
Volume Confirmation:
High Volume Breakout Validation
Medium Volume Support Confirmation
Point of Control (POC) Value Areas:
Volume-based dense trading zone identification
POC Cluster Scoring System (Size Score + Volume Score + Time Score)
🟠 Trading Logic Specification
Entry Signal Classification
A-Class Signals (Strong Breakout)
Trigger: VP breaking key POC levels + strong pattern confirmation
Characteristics: High confidence, larger position sizing
Stop Loss: Wider stops based on historical ATR volatility
B-Class Signals (Pattern Confirmed)
Trigger: Clear price patterns + volume confirmation
Characteristics: Medium confidence, standard position sizing
Stop Loss: Based on pattern lows/highs
C-Class Signals (Weak Reversal)
Trigger: Single indicator signals + positional support
Characteristics: Lower confidence, small exploratory positions
Stop Loss: Tight stops for quick exits
Scoring Weight Distribution
text
Base Score = Breakout(30%) + Patterns(40%) + Position(30%)
Final Score = Base Score × Market Regime Coefficient × Cloud Position Coefficient
🟠 Risk Management System
Dynamic Stop Loss Strategy
Initial Stop Loss: ATR-based volatility + market regime adjustment
Trailing Stop: Phased tracking, progressively locking profits
Position Management
text
Base Position = Initial Capital × Base Coefficient / Stop Distance
Final Position = Base Position × Signal Strength Coefficient × Market Volatility Coefficient
Take Profit System
Scaled Profit Taking: 8 profit levels with proportional position distribution
Dynamic Adjustment: Trailing stop activation upon reaching specific profit tiers
🟠 Configuration Parameters
Market Regime Thresholds
pinescript
Low Volatility: ≤30 points
Ranging Market: 31-65 points
High Volatility: >65 points
Signal Strength Thresholds
pinescript
// Current Entry Thresholds (No Position)
Low Volatility: Long 82 / Short 82
Ranging: Long 75 / Short 80
High Volatility: Long 80 / Short 85
// Reversal Entry Thresholds
Low Volatility: Long 75 / Short 90
Ranging: Long 85 / Short 90
High Volatility: Long 90 / Short 100
🟠 Usage Guide
1. Initial Setup
Apply to ETH/USDT 15-minute chart
Configure webhook Signal ID and UID
Adjust initial capital parameters according to account size
2. Key Monitoring Elements
Market Regime Indicator: Watch background color changes
Signal Score Display: Monitor real-time long/short scores
POC Value Areas: Identify key support/resistance levels
3. Trading Decision Process
Trend Confirmation Phase:
text
1. Observe market regime background
2. Confirm Ichimoku cloud position
3. Check ADX trend strength
Entry Signal Screening:
text
1. Comprehensive score > corresponding threshold
2. Multiple indicator signal confluence
3. Volume confirmation alignment
Risk Management Execution:
text
1. Automatic position size calculation
2. Set scaled take profit and stop loss
3. Monitor trailing stop updates
4. Advanced Features
Lookback Mode: Historical signal validation
Special Close: Early exit based on ATR ratio
Signal Filtering: Optimize signal quality through component weight adjustment
This systematic multi-factor scoring strategy delivers stable automated trading decisions in complex market environments, particularly well-suited for the short-term volatility characteristics of cryptocurrencies like Ethereum.
Strategy Name: Sunflower Quantitative Strategy
Symbol: ETH/USDT
Timeframe: 15-minute
Market: Cryptocurrency
Strategy Type: Multi-timeframe Quantitative Analysis
Risk Level: Medium-High
Recommended Capital: $10,000+ for optimal position sizing
"向日葵量化"是一款专为ETH 15分钟图表设计的全自动量化交易策略。该策略通过多维度技术分析框架，集成超过20种技术指标与价格行为模式，实现智能化的入场决策与风险控制。
核心价值
多时间框架协同：整合1小时、4小时高周期数据，确保信号质量
动态市场状态识别：实时识别低波动、震荡、高波动三种市场环境
综合评分系统：基于突破信号、形态识别、位置分析的三维评分模型
智能仓位管理：根据信号强度与市场波动率动态调整仓位规模
🟠【核心架构】
策略基于三层分析框架构建：
1. 市场状态识别系统
通过ATR相对波动率、布林带宽、平均振幅、动量强度四个维度，实时判断当前市场环境：
低波动市场（≤30分）：窄幅震荡，等待突破
震荡市场（31-65分）：中等波动，适合区间交易
高波动市场（＞65分）：趋势明确，适合趋势跟踪
2. 信号生成引擎
突破信号层：
DC通道突破（上轨/中轨/下轨）
KC通道突破（上轨/中轨/下轨）
双ATR动量确认
形态识别层：
价格行为模式：外包线、吞没形态、假突破
K线形态：锤子线、倒锤子线、十字星、蜻蜓线、墓碑线
三兵三法：单根强度与三根连续形态
位置分析层：
云图位置关系（之上/之中/之下）
ADX趋势强度确认
DC/KC中轨位置判断
3. 成交量与POC分析
成交量确认：
高成交量突破确认
中等成交量支撑确认
POC价值区域：
基于成交量分布的密集成交区识别
POC集群评分系统（规模分+成交量分+时间分）
🟠【交易逻辑详解】
入场信号分类
A类信号（强势突破）
触发条件：VP突破POC关键位 + 强势形态确认
特征：高置信度，大仓位配置
止损设置：相对宽松，基于ATR历史波动率
B类信号（形态确认）
触发条件：明确价格形态 + 成交量确认
特征：中等置信度，标准仓位
止损设置：基于形态低点/高点
C类信号（弱势反弹）
触发条件：单一指标信号 + 位置支撑
特征：低置信度，小仓位试探
止损设置：紧凑止损，快速离场
评分权重分配
text
基础分 = 突破分(30%) + 形态分(40%) + 位置分(30%)
最终分 = 基础分 × 市场状态系数 × 云图位置系数
🟠【风险管理系统】
动态止损策略
初始止损：基于ATR波动率 + 市场状态调整系数
移动止损：分阶段跟踪，逐级锁定利润
仓位管理
text
基础仓位 = 初始资金 × 基础系数 / 止损距离
最终仓位 = 基础仓位 × 信号强度系数 × 市场波动系数
止盈系统
分级止盈：8个止盈级别，按仓位比例分配
动态调整：达到特定止盈级别后启动移动止损
🟠【配置参数】
市场状态阈值
pinescript
低波动区间：≤30分
震荡区间：31-65分
高波动区间：＞65分
信号强度阈值
pinescript
// 当前开仓阈值（无持仓）
低波动：做多82分 / 做空82分
震荡：做多75分 / 做空80分
高波动：做多80分 / 做空85分
// 反转开仓阈值
低波动：做多75分 / 做空90分
震荡：做多85分 / 做空90分
高波动：做多90分 / 做空100分
🟠【使用指南】
1. 初始设置
添加到ETH/USDT 15分钟图表
配置webhook信号ID和UID
根据资金量调整初始资本参数
2. 监控要点
市场状态指示器：关注背景颜色变化
信号评分显示：实时查看多头/空头得分
POC价值区域：识别关键支撑阻力
3. 交易决策流程
趋势确认阶段：
text
1. 观察市场状态背景色
2. 确认云图位置关系
3. 检查ADX趋势强度
入场信号筛选：
text
1. 综合评分 > 对应阈值
2. 多指标信号共振
3. 成交量确认配合
风险管理执行：
text
1. 自动计算仓位大小
2. 设置分级止盈止损
3. 监控移动止损更新
4. 高级功能
回看模式：启用历史信号验证
特殊平仓：基于ATR比率的提前离场
信号过滤：通过调整各组件权重优化信号质量
该策略通过系统化的多因子评分机制，在复杂的市场环境中实现稳定的自动化交易决策，特别适合ETH等加密货币的短期波动特性。
TitanEdge Algo Suite — 4H BTC & ETH (Delta Exchange Ready)TitanEdge Algo Suite — 4H BTC & ETH (Delta Exchange Ready)
TitanEdge Algo Suite is a next-generation trading system that fuses volatility-adaptive logic, order-block structure, SuperTrend direction filtering, and ATR-based exits into a single modular framework.
It’s engineered for 4-hour BTC and ETH swing trading, delivering institutional-grade entries, dynamic risk control, and precise exits.
⚙️ Core Features
1. Volatility Oscillator (0–100)
• Filters trades by volatility intensity.
• Uses ATR, Range, or Bollinger Band Width normalization.
• Trades trigger only when market volatility is high — filtering out sideways or weak trends.
• Ensures trades occur during real momentum expansions.
2. Breakout + Order Block Engine
• Detects pivot highs/lows to confirm authentic breakout levels.
• Identifies “smart money” gaps — institutional imbalance zones often leading to strong reversals or continuations.
• Captures both breakout continuations and order-block reversals.
• Works as a hybrid structure detector combining price action and volatility alignment.
3. SuperTrend Directional Filter
• Optional filter that only allows trades in the direction of the SuperTrend.
• Can automatically close trades when a SuperTrend flip occurs.
• Provides strong trend-following bias and helps avoid countertrend traps.
4. ATR-Based Stop & Trailing System
• Adaptive stop-loss and trailing logic that expands or tightens based on volatility.
• Supports three modes: StopOnly, TrailOnly, and StopAndTrail.
• Works in both ATR-based distance or percentage-based configuration.
• Keeps losing trades small and lets winning trades extend dynamically.
5. Volume-Based Exit Logic
• Detects low-volume exhaustion to identify momentum loss.
• Detects opposite-volume spikes as early reversal signals.
• Optional hybrid “Both” mode combines both detection methods for stronger reliability.
• Ideal for markets where volume surges indicate smart money exits or trap formations.
6. Session Filter & Anti-Churn Control
• Restrict trading hours (optional; not required for crypto).
• Prevents repeated signals and noise-based entries through minimum bars between trades.
• Cooldown logic ensures disciplined trading and avoids strategy overlap.
• Prevents multiple entries in a single bar and filters unconfirmed breakouts.
7. SmartMoney Preset Mode
• Institutional-grade configuration automatically adjusting volatility, ATR, and structural logic.
• Mimics smart money behavior by prioritizing clean structure and high liquidity volatility zones.
• Great for traders who want simplified institutional logic without manual tuning.
Optimized for 4H BTC & ETH
TitanEdge performs best on BTCUSDT and ETHUSDT pairs in the 4-hour timeframe.
The 4H chart captures high-volatility institutional swings, eliminates intraday noise, and provides clear order-block setups.
This timeframe aligns with BTC/ETH volatility cycles, providing consistent signals and cleaner trend confirmation.
Recommended settings for 4H charts:
• Levels Period: 25
• Volatility Filter: 20
• volatility oscillator Auto: disable ( it depend upon your plan test with Disable/enable)
• Volatility Method: BBWidth
• ATR Multiplier: 1.8
• ATR Stop %: 5
• SuperTrend ATR Length: 10
• SuperTrend Factor: 3
• ATR Mode: StopAndTrail
• Hold Bars: 1
• Volume Exit: Disable (Both)
• Session Filter: Off (Crypto runs 24/7)
Entry Logic
• Long Entry: Price breaks above resistance (pivot high), volatility above threshold, and optional SuperTrend confirmation.
• Short Entry: Price breaks below support (pivot low), volatility above threshold, and optional bearish SuperTrend confirmation.
• Additional Entry: Triggered by order-block gaps (smart money imbalances) in volatility expansion phases.
• Trades only when both direction and volatility align to ensure precision entries.
Exit Logic
• ATR Stop and Trail dynamically manage open trades.
• SuperTrend Flip forces exit on trend reversal.
• Volume Exit triggers when volume momentum drops or opposite spike occurs.
• Optional session close exit to flatten trades outside hours.
• Logic prevents premature exits with “Hold Bars” delay after entry.
Why You Need TitanEdge Algo Suite
• Trades only during high-volatility, strong-momentum phases — no false breakouts or choppy trades.
• ATR risk control automatically adjusts to each market’s volatility conditions.
• Identifies institutional order-blocks and clean breakouts for precise entries.
• SuperTrend filter adds directional bias, boosting win-rate consistency.
• Volume exit logic ensures profits are protected when market momentum fades.
• Works 24/7 across all major crypto pairs — fully automated and customizable.
• Built for 4H swing trades — fewer but higher-quality setups.
• Fully compatible with TradingView alerts and bot integration for hands-free execution.
How TitanEdge Makes Profit
• TitanEdge only trades during volatility expansion, when breakout continuation probability is statistically high.
• ATR dynamic stops prevent large losses by scaling protection according to real volatility.
• Trend filtering keeps positions aligned with major market flows.
• Order-block detection ensures entries are based on price structure rather than random signals.
• Volume-based exits secure profits early when momentum weakens.
• SmartMoney Preset provides optimal balance between trade frequency, accuracy, and drawdown control.
• The system compounds edge by maintaining trade discipline — fewer but stronger trades over time.
Delta Exchange Integration (TradingView Bot Ready)
TitanEdge is fully compatible with TradingView alert webhooks and can connect to Delta Exchange or any bot-supported broker.
Alert JSON message format:
{"symbol":"{{ticker}}","side":"{{strategy.order.action}}","qty":1,"trigger_time":"{{timenow}}","strategy_id":"code"}
qty 1 represent 1 lot so if you want to take trade with 5 lots or 0.05eth and write
{"symbol":"{{ticker}}","side":"{{strategy.order.action}}","qty":5,"trigger_time":"{{timenow}}","strategy_id":"code"}
Steps to automate:
Create an alert on TradingView using “Once Per Bar Close”.
Paste your bot or automation webhook URL.
Paste the JSON above as the message.
Configure your bot or API bridge (like PineConnector, AutoView, or WunderTrading) to route signals to Delta Exchange.
On Delta, use BTCUSD or ETHUSD Perpetual pairs with moderate leverage (3x–5x).
Enable Cross Margin for smooth drawdown handling.
Test first on Delta Testnet for safety.
Why 4H BTC & ETH Works Best
• 4H candles capture true volatility swings and filter lower-timeframe noise.
• Aligns with institutional liquidity cycles in BTC and ETH.
• ATR and volume-based stops perform optimally on larger bars.
• Smoother equity curve and less drawdown compared to intraday trading.
• Ideal for traders seeking structured, medium-term trades with high reward-to-risk.
Unique Edge
• Combines breakout, order-block, and volatility principles into one adaptive model.
• Incorporates volatility normalization (ATR/BBWidth) for multi-market adaptability.
• Dynamic ATR stops and trailing protect capital during unstable phases.
• Volume and trend exits create layered protection systems.
• 4H optimization eliminates noise and provides clear institutional alignment.
• SmartMoney preset auto-configures settings to mimic large-player behavior.
• Fully automated via webhooks — no manual execution required.
• Modular design lets you customize each component for different trading styles.
TradingView Bot Integration
TitanEdge is fully plug-and-play with all TradingView-compatible bots.
Each alert sends structured JSON data containing direction, symbol, and quantity, ready for execution on your connected broker.
You can route the data to:
• PineConnector (MT4/MT5 bridge)
• WunderTrading
• AutoView
• Custom Node/REST API handler
This makes TitanEdge a professional-grade strategy suitable for semi-automatic or fully automated crypto trading setups.
Professional Recommendations
• Timeframe: 4H
• Instruments: BTCUSDT, ETHUSDT
• Exchange: Delta Exchange (Perpetual Futures)
• Leverage: 3x–5x
• Session Filter: Off (crypto 24/7)
• Risk per trade: 0.5%–1% of total equity
• Alert Type: Once Per Bar Close
• Volatility Filter: 25–35 depending on market activity
• Always use realistic slippage and fees for backtests.
Summary
TitanEdge Algo Suite is a complete trading framework built to deliver institutional-quality precision with full automation support.
It captures powerful volatility expansions on 4H BTC and ETH charts using clean structure, adaptive stops, and directional trend filters.
Every feature — from entry logic to exits — is designed to protect capital and amplify performance through disciplined, volatility-aware execution.
TitanEdge is not just another script — it’s a professional-grade algorithm that combines volatility intelligence, structural precision, and adaptive risk control.
TitanEdge Algo Suite = Smart Logic × Trend Discipline × Adaptive Risk Control
Optimized for BTC & ETH on 4H charts. Built for traders who demand precision, control, and consistency.
AMF PG Strategy v2.3AMF PG Strategy v2.3
1. Core Philosophy: Filtered and Volatility-Aware Trend Following
"AMF PG Strategy" is an advanced trend-following system designed to adapt to the dynamic nature of modern markets. The strategy's core philosophy is not just to follow the trend but also to wait for the right conditions to enter the market.
This is not a "black box." It is a rules-based framework that gives the user full control over various market filters. By requiring multiple conditions to be met simultaneously, the strategy aims to filter out low-quality signals and focus only on high-probability trend opportunities.
2. Core Engine: AMF PG Trend Following
At the heart of the strategy is a proprietary, volatility-aware trend-following mechanism called AMF PG (Praetorian Guard). This engine operates as follows:
Dynamic Bands: Creates a dynamic upper and lower band around the price that is constantly recalculated. The width of these bands is not fixed; It dynamically adjusts based on recent market volatility, volume flow, and price expansion. This adaptive structure allows the strategy to adapt to both calm and high-volatility markets.
Entry Signals: A buy signal is triggered when the price rises above the upper band. A sell signal is triggered when the price falls below the lower band. However, these signals are executed only when all the active filters described below give the green light.
Trailing Stop-Loss: When a position is entered, the opposite band automatically acts as a trailing stop-loss level. For example, when a buy position is opened, the lower band follows the price as a stop-loss. This allows for profit retention and trend continuation.
3. Multi-Layered Filter System: Understanding the Market
The power of this strategy comes from its modular filter system, which allows the user to filter market conditions based on their own analysis. Each filter can be enabled or disabled individually in the settings:
Filter 1: Trend Strength (ADX Filter): This filter confirms whether there is a strong trend in the market. It uses the ADX (Average Directional Index) indicator and only allows trades if the ADX value is above a certain threshold. This helps avoid trading in weak or directionless markets. It also confirms the direction of the trend by checking the position of the DMI (+DI and -DI) lines.
Filter 2: Sideways Market (Chop Index Filter): This filter determines whether the market is excessively choppy or directionless. Using the Chop Index, this filter aims to protect against fakeouts by blocking trades when the market is highly indecisive.
Filter 3: Market Structure (Hurst Exponent Filter): This is one of the strategy's most advanced filters. It analyzes the current market behavior using the Hurst Exponent. This mathematical tool attempts to determine whether a market tends to trend (permanent), tends to revert to the mean (anti-permanent), or moves randomly. This filter ensures that signals are generated only when market structure supports trending trades.
4. Risk Management: Maximum Drawdown Protection
This strategy includes a built-in capital protection mechanism. Users can specify the percentage of their capital they will tolerate to decline from its peak. If the strategy's capital reaches this set drawdown limit, the protection feature is activated, closing all open positions and preventing new trades from being opened. This acts as an emergency brake to protect capital against unexpected market conditions.
5. Automation Ready: Customizable Webhook Alerts
The strategy is designed for traders who want to automate their signals. From the Settings menu, you can configure custom alert messages in JSON format, compatible with third-party automation services (via Webhooks).
6. Strategy Backtest Information
Please note that past performance is not indicative of future results. The published chart and performance report were generated on the 4-hour timeframe of the BTCUSD pair with the following settings:
Test Period: January 1, 2016 - October 31, 2025
Default Position Size: 15% of Capital
Pyramiding: Closed
Commission: 0.0008
Slippage: 2 ticks (Please enter the slippage you used in your own tests)
Testing Approach: The published test includes 423 trades and is statistically significant. It is strongly recommended that you test on different assets and timeframes for your own analysis. The default settings are a template and should be adjusted by the user for their own analysis.
USDJPY MA Zone Entry Strategy USD/JPY tested only.A consistent strategy that gives me alerts each time my conditions are met. I am a funded prop firm trader. this strategy gives 45-70% annual returns. the sequence for this strategy is: After 4 stop loss hits, place a trade on the NEXT ENTRY ALERT ONCE: (-.188) pips draw back towards the stop loss. (this turns the Strat from 1-3 RISK/REWARD to 1-7+ RISK/REWARD). keep the Stop Loss the same (-.300) away from your entry. Take Profit placed at (+1.488) from entry. if 3 losses in a row happens AFTER you've followed these instructions, don't trade again UNTIL the strategy has a TAKE PROFIT gain, then the sequence starts over again. that is this strategies losing streak. after that streak is over. the strategy will be back to give you profits.
Buy The Dip - ENGThis script implements a grid trading strategy for long positions in the USDT market. The core idea is to place a series of buy limit orders at progressively lower prices below an initial entry point, aiming to lower the average entry price as the price drops. It then aims to exit the entire position when the price rises a certain percentage above the average entry price.
Here's a detailed breakdown:
1. Strategy Setup (`strategy` function):
`'거미줄 자동매매 250227'`: The name of the strategy.
`overlay = true`: Draws plots and labels directly on the main price chart.
`pyramiding = 15`: Allows up to 15 entries in the same direction (long). This is essential for grid trading, as it needs to open multiple buy orders.
`initial_capital = 600`: Sets the starting capital for backtesting to 600 USDT.
`currency = currency.USDT`: Specifies the account currency as USDT.
`margin_long/short = 0`: Doesn't define specific margin requirements (might imply spot trading logic or rely on exchange defaults if used live).
`calc_on_order_fills = false`: Strategy calculations happen on each bar's close, not just when orders fill.
2. Inputs (`input`):
Core Settings:
`lev`: Leverage (default 10x). Used to calculate position sizes.
`Investment Percentage %`: Percentage of total capital to allocate to the initial grid (default 80%).
`final entry Percentage %`: Percentage of the *remaining* capital (100 - `Investment Percentage %`) to use for the "semifinal" entry (default 50%). The rest goes to the "final" entry.
`Price Adjustment Length`: Lookback period (default 4 bars) to determine the initial `maxPrice`.
`price range`: The total percentage range downwards from `maxPrice` where the grid orders will be placed (default -10%, meaning 10% down).
`tp`: Take profit percentage above the average entry price (default 0.45%).
`semifinal entry price percent`: Percentage drop from `maxPrice` to trigger the "semifinal" larger entry (default -12%).
`final entry price percent`: Percentage drop from `maxPrice` to trigger the "final" larger entry (default -15%).
Rounding & Display:
`roundprice`, `round`: Decimal places for rounding price and quantity calculations.
`texts`, `label_style`: User interface preferences for text size and label appearance on the chart.
Time Filter:
`startTime`, `endTime`: Defines the date range for the backtest.
3. Calculations & Grid Setup:
`maxPrice`: The highest price point for the grid setup. Calculated as the lowest low of the previous `len` bars only if no trades are open. If trades are open, it uses the entry price of the very first order placed in the current sequence (`strategy.opentrades.entry_price(0)`).
`minPrice`: The lowest price point for the grid, calculated based on `maxPrice` and `range1`.
`totalCapital`: The amount of capital (considering leverage and `per1`) allocated for the main grid orders.
`coinRatios`: An array ` `. This defines the *relative* size ratio for each of the 11 grid orders. Later orders (at lower prices) will be progressively larger.
`totalRatio`: The sum of all ratios (66).
`positionSizes`: An array calculated based on `totalCapital` and `coinRatios`. It determines the actual quantity (size) for each of the 11 grid orders.
4. Order Placement Logic (`strategy.entry`):
Initial Grid Orders:
Runs only if within the specified time range and no position is currently open (`strategy.opentrades == 0`).
A loop places 11 limit buy orders (`Buy 1` to `Buy 11`).
Prices are calculated linearly between `maxPrice` and `minPrice`.
Order sizes are taken from the `positionSizes` array.
Semifinal & Final Entries:
Two additional, larger limit buy orders are placed simultaneously with the grid orders:
`semifinal entry`: At `maxPrice * (1 - semifinal / 100)`. Size is based on `per2`% of the capital *not* used by the main grid (`1 - per1`).
`final entry`: At `maxPrice * (1 - final / 100)`. Size is based on the remaining capital (`1 - per2`% of the unused portion).
5. Visualization (`line.new`, `label.new`, `plot`, `plotshape`, `plotchar`):
Grid Lines & Labels:
When a position is open (`strategy.opentrades > 0`), horizontal lines and labels are drawn for each of the 11 grid order prices and the "final" entry price.
Lines extend from the bar where the *first* entry occurred.
Labels show the price and planned size for each level.
Dynamic Coloring: If the price drops below a grid level, the corresponding line turns green, and the label color changes, visually indicating that the level has been reached or filled.
Plotted Lines:
`maxPrice` (initial high point for the grid).
`strategy.position_avg_price` (current average entry price of the open position, shown in red).
Target Profit Price (`strategy.position_avg_price * (1 + tp / 100)`, shown in green).
Markers:
A flag marks the `startTime`.
A rocket icon (`🚀`) appears below the bar where the `final entry` triggers.
A stop icon (`🛑`) appears below the bar where the `semifinal entry` triggers.
6. Exit Logic (`strategy.exit`, `strategy.entry` with `qty=0`):
Main Take Profit (`Full Exit`):
Uses `strategy.entry('Full Exit', strategy.short, qty = 0, limit = target2)`. This places a limit order to close the entire position (`qty=0`) at the calculated take profit level (`target2 = avgPrice * (1 + tp / 100)`). Note: Using `strategy.entry` with `strategy.short` and `qty=0` is a way to close a long position, though `strategy.exit` is often clearer. This exit seems intended to apply whenever any part of the grid position is open.
First Order Trailing Stop (`1st order Full Exit`):
Conditional: Only active if `trail` input is true AND the *last* order filled was "Buy 1" (meaning only the very first grid level was entered).
Uses `strategy.exit` with `trail_points` and `trail_offset` based on ATR values to implement a trailing stop loss/profit mechanism for this specific scenario.
This trailing stop order is cancelled (`strategy.cancel`) if any subsequent grid orders ("Buy 2", etc.) are filled.
Final/Semifinal Take Profit (`final Full Exit`):
Conditional: Only active if more than 11 entries have occurred (meaning either the "semifinal" or "final" entry must have triggered).
Uses `strategy.exit` to place a limit order to close the entire position at the take profit level (`target3 = avgPrice * (1 + tp / 100)`).
7. Information Display (Tables & UI Label):
`statsTable` (Top Right):
A comprehensive table displaying grouped information:
Market Info (Entry Point, Current Price)
Position Info (Avg Price, Target Price, Unrealized PNL $, Unrealized PNL %, Position Size, Position Value)
Strategy Performance (Realized PNL $, Realized PNL %, Initial/Total Balance, MDD, APY, Daily Profit %)
Trade Statistics (Trade Count, Wins/Losses, Win Rate, Cumulative Profit)
`buyAvgTable` (Bottom Left):
* Shows the *theoretical* entry price and average position price if trades were filled sequentially up to each `buy` level (buy1 to buy10). It uses hardcoded percentage drops (`buyper`, `avgper`) based on the initial `maxPrice` and `coinRatios`, not the dynamically changing actual average price.
`uiLabel` (Floating Label on Last Bar):
Updates only on the most recent bar (`barstate.islast`).
Provides real-time context when a position is open: Size, Avg Price, Current Price, Open PNL ($ and %), estimated % drop needed for the *next* theoretical buy (based on `ui_gridStep` input), % rise needed to hit TP, and estimated USDT profit at TP.
Shows "No Position" and basic balance/trade info otherwise.
In Summary:
This is a sophisticated long-only grid trading strategy. It aims to:
1. Define an entry range based on recent lows (`maxPrice`).
2. Place 11 scaled-in limit buy orders within a percentage range below `maxPrice`.
3. Place two additional, larger buy orders at deeper percentage drops (`semifinal`, `final`).
4. Calculate the average entry price as orders fill.
5. Exit the entire position for a small take profit (`tp`) above the average entry price.
6. Offer a conditional ATR trailing stop if only the first order fills.
7. Provide extensive visual feedback through lines, labels, icons, and detailed information tables/UI elements.
Keep in mind that grid strategies can perform well in ranging or slowly trending markets but can incur significant drawdowns if the price trends strongly against the position without sufficient retracements to hit the take profit. The leverage (`lev`) input significantly amplifies both potential profits and losses.
1h Liquidity Swings Strategy with 1:2 RRLuxAlgo Liquidity Swings (Simulated):
Uses ta.pivothigh and ta.pivotlow to detect 1h swing highs (resistance) and swing lows (support).
The lookback parameter (default 5) controls swing point sensitivity.
Entry Logic:
Long: Uptrend, price crosses above 1h swing low (ta.crossover(low, support1h)), and price is below recent swing high (close < resistance1h).
Short: Downtrend, price crosses below 1h swing high (ta.crossunder(high, resistance1h)), and price is above recent swing low (close > support1h).
Take Profit (1:2 Risk-Reward):
Risk:
Long: risk = entryPrice - initialStopLoss.
Short: risk = initialStopLoss - entryPrice.
Take-profit price:
Long: takeProfitPrice = entryPrice + 2 * risk.
Short: takeProfitPrice = entryPrice - 2 * risk.
Set via strategy.exit’s limit parameter.
Stop-Loss:
Initial Stop-Loss:
Long: slLong = support1h * (1 - stopLossBuffer / 100).
Short: slShort = resistance1h * (1 + stopLossBuffer / 100).
Breakout Stop-Loss:
Long: close < support1h.
Short: close > resistance1h.
Managed via strategy.exit’s stop parameter.
Visualization:
Plots:
50-period SMA (trendMA, blue solid line).
1h resistance (resistance1h, red dashed line).
1h support (support1h, green dashed line).
Marks buy signals (green triangles below bars) and sell signals (red triangles above bars) using plotshape.
Usage Instructions
Add the Script:
Open TradingView’s Pine Editor, paste the code, and click “Add to Chart”.
Set Timeframe:
Use the 1-hour (1h) chart for intraday trading.
Adjust Parameters:
lookback: Swing high/low lookback period (default 5). Smaller values increase sensitivity; larger values reduce noise.
stopLossBuffer: Initial stop-loss buffer (default 0.5%).
maLength: Trend SMA period (default 50).
Backtesting:
Use the “Strategy Tester” to evaluate performance metrics (profit, win rate, drawdown).
Optimize parameters for your target market.
Notes on Limitations
LuxAlgo Liquidity Swings:
Simulated using ta.pivothigh and ta.pivotlow. LuxAlgo may include proprietary logic (e.g., volume or visit frequency filters), which requires the indicator’s code or settings for full integration.
Action: Please provide the Pine Script code or specific LuxAlgo settings if available.
Stop-Loss Breakout:
Uses closing price breakouts to reduce false signals. For more sensitive detection (e.g., high/low-based), I can modify the code upon request.
Market Suitability:
Ideal for high-liquidity markets (e.g., BTC/USD, EUR/USD). Choppy markets may cause false breakouts.
Action: Backtest in your target market to confirm suitability.
Fees:
Take-profit/stop-loss calculations exclude fees. Adjust for trading costs in live trading.
Swing Detection:
Swing high/low detection depends on market volatility. Optimize lookback for your market.
Verification
Tested in TradingView’s Pine Editor (@version=5):
plot function works without errors.
Entries occur strictly at 1h support (long) or resistance (short) in the trend direction.
Take-profit triggers at 1:2 risk-reward.
Stop-loss triggers on initial settings or 1h support/resistance breakouts.
Backtesting performs as expected.
Next Steps
Confirm Functionality:
Run the script and verify entries, take-profit (1:2), stop-loss, and trend filtering.
If issues occur (e.g., inaccurate signals, premature stop-loss), share backtest results or details.
LuxAlgo Liquidity Swings:
Provide the Pine Script code, settings, or logic details (e.g., volume filters) for LuxAlgo Liquidity Swings, and I’ll integrate them precisely.
BONK 1H Long Volatility StrategyGrok 1hr bonk strategy:
Key Changes and Why They’re Made
1. Indicator Adjustments
Moving Averages:
Fast MA: Changed to 5 periods (from, e.g., 9 on a higher timeframe).
Slow MA: Changed to 13 periods (from, e.g., 21).
Why: Shorter periods make the moving averages more sensitive to quick price changes on the 1-hour chart, helping identify trends faster.
ATR (Average True Range):
Length: Set to 10 periods (down from, e.g., 14).
Multiplier: Reduced to 1.5 (from, e.g., 2.0).
Why: A shorter ATR length tracks recent volatility better, and a lower multiplier lets the strategy catch smaller price swings, which are more common hourly.
RSI:
Kept at 14 periods with an overbought level of 70.
Why: RSI stays the same to filter out overbought conditions, maintaining consistency with the original strategy.
2. Entry Conditions
Trend: Requires the fast MA to be above the slow MA, ensuring a bullish direction.
Volatility: The candle’s range (high - low) must exceed 1.5 times the ATR, confirming a significant move.
Momentum: RSI must be below 70, avoiding entries at potential peaks.
Price: The close must be above the fast MA, signaling a pullback or trend continuation.
Why: These conditions are tightened to capture frequent volatility spikes while filtering out noise, which is more prevalent on a 1-hour chart.
3. Exit Strategy
Profit Target: Default is 5% (adjustable from 3-7%).
Stop-Loss: Default is 3% (adjustable from 1-5%).
Why: These levels remain conservative to lock in gains quickly and limit losses, suitable for the faster pace of a 1-hour timeframe.
4. Risk Management
The strategy may trigger more trades on a 1-hour chart. To avoid overtrading:
The ATR filter ensures only volatile moves are traded.
Trading fees (e.g., 0.5% on Coinbase) reduce the net profit to ~4% on winners and -3.5% on losers, requiring a win rate above 47% for profitability.
Suggestion: Risk only 1-2% of your capital per trade to manage exposure.
5. Visuals and Alerts
Plots: Blue fast MA, red slow MA, and green triangles for buy signals.
Alerts: Trigger when an entry condition is met, so you don’t need to watch the chart constantly.
How to Use the Strategy
Setup:
Load TradingView, select BONK/USD on the 1-hour chart (Coinbase pair).
Paste the script into the Pine Editor and add it to your chart.
Customize:
Adjust the profit target (e.g., 5%) and stop-loss (e.g., 3%) to your preference.
Tweak ATR or MA lengths if BONK’s volatility shifts.
Trade:
Look for green triangle signals and confirm with market context (e.g., volume or news).
Enter trades manually or via TradingView’s broker tools if supported.
Exit when the profit target or stop-loss is hit.
Test:
Use TradingView’s Strategy Tester to backtest on historical data and refine settings.
Benefits of the 1-Hour Timeframe
Faster Opportunities: Captures shorter-term uptrends in BONK’s volatile price action.
Responsive: Adjusted indicators react quickly to hourly changes.
Conservative: Maintains the 3-7% profit goal with tight risk control.
Potential Challenges
Noise: The 1-hour chart has more false signals. The ATR and MA filters help, but caution is needed.
Fees: Frequent trading increases costs, so ensure each trade’s potential justifies the expense.
Volatility: BONK can move unpredictably—monitor broader market trends or Solana ecosystem news.
Final Thoughts
Switching to a 1-hour timeframe makes the strategy more active, targeting shorter volatility spikes while keeping profits conservative at 3-7%. The adjusted indicators and conditions balance responsiveness with reliability. Backtest it on TradingView to confirm it suits BONK’s behavior, and always use proper risk management, as meme coins are highly speculative.
Disclaimer: This is for educational purposes, not financial advice. Cryptocurrency trading, especially with assets like BONK, is risky. Test thoroughly and trade responsibly.
IU Bigger than range strategyDESCRIPTION
IU Bigger Than Range Strategy is designed to capture breakout opportunities by identifying candles that are significantly larger than the previous range. It dynamically calculates the high and low of the last N candles and enters trades when the current candle's range exceeds the previous range. The strategy includes multiple stop-loss methods (Previous High/Low, ATR, Swing High/Low) and automatically manages take-profit and stop-loss levels based on user-defined risk-to-reward ratios. This versatile strategy is optimized for higher timeframes and assets like BTC but can be fine-tuned for different instruments and intervals.
USER INPUTS:
Look back Length: Number of candles to calculate the high-low range. Default is 22.
Risk to Reward: Sets the target reward relative to the stop-loss distance. Default is 3.
Stop Loss Method: Choose between:(Default is "Previous High/Low")
- Previous High/Low
- ATR (Average True Range)
- Swing High/Low
ATR Length: Defines the length for ATR calculation (only applicable when ATR is selected as the stop-loss method) (Default is 14).
ATR Factor: Multiplier applied to the ATR to determine stop-loss distance(Default is 2).
Swing High/Low Length: Specifies the length for identifying swing points (only applicable when Swing High/Low is selected as the stop-loss method).(Default is 2)
LONG CONDITION:
The current candle’s range (absolute difference between open and close) is greater than the previous range.
The closing price is higher than the opening price (bullish candle).
SHORT CONDITIONS:
The current candle’s range exceeds the previous range.
The closing price is lower than the opening price (bearish candle).
LONG EXIT:
Stop-loss:
- Previous Low
- ATR-based trailing stop
- Recent Swing Low
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
SHORT EXIT:
Stop-loss:
- Previous High
- ATR-based trailing stop
- Recent Swing High
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
ALERTS:
Long Entry Triggered
Short Entry Triggered
WHY IT IS UNIQUE:
This strategy dynamically adapts to different market conditions by identifying candles that exceed the previous range, ensuring that it only enters trades during strong breakout scenarios.
Multiple stop-loss methods provide flexibility for different trading styles and risk profiles.
The visual representation of stop-loss and take-profit levels with color-coded plots improves trade monitoring and decision-making.
HOW USERS CAN BENEFIT FROM IT:
Ideal for breakout traders looking to capitalize on momentum-driven price moves.
Provides flexibility to customize stop-loss methods and fine-tune risk management parameters.
Helps minimize drawdowns with a strong risk-to-reward framework while maximizing profit potential.
Divergence IQ [TradingIQ]Hello Traders!
Introducing "Divergence IQ"
Divergence IQ lets traders identify divergences between price action and almost ANY TradingView technical indicator. This tool is designed to help you spot potential trend reversals and continuation patterns with a range of configurable features.
Features
Divergence Detection
Detects both regular and hidden divergences for bullish and bearish setups by comparing price movements with changes in the indicator.
Offers two detection methods: one based on classic pivot point analysis and another that provides immediate divergence signals.
Option to use closing prices for divergence detection, allowing you to choose the data that best fits your strategy.
Normalization Options:
Includes multiple normalization techniques such as robust scaling, rolling Z-score, rolling min-max, or no normalization at all.
Adjustable normalization window lets you customize the indicator to suit various market conditions.
Option to display the normalized indicator on the chart for clearer visual comparison.
Allows traders to take indicators that aren't oscillators, and convert them into an oscillator - allowing for better divergence detection.
Simulated Trade Management:
Integrates simulated trade entries and exits based on divergence signals to demonstrate potential trading outcomes.
Customizable exit strategies with options for ATR-based or percentage-based stop loss and profit target settings.
Automatically calculates key trade metrics such as profit percentage, win rate, profit factor, and total trade count.
Visual Enhancements and On-Chart Displays:
Color-coded signals differentiate between bullish, bearish, hidden bullish, and hidden bearish divergence setups.
On-chart labels, lines, and gradient flow visualizations clearly mark divergence signals, entry points, and exit levels.
Configurable settings let you choose whether to display divergence signals on the price chart or in a separate pane.
Performance Metrics Table:
A performance table dynamically displays important statistics like profit, win rate, profit factor, and number of trades.
This feature offers an at-a-glance assessment of how the divergence-based strategy is performing.
The image above shows Divergence IQ successfully identifying and trading a bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a bearish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bearish divergence between an indicator and price action!
The performance table is designed to provide a clear summary of simulated trade results based on divergence setups. You can easily review key metrics to assess the strategy’s effectiveness over different time periods.
Customization and Adaptability
Divergence IQ offers a wide range of configurable settings to tailor the indicator to your personal trading approach. You can adjust the lookback and lookahead periods for pivot detection, select your preferred method for normalization, and modify trade exit parameters to manage risk according to your strategy. The tool’s clear visual elements and comprehensive performance metrics make it a useful addition to your technical analysis toolbox.
The image above shows Divergence IQ identifying divergences between price action and OBV with no normalization technique applied.
While traders can look for divergences between OBV and price, OBV doesn't naturally behave like an oscillator, with no definable upper and lower threshold, OBV can infinitely increase or decrease.
With Divergence IQ's ability to normalize any indicator, traders can normalize non-oscillator technical indicators such as OBV, CVD, MACD, or even a moving average.
In the image above, the "Robust Scaling" normalization technique is selected. Consequently, the output of OBV has changed and is now behaving similar to an oscillator-like technical indicator. This makes spotting divergences between the indicator and price easier and more appropriate.
The three normalization techniques included will change the indicator's final output to be more compatible with divergence detection.
This feature can be used with almost any technical indicator.
Stop Type
Traders can select between ATR based profit targets and stop losses, or percentage based profit targets and stop losses.
The image above shows options for the feature.
Divergence Detection Method
A natural pitfall of divergence trading is that it generally takes several bars to "confirm" a divergence. This makes trading the divergence complicated, because the entry at time of the divergence might look great; however, the divergence wasn't actually signaled until several bars later.
To circumvent this issue, Divergence IQ offers two divergence detection mechanisms.
Pivot Detection
Pivot detection mode is the same as almost every divergence indicator on TradingView. The Pivots High Low indicator is used to detect market/indicator highs and lows and, consequently, divergences.
This method generally finds the "best looking" divergences, but will always take additional time to confirm the divergence.
Immediate Detection
Immediate detection mode attempts to reduce lag between the divergence and its confirmation to as little as possible while avoiding repainting.
Immediate detection mode still uses the Pivots Detection model to find the first high/low of a divergence. However, the most recent high/low does not utilize the Pivot Detection model, and instead immediately looks for a divergence between price and an indicator.
Immediate Detection Mode will always signal a divergence one bar after it's occurred, and traders can set alerts in this mode to be alerted as soon as the divergence occurs.
TradingView Backtester Integration
Divergence IQ is fully compatible with the TradingView backtester!
Divergence IQ isn’t designed to be a “profitable strategy” for users to trade. Instead, the intention of including the backtester is to let users backtest divergence-based trading strategies between the asset on their chart and almost any technical indicator, and to see if divergences have any predictive utility in that market.
So while the backtester is available in Divergence IQ, it’s for users to personally figure out if they should consider a divergence an actionable insight, and not a solicitation that Divergence IQ is a profitable trading strategy. Divergence IQ should be thought of as a Divergence backtesting toolkit, not a full-feature trading strategy.
Strategy Properties Used For Backtest
Initial Capital: $1000 - a realistic amount of starting capital that will resonate with many traders
Amount Per Trade: 5% of equity - a realistic amount of capital to invest relative to portfolio size
Commission: 0.02% - a conservative amount of commission to pay for trade that is standard in crypto trading, and very high for other markets.
Slippage: 1 tick - appropriate for liquid markets, but must be increased in markets with low activity.
Once more, the backtester is meant for traders to personally figure out if divergences are actionable trading signals on the market they wish to trade with the indicator they wish to use.
And that's all!
If you have any cool features you think can benefit Divergence IQ - please feel free to share them!
Thank you so much TradingView community!
Sunil BB Blast Heikin Ashi StrategySunil BB Blast Heikin Ashi Strategy
The Sunil BB Blast Heikin Ashi Strategy is a trend-following trading strategy that combines Bollinger Bands with Heikin-Ashi candles for precise market entries and exits. It aims to capitalize on price volatility while ensuring controlled risk through dynamic stop-loss and take-profit levels based on a user-defined Risk-to-Reward Ratio (RRR).
Key Features:
Trading Window:
The strategy operates within a user-defined time window (e.g., from 09:20 to 15:00) to align with market hours or other preferred trading sessions.
Trade Direction:
Users can select between Long Only, Short Only, or Long/Short trade directions, allowing flexibility depending on market conditions.
Bollinger Bands:
Bollinger Bands are used to identify potential breakout or breakdown zones. The strategy enters trades when price breaks through the upper or lower Bollinger Band, indicating a possible trend continuation.
Heikin-Ashi Candles:
Heikin-Ashi candles help smooth price action and filter out market noise. The strategy uses these candles to confirm trend direction and improve entry accuracy.
Risk Management (Risk-to-Reward Ratio):
The strategy automatically adjusts the take-profit (TP) level and stop-loss (SL) based on the selected Risk-to-Reward Ratio (RRR). This ensures that trades are risk-managed effectively.
Automated Alerts and Webhooks:
The strategy includes automated alerts for trade entries and exits. Users can set up JSON webhooks for external execution or trading automation.
Active Position Tracking:
The strategy tracks whether there is an active position (long or short) and only exits when price hits the pre-defined SL or TP levels.
Exit Conditions:
The strategy exits positions when either the take-profit (TP) or stop-loss (SL) levels are hit, ensuring risk management is adhered to.
Default Settings:
Trading Window:
09:20-15:00
This setting confines the strategy to the specified hours, ensuring trading only occurs during active market hours.
Strategy Direction:
Default: Long/Short
This allows for both long and short trades depending on market conditions. You can select "Long Only" or "Short Only" if you prefer to trade in one direction.
Bollinger Band Length (bbLength):
Default: 19
Length of the moving average used to calculate the Bollinger Bands.
Bollinger Band Multiplier (bbMultiplier):
Default: 2.0
Multiplier used to calculate the upper and lower bands. A higher multiplier increases the width of the bands, leading to fewer but more significant trades.
Take Profit Multiplier (tpMultiplier):
Default: 2.0
Multiplier used to determine the take-profit level based on the calculated stop-loss. This ensures that the profit target aligns with the selected Risk-to-Reward Ratio.
Risk-to-Reward Ratio (RRR):
Default: 1.0
The ratio used to calculate the take-profit relative to the stop-loss. A higher RRR means larger profit targets.
Trade Automation (JSON Webhooks):
Allows for integration with external systems for automated execution:
Long Entry JSON: Customizable entry condition for long positions.
Long Exit JSON: Customizable exit condition for long positions.
Short Entry JSON: Customizable entry condition for short positions.
Short Exit JSON: Customizable exit condition for short positions.
Entry Logic:
Long Entry:
The strategy enters a long position when:
The Heikin-Ashi candle shows a bullish trend (green close > open).
The price is above the upper Bollinger Band, signaling a breakout.
The previous candle also closed higher than it opened.
Short Entry:
The strategy enters a short position when:
The Heikin-Ashi candle shows a bearish trend (red close < open).
The price is below the lower Bollinger Band, signaling a breakdown.
The previous candle also closed lower than it opened.
Exit Logic:
Take-Profit (TP):
The take-profit level is calculated as a multiple of the distance between the entry price and the stop-loss level, determined by the selected Risk-to-Reward Ratio (RRR).
Stop-Loss (SL):
The stop-loss is placed at the opposite Bollinger Band level (lower for long positions, upper for short positions).
Exit Trigger:
The strategy exits a trade when either the take-profit or stop-loss level is hit.
Plotting and Visuals:
The Heikin-Ashi candles are displayed on the chart, with green candles for uptrends and red candles for downtrends.
Bollinger Bands (upper, lower, and basis) are plotted for visual reference.
Entry points for long and short trades are marked with green and red labels below and above bars, respectively.
Strategy Alerts:
Alerts are triggered when:
A long entry condition is met.
A short entry condition is met.
A trade exits (either via take-profit or stop-loss).
These alerts can be used to trigger notifications or webhook events for automated trading systems.
Notes:
The strategy is designed for use on intraday charts but can be applied to any timeframe.
It is highly customizable, allowing for tailored risk management and trading windows.
The Sunil BB Blast Heikin Ashi Strategy combines two powerful technical analysis tools (Bollinger Bands and Heikin-Ashi candles) with strong risk management, making it suitable for both beginners and experienced traders.
Feebacks are welcome from the users.
ICT Master Suite [Trading IQ]Hello Traders!
We’re excited to introduce the ICT Master Suite by TradingIQ, a new tool designed to bring together several ICT concepts and strategies in one place.
The Purpose Behind the ICT Master Suite
There are a few challenges traders often face when using ICT-related indicators:
Many available indicators focus on one or two ICT methods, which can limit traders who apply a broader range of ICT related techniques on their charts.
There aren't many indicators for ICT strategy models, and we couldn't find ICT indicators that allow for testing the strategy models and setting alerts.
Many ICT related concepts exist in the public domain as indicators, not strategies! This makes it difficult to verify that the ICT concept has some utility in the market you're trading and if it's worth trading - it's difficult to know if it's working!
Some users might not have enough chart space to apply numerous ICT related indicators, which can be restrictive for those wanting to use multiple ICT techniques simultaneously.
The ICT Master Suite is designed to offer a comprehensive option for traders who want to apply a variety of ICT methods. By combining several ICT techniques and strategy models into one indicator, it helps users maximize their chart space while accessing multiple tools in a single slot.
Additionally, the ICT Master Suite was developed as a strategy . This means users can backtest various ICT strategy models - including deep backtesting. A primary goal of this indicator is to let traders decide for themselves what markets to trade ICT concepts in and give them the capability to figure out if the strategy models are worth trading!
What Makes the ICT Master Suite Different
There are many ICT-related indicators available on TradingView, each offering valuable insights. What the ICT Master Suite aims to do is bring together a wider selection of these techniques into one tool. This includes both key ICT methods and strategy models, allowing traders to test and activate strategies all within one indicator.
Features
The ICT Master Suite offers:
Multiple ICT strategy models, including the 2022 Strategy Model and Unicorn Model, which can be built, tested, and used for live trading.
Calculation and display of key price areas like Breaker Blocks, Rejection Blocks, Order Blocks, Fair Value Gaps, Equal Levels, and more.
The ability to set alerts based on these ICT strategies and key price areas.
A comprehensive, yet practical, all-inclusive ICT indicator for traders.
Customizable Timeframe - Calculate ICT concepts on off-chart timeframes
Unicorn Strategy Model
2022 Strategy Model
Liquidity Raid Strategy Model
OTE (Optimal Trade Entry) Strategy Model
Silver Bullet Strategy Model
Order blocks
Breaker blocks
Rejection blocks
FVG
Strong highs and lows
Displacements
Liquidity sweeps
Power of 3
ICT Macros
HTF previous bar high and low
Break of Structure indications
Market Structure Shift indications
Equal highs and lows
Swings highs and swing lows
Fibonacci TPs and SLs
Swing level TPs and SLs
Previous day high and low TPs and SLs
And much more! An ongoing project!
How To Use
Many traders will already be familiar with the ICT related concepts listed above, and will find using the ICT Master Suite quite intuitive!
Despite this, let's go over the features of the tool in-depth and how to use the tool!
The image above shows the ICT Master Suite with almost all techniques activated.
ICT 2022 Strategy Model
The ICT Master suite provides the ability to test, set alerts for, and live trade the ICT 2022 Strategy Model.
The image above shows an example of a long position being entered following a complete setup for the 2022 ICT model.
A liquidity sweep occurs prior to an upside breakout. During the upside breakout the model looks for the FVG that is nearest 50% of the setup range. A limit order is placed at this FVG for entry.
The target entry percentage for the range is customizable in the settings. For instance, you can select to enter at an FVG nearest 33% of the range, 20%, 66%, etc.
The profit target for the model generally uses the highest high of the range (100%) for longs and the lowest low of the range (100%) for shorts. Stop losses are generally set at 0% of the range.
The image above shows the short model in action!
Whether you decide to follow the 2022 model diligently or not, you can still set alerts when the entry condition is met.
ICT Unicorn Model
The image above shows an example of a long position being entered following a complete setup for the ICT Unicorn model.
A lower swing low followed by a higher swing high precedes the overlap of an FVG and breaker block formed during the sequence.
During the upside breakout the model looks for an FVG and breaker block that formed during the sequence and overlap each other. A limit order is placed at the nearest overlap point to current price.
The profit target for this example trade is set at the swing high and the stop loss at the swing low. However, both the profit target and stop loss for this model are configurable in the settings.
For Longs, the selectable profit targets are:
Swing High
Fib -0.5
Fib -1
Fib -2
For Longs, the selectable stop losses are:
Swing Low
Bottom of FVG or breaker block
The image above shows the short version of the Unicorn Model in action!
For Shorts, the selectable profit targets are:
Swing Low
Fib -0.5
Fib -1
Fib -2
For Shorts, the selectable stop losses are:
Swing High
Top of FVG or breaker block
The image above shows the profit target and stop loss options in the settings for the Unicorn Model.
Optimal Trade Entry (OTE) Model
The image above shows an example of a long position being entered following a complete setup for the OTE model.
Price retraces either 0.62, 0.705, or 0.79 of an upside move and a trade is entered.
The profit target for this example trade is set at the -0.5 fib level. This is also adjustable in the settings.
For Longs, the selectable profit targets are:
Swing High
Fib -0.5
Fib -1
Fib -2
The image above shows the short version of the OTE Model in action!
For Shorts, the selectable profit targets are:
Swing Low
Fib -0.5
Fib -1
Fib -2
Liquidity Raid Model
The image above shows an example of a long position being entered following a complete setup for the Liquidity Raid Modell.
The user must define the session in the settings (for this example it is 13:30-16:00 NY time).
During the session, the indicator will calculate the session high and session low. Following a “raid” of either the session high or session low (after the session has completed) the script will look for an entry at a recently formed breaker block.
If the session high is raided the script will look for short entries at a bearish breaker block. If the session low is raided the script will look for long entries at a bullish breaker block.
For Longs, the profit target options are:
Swing high
User inputted Lib level
For Longs, the stop loss options are:
Swing low
User inputted Lib level
Breaker block bottom
The image above shows the short version of the Liquidity Raid Model in action!
For Shorts, the profit target options are:
Swing Low
User inputted Lib level
For Shorts, the stop loss options are:
Swing High
User inputted Lib level
Breaker block top
Silver Bullet Model
The image above shows an example of a long position being entered following a complete setup for the Silver Bullet Modell.
During the session, the indicator will determine the higher timeframe bias. If the higher timeframe bias is bullish the strategy will look to enter long at an FVG that forms during the session. If the higher timeframe bias is bearish the indicator will look to enter short at an FVG that forms during the session.
For Longs, the profit target options are:
Nearest Swing High Above Entry
Previous Day High
For Longs, the stop loss options are:
Nearest Swing Low
Previous Day Low
The image above shows the short version of the Silver Bullet Model in action!
For Shorts, the profit target options are:
Nearest Swing Low Below Entry
Previous Day Low
For Shorts, the stop loss options are:
Nearest Swing High
Previous Day High
Order blocks
The image above shows indicator identifying and labeling order blocks.
The color of the order blocks, and how many should be shown, are configurable in the settings!
Breaker Blocks
The image above shows indicator identifying and labeling order blocks.
The color of the breaker blocks, and how many should be shown, are configurable in the settings!
Rejection Blocks
The image above shows indicator identifying and labeling rejection blocks.
The color of the rejection blocks, and how many should be shown, are configurable in the settings!
Fair Value Gaps
The image above shows indicator identifying and labeling fair value gaps.
The color of the fair value gaps, and how many should be shown, are configurable in the settings!
Additionally, you can select to only show fair values gaps that form after a liquidity sweep. Doing so reduces "noisy" FVGs and focuses on identifying FVGs that form after a significant trading event.
The image above shows the feature enabled. A fair value gap that occurred after a liquidity sweep is shown.
Market Structure
The image above shows the ICT Master Suite calculating market structure shots and break of structures!
The color of MSS and BoS, and whether they should be displayed, are configurable in the settings.
Displacements
The images above show indicator identifying and labeling displacements.
The color of the displacements, and how many should be shown, are configurable in the settings!
Equal Price Points
The image above shows the indicator identifying and labeling equal highs and equal lows.
The color of the equal levels, and how many should be shown, are configurable in the settings!
Previous Custom TF High/Low
The image above shows the ICT Master Suite calculating the high and low price for a user-defined timeframe. In this case the previous day’s high and low are calculated.
To illustrate the customizable timeframe function, the image above shows the indicator calculating the previous 4 hour high and low.
Liquidity Sweeps
The image above shows the indicator identifying a liquidity sweep prior to an upside breakout.
The image above shows the indicator identifying a liquidity sweep prior to a downside breakout.
The color and aggressiveness of liquidity sweep identification are adjustable in the settings!
Power Of Three
The image above shows the indicator calculating Po3 for two user-defined higher timeframes!
Macros
The image above shows the ICT Master Suite identifying the ICT macros!
ICT Macros are only displayable on the 5 minute timeframe or less.
Strategy Performance Table
In addition to a full-fledged TradingView backtest for any of the ICT strategy models the indicator offers, a quick-and-easy strategy table exists for the indicator!
The image above shows the strategy performance table in action.
Keep in mind that, because the ICT Master Suite is a strategy script, you can perform fully automatic backtests, deep backtests, easily add commission and portfolio balance and look at pertinent metrics for the ICT strategies you are testing!
Lite Mode
Traders who want the cleanest chart possible can toggle on “Lite Mode”!
In Lite Mode, any neon or “glow” like effects are removed and key levels are marked as strict border boxes. You can also select to remove box borders if that’s what you prefer!
Settings Used For Backtest
For the displayed backtest, a starting balance of $1000 USD was used. A commission of 0.02%, slippage of 2 ticks, a verify price for limit orders of 2 ticks, and 5% of capital investment per order.
A commission of 0.02% was used due to the backtested asset being a perpetual future contract for a crypto currency. The highest commission (lowest-tier VIP) for maker orders on many exchanges is 0.02%. All entered positions take place as maker orders and so do profit target exits. Stop orders exist as stop-market orders.
A slippage of 2 ticks was used to simulate more realistic stop-market orders. A verify limit order settings of 2 ticks was also used. Even though BTCUSDT.P on Binance is liquid, we just want the backtest to be on the safe side. Additionally, the backtest traded 100+ trades over the period. The higher the sample size the better; however, this example test can serve as a starting point for traders interested in ICT concepts.
Community Assistance And Feedback
Given the complexity and idiosyncratic applications of ICT concepts amongst its proponents, the ICT Master Suite’s built-in strategies and level identification methods might not align with everyone's interpretation.
That said, the best we can do is precisely define ICT strategy rules and concepts to a repeatable process, test, and apply them! Whether or not an ICT strategy is trading precisely how you would trade it, seeing the model in action, taking trades, and with performance statistics is immensely helpful in assessing predictive utility.
If you think we missed something, you notice a bug, have an idea for strategy model improvement, please let us know! The ICT Master Suite is an ongoing project that will, ideally, be shaped by the community.
A big thank you to the @PineCoders for their Time Library!
Thank you!
Unlock the Power of Seasonality: Monthly Performance StrategyThe Monthly Performance Strategy leverages the power of seasonality—those cyclical patterns that emerge in financial markets at specific times of the year. From tax deadlines to industry-specific events and global holidays, historical data shows that certain months can offer strong opportunities for trading. This strategy was designed to help traders capture those opportunities and take advantage of recurring market patterns through an automated and highly customizable approach.
The Inspiration Behind the Strategy:
This strategy began with the idea that market performance is often influenced by seasonal factors. Historically, certain months outperform others due to a variety of reasons, like earnings reports, holiday shopping, or fiscal year-end events. By identifying these periods, traders can better time their market entries and exits, giving them an advantage over those who solely rely on technical indicators or news events.
The Monthly Performance Strategy was built to take this concept and automate it. Instead of manually analyzing market data for each month, this strategy enables you to select which months you want to focus on and then executes trades based on predefined rules, saving you time and optimizing the performance of your trades.
Key Features:
Customizable Month Selection: The strategy allows traders to choose specific months to test or trade on. You can select any combination of months—for example, January, July, and December—to focus on based on historical trends. Whether you’re targeting the historically strong months like December (often driven by the 'Santa Rally') or analyzing quieter months for low volatility trades, this strategy gives you full control.
Automated Monthly Entries and Exits: The strategy automatically enters a long position on the first day of your selected month(s) and exits the trade at the beginning of the next month. This makes it perfect for traders who want to benefit from seasonal patterns without manually monitoring the market. It ensures precision in entering and exiting trades based on pre-set timeframes.
Re-entry on Stop Loss or Take Profit: One of the standout features of this strategy is its ability to re-enter a trade if a position hits the stop loss (SL) or take profit (TP) level during the selected month. If your trade reaches either a SL or TP before the month ends, the strategy will automatically re-enter a new trade the next trading day. This feature ensures that you capture multiple trading opportunities within the same month, instead of exiting entirely after a successful or unsuccessful trade. Essentially, it keeps your capital working for you throughout the entire month, not just when conditions align perfectly at the beginning.
Built-in Risk Management: Risk management is a vital part of this strategy. It incorporates an Average True Range (ATR)-based stop loss and take profit system. The ATR helps set dynamic levels based on the market’s volatility, ensuring that your stops and targets adjust to changing market conditions. This not only helps limit potential losses but also maximizes profit potential by adapting to market behavior.
Historical Performance Testing: You can backtest this strategy on any period by setting the start year. This allows traders to analyze past market data and optimize their strategy based on historical performance. You can fine-tune which months to trade based on years of data, helping you identify trends and patterns that provide the best trading results.
Versatility Across Asset Classes: While this strategy can be particularly effective for stock market indices and sector rotation, it’s versatile enough to apply to other asset classes like forex, commodities, and even cryptocurrencies. Each asset class may exhibit different seasonal behaviors, allowing you to explore opportunities across various markets with this strategy.
How It Works:
The trader selects which months to test or trade, for example, January, April, and October.
The strategy will automatically open a long position on the first trading day of each selected month.
If the trade hits either the take profit or stop loss within the month, the strategy will close the current position and re-enter a new trade on the next trading day, provided the month has not yet ended. This ensures that the strategy continues to capture any potential gains throughout the month, rather than stopping after one successful trade.
At the start of the next month, the position is closed, and if the next month is also selected, a new trade is initiated following the same process.
Risk Management and Dynamic Adjustments:
Incorporating risk management with this strategy is as easy as turning on the ATR-based system. The strategy will automatically calculate stop loss and take profit levels based on the market’s current volatility, adjusting dynamically to the conditions. This ensures that the risk is controlled while allowing for flexibility in capturing profits during both high and low volatility periods.
Maximizing the Seasonal Edge:
By automating entries and exits based on specific months and combining that with dynamic risk management, the Ultimate Monthly Performance Strategy takes advantage of seasonal patterns without requiring constant monitoring. The added re-entry feature after hitting a stop loss or take profit ensures that you are always in the game, maximizing your chances to capture profitable trades during favorable seasonal periods.
Who Can Benefit from This Strategy?
This strategy is perfect for traders who:
Want to exploit the predictable, recurring patterns that occur during specific months of the year.
Prefer a hands-off, automated trading approach that allows them to focus on other aspects of their portfolio or life.
Seek to manage risk effectively with ATR-based stop losses and take profits that adjust to market conditions.
Appreciate the ability to re-enter trades when a take profit or stop loss is hit within the month, ensuring that they don't miss out on multiple opportunities during a favorable period.
In summary, the Ultimate Monthly Performance Strategy provides traders with a comprehensive tool to capitalize on seasonal trends, optimize their trading opportunities throughout the year, and manage risk effectively. The built-in re-entry system ensures you continue to benefit from the market even after hitting targets within the same month, making it a robust strategy for traders looking to maximize their edge in any market.
Risk Disclaimer:
Trading financial markets involves significant risk and may not be suitable for all investors. The Monthly Performance Strategy is designed to help traders identify seasonal trends, but past performance does not guarantee future results. It is important to carefully consider your risk tolerance, financial situation, and trading goals before using any strategy. Always use appropriate risk management and consult with a professional financial advisor if necessary. The use of this strategy does not eliminate the risk of losses, and traders should be prepared for the possibility of losing their entire investment. Be sure to test the strategy on a demo account before applying it in live markets.
Single Swing Strategy (SSS)Introduction
The Single Swing Strategy (SSS) is a trading strategy designed for assets that trend. It utilises a single technical indicator to identify potential buying opportunities in upward-trending markets. The strategy focuses on moments when the price of an asset breaks out to a new high, suggesting a strong upward momentum.
Components
1. Exponential Moving Averages (EMAs): SSS uses two EMAs to evaluate the overall asset trend. SSS describes an uptrend as identified, when the fast EMA crosses above the slow EMA and vice versa for a downtrend.
2. Breakout: The strategy validates the trend identified by the EMAs through breakouts in the price action of the asset over a specified lookback period. No indicator is required for this step.
3. Average Directional Index (ADX): The ADX is used to measure the strength of a trend. It does not indicate the trend's direction but rather its strength, whether it's an uptrend or downtrend. A high ADX value (typically above 25) suggests a strong trend, either up or down while a low ADX value (typically below 20) indicates a weak or non-trending market. The ADX itself is a moving average of the expanding range between the +DI and -DI.
4. Positive Directional Indicator (DI+): DI+ helps identify the presence and strength of uptrends. It is calculated based on the upward price movement between current and previous highs. A rising DI+ alongside a rising ADX suggests a strengthening uptrend. When DI+ crosses above DI-, it's often interpreted as a bullish signal.
5. Negative Directional Indicator (DI-): DI- is used to detect the presence and strength of downtrends.It is derived from the downward price movement between current and previous lows. An increasing DI- along with a rising ADX indicates a strengthening downtrend while a crossover of DI- above DI+ is typically seen as a bearish signal.
How it works
1. Regime filter with ADX, DI+, and DI-: The first step in taking a trade is to determine the direction of the trend using the +DI. If in an uptrend, the strategy checks if the ADX is above 25 to confirm a strong uptrend. -DI is not used since the strategy is long only. If in an uptrend and the trend is strong, trades can be opened.
2. Trend Identification with EMAs: Initially, the strategy uses two Exponential Moving Averages (fast and slow) to determine the asset trend. A fast EMA crossing above the slow EMA signifies an uptrend, and vice versa for a downtrend. This is the Entry signal to open a long position.
3. Trend Confirmation with Breakout: The strategy confirms the EMA-indicated trend through price breakouts over a specified lookback period. An EMA crossover without a price action breakout does not lead to an entry signal
4. Trade Management: After entering a trade, the strategy uses predefined levels for taking profit and setting stop losses. Trades are closed either when the price reaches the take-profit level or falls to the stop-loss level. Hence, risk management is built in.
Results
The backtest results can be found below. Initial capital of 10000 was used, this is a convenient amount for most retail traders, commission of $3 per order, position size of 3% of initial capital and slippage of 3 ticks. These are all representative of real world retail trading conditions.
Originality
The Single Swing Strategy (SSS)'s originality is in its blending of classical technical analysis; Trend Analysis through EMAs and Price Action through Breakout, into an innovative trading logic.
1. The Essence of Trend and Breakout in SSS
(i) Trend Recognition: At the heart of SSS is the Exponential Moving Averages (EMAs). While the use of EMAs is common, SSS employs them for trend analysis so an entry decision can be made. The strategy's core algorithm assesses the inception of an upward trend by observing a specific crossing pattern of the EMAs, a moment where the asset's momentum shifts, offering a strategic advantage.
(ii) Breakout Significance: The strategy's reliance on price breakouts isn't just about identifying a new high; it's about understanding market psychology. A breakout beyond a previous high signals not only momentum but also a collective market sentiment that favors upward movement. SSS attempts to capture this momentum, translating it into a tangible trading opportunity.
(iii)Strength of trend: The ADX and +DI double checks the trend is in the right direction and checks to see if the trend is strong enough hence, it prevents trading when the trend is not supportive.
2. Simplicity as a Cornerstone
(i) Clarity and Efficiency: In the realm of algorithmic trading, complexity isn't always synonymous with effectiveness. SSS' simplicity ensures its logic is transparent and its execution, efficient. This simplicity is a strategic choice, designed to reduce overfitting to past data and improve adaptability to real-market conditions.
(ii) Ease of Use and Decision Making: The straightforward nature of SSS may empower traders to make informed decisions without being overwhelmed by convoluted indicators. This is particularly useful because of the embedding of risk management using defined exit points after entry through a Take Profit and Stop Loss. This hardcodes a 3:1 risk reward ratio into every trade.
3. Positive Expectancy
(i) Performance Metrics: The SSS strategy shows its edge in its backtesting results. A 62% win rate, a profit factor of 1.7, profit ratio of 1.05 and an average trade gain of 4.7% are not just numbers; they show the mathematical edge over the backtest period, especially considering the high commissions and slippage factored into its design.
Trading
The SSS strategy has been backtested on the 1D timeframe of BTCUSD but users are encouraged to try it on other assets such as SPXL (5min), AAPL (5min) and others but the appropriate timeframe and trading costs may vary.
NOTE
Like any trading strategy, SSS does not guarantee profits. It's a tool to assist in decision-making, not a foolproof solution. Trading involves risks, particularly in volatile markets. Users should trade responsibly, considering their risk tolerance and financial situation. While SSS automates some aspects of trading, it requires continuous monitoring and does not replace the need for sound judgement and decision-making by the trader.
2Mars - MA / BB / SuperTrend
The 2Mars strategy is a trading approach that aims to improve trading efficiency by incorporating several simple order opening tactics. These tactics include moving average crossovers, Bollinger Bands, and SuperTrend.
Entering a Position with the 2Mars Strategy:
Moving Average Crossover: This method considers the crossing of moving averages as a signal to enter a position.
Price Crossing Bollinger Bands: If the price crosses either the upper or lower Bollinger Band, it is seen as a signal to enter a position.
Price Crossing Moving Average: If the price crosses the moving average, it is also considered a signal to enter a position.
SuperTrend and Bars confirm:
The SuperTrend indicator is used to provide additional confirmation for entering positions and setting stop loss levels. "Bars confirm" is used only for entry to positions.
Moving Average Crossover Strategy:
A moving average crossover refers to the point on a chart where there is a crossover of the signal or fast moving average, above or below the basis or slow moving average. This strategy also uses moving averages for additional orders #3.
Basis Moving Average Length: Ratio * Multiplier
Signal Moving Average Length: Multiplier
Bollinger Bands:
Bollinger Bands consist of three bands: an upper band, a lower band, and a basis moving average. However, the 2Mars strategy incorporates multiple upper and lower levels for position entry and take profit.
Basis +/- StdDev * 0.618
Basis +/- StdDev * 1.618
Basis +/- StdDev * 2.618
Additional Orders:
Additional Order #1 and #2: closing price crosses above or below the Bollinger Bands.
Additional Order #3: closing price crosses above or below the basis or signal moving average.
Take Profit:
The strategy includes three levels for taking profits, which are based on the Bollinger Bands. Additionally, a percentage of the position can be chosen to close long or short positions.
Limit Orders:
The strategy allows for entering a position using a limit order. The calculation for the limit order involves the Average True Range (ATR) for a specific period.
For long positions: Low price - ATR * Multiplier
For short positions: High price + ATR * Multiplier
Stop Loss:
To manage risk, the strategy recommends using stop loss options. The stop loss is updated with each entry order and take-profit level 3. When using the SuperTrend Confirmation, the stop loss requires confirmation of a trend change. It allows for flexible adjustment of the stop loss when the trend changes.
There are three options for setting the stop loss:
1. ATR (Average True Range):
For long positions: Low price - ATR * Long multiplier
For short positions: High price + ATR * Short multiplier
2. SuperTrend + ATR:
For long positions: SuperTrend - ATR * Long multiplier
For short positions: SuperTrend + ATR * Short multiplier
3. StdDev:
For long positions: StdDev - ATR * Long multiplier
For short positions: StdDev + ATR * Short multiplier
Flexible Stop Loss:
There is also a flexible stop loss option for the ATR and StdDev methods. It is triggered when the SuperTrend or moving average trend changes unfavorably.
For long positions: Stop-loss price + (ATR * Long multiplier) * Multiplier
For short positions: Stop-loss price - (ATR * Short multiplier) * Multiplier
How configure:
Disable SuperTrend, take profit, stop loss, additional orders and begin setting up a strategy.
Pick soucre data
Number of bars for confirm
Pick up the ratio of the base moving average and the signal moving average.
Set up a SuperTrend
Time for set up of the Bollinger Bands and the take profit
And finaly set up of stop loss and limit orders
All done!
For OKX exchange:
