Obos — Indicators and Strategies — TradingView

Adaptive Valuation [BackQuant]Adaptive Valuation What this is A composite, zero-centered oscillator that standardizes several classic indicators and blends them into one “valuation” line. It computes RSI, CCI, Demarker, and the Price Zone Oscillator, converts each to a rolling z-score, then forms a weighted average. Optional smoothing, dynamic overbought and oversold bands, and an on-chart table make the inputs and the final score easy to inspect. How it works Components • RSI with its own lookback. • CCI with its own lookback. • DM (Demarker) with its own lookback. • PZO (Price Zone Oscillator) with its own lookback. Standardization via z-score Each component is transformed using a rolling z-score over lookback bars: z = (value − mean) ÷ stdev , where the mean is an EMA and the stdev is rolling. This puts all inputs on a comparable scale measured in standard deviations. Weighted blend The z-scores are combined with user weights w_rsi, w_cci, w_dm, w_pzo to produce a single valuation series. If desired, it is then smoothed with a selected moving average (SMA, EMA, WMA, HMA, RMA, DEMA, TEMA, LINREG, ALMA, T3). ALMA’s sigma input shapes its curve. Dynamic thresholds (optional) Two ways to set overbought and oversold: • Static : fixed levels at ob_thres and os_thres . • Dynamic : ±k·σ bands, where σ is the rolling standard deviation of the valuation over dynLen . Bands can be centered at zero or around the valuation’s rolling mean ( centerZero ). Visualization and UI • Zero line at 0 with gradient fill that darkens as the valuation moves away from 0. • Optional plotting of band lines and background highlights when OB or OS is active. • Optional candle and background coloring driven by the valuation. • Summary table showing each component’s current z-score, the final score, and a compact status. How it can be used • Bias filter : treat crosses above 0 as bullish bias and below 0 as bearish bias. • Mean-reversion context : look for exhaustion when the valuation enters the OB or OS region, then watch for exits from those regions or a return toward 0. • Signal confirmation : use the final score to confirm setups from structure or price action. • Adaptive banding : with dynamic thresholds, OB and OS adjust to prevailing variability rather than relying on fixed lines. • Component tuning : change weights to emphasize trend (raise DM, reduce RSI/CCI) or range behavior (raise RSI/CCI, reduce DM). PZO can help in swing environments. Why z-score blending helps Indicators often live on different scales. Z-scoring places them on a common, unitless axis, so a one-sigma move in RSI has comparable influence to a one-sigma move in CCI. This reduces scale bias and allows transparent weighting. It also facilitates regime-aware thresholds because the dynamic bands scale with recent dispersion. Inputs to know • Component lookbacks : rsilb, ccilb, dmlb, pzolb control each raw signal. • Standardization window : lookback sets the z-score memory. Longer smooths, shorter reacts. • Weights : w_rsi, w_cci, w_dm, w_pzo determine each component’s influence. • Smoothing : maType, smoothP, sig govern optional post-blend smoothing. • Dynamic bands : dyn_thres, dynLen, thres_k, centerZero configure the adaptive OB/OS logic. • UI : toggle the plot, table, candle coloring, and threshold lines. Reading the plot • Above 0 : composite pressure is positive. • Below 0 : composite pressure is negative. • OB region : valuation above the chosen OB line. Risk of mean reversion rises and momentum continuation needs evidence. • OS region : mirror logic on the downside. • Band exits : leaving OB or OS can serve as a normalization cue. Strengths • Normalizes heterogeneous signals into one interpretable series. • Adjustable component weights to match instrument behavior. • Dynamic thresholds adapt to changing volatility and drift. • Transparent diagnostics from the on-chart table. • Flexible smoothing choices, including ALMA and T3. Limitations and cautions • Z-scores assume a reasonably stationary window. Sharp regime shifts can make recent bands unrepresentative. • Highly correlated components can overweight the same effect. Consider adjusting weights to avoid double counting. • More smoothing adds lag. Less smoothing adds noise. • Dynamic bands recalibrate with dynLen ; if set too short, bands may swing excessively. If too long, bands can be slow to adapt. Practical tuning tips • Trending symbols: increase w_dm , use a modest smoother like EMA or T3, and use centerZero dynamic bands. • Choppy symbols: increase w_rsi and w_cci , consider ALMA with a higher sigma , and widen bands with a larger thres_k . • Multiday swing charts: lengthen lookback and dynLen to stabilize the scale. • Lower timeframes: shorten component lookbacks slightly and reduce smoothing to keep signals timely. Alerts • Enter and exit of Overbought and Oversold, based on the active band choice. • Bullish and bearish zero crosses. Use alerts as prompts to review context rather than as stand-alone trade commands. Final Remarks We created this to show people a different way of making indicators & trading. You can process normal indicators in multiple ways to enhance or change the signal, especially with this you can utilise machine learning to optimise the weights, then trade accordingly. All of the different components were selected to give some sort of signal, its made out of simple components yet is effective. As long as the user calibrates it to their Trading/ investing style you can find good results. Do not use anything standalone, ensure you are backtesting and creating a proper system.

Moving Average Adaptive RSI [BackQuant]Moving Average Adaptive RSI What this is A momentum oscillator that reshapes classic RSI into a zero-centered column plot and makes it adaptive. It builds RSI from two parts: • A sensitivity window that scans several recent bars to capture the strongest up and down impulses. • A selectable moving average that smooths those impulses before computing RSI. The output ranges roughly from −100 to +100 with 0 as the midline, with optional extra smoothing and built-in divergence detection. How it works Impulse extraction • For each bar the script inspects the last rsi_sen bars and collects upward and downward price changes versus the current price. • It keeps the maximum upward change and maximum downward change from that window, emphasizing true bursts over single-bar noise. MA-based averaging • The up and down impulse series are averaged with your chosen MA over rsi_len bars. • Supported MA types: SMA, EMA, DEMA, WMA, HMA, SMMA (RMA), TEMA. Zero-centered RSI transform • RS = UpMA ÷ DownMA, then mapped to a symmetric scale: 100 − 200 ÷ (1 + RS) . • Above 0 implies positive momentum bias. Below 0 implies negative momentum bias. Optional extra smoothing • A second smoothing pass can be applied to the final oscillator using smoothing_len and smooth_type . Toggle with “Use Extra Smoothing”. Visual encoding • The oscillator is drawn as columns around the zero line with a gradient that intensifies toward extremes. • Static bands mark 80 to 100 and −80 to −100 for extreme conditions. Key inputs and what they change • Price Source : input series for momentum. • Calculation Period (rsi_len) : primary averaging window on up and down components. Higher = smoother, slower. • Sensitivity (rsi_sen) : how many recent bars are scanned to find max impulses. Higher = more responsive to bursts. • Calculation Type (ma_type) : MA family that shapes the core behavior. HMA or DEMA is faster, SMA or SMMA is slower. • Smoothing Type and Length : optional second pass to calm noise on the final output. • UI toggles : show or hide the oscillator, candle painting, and extreme bands. Reading the oscillator • Midline cross up (0) : momentum bias turning positive. • Midline cross down (0) : momentum bias turning negative. • Positive territory : – 0 to 40: constructive but not stretched. – 40 to 80: strong momentum, continuation more likely. – Above 80: extreme risk of mean reversion grows. • Negative territory : mirror the same levels for the downside. Divergence detection The script plots four divergence types using pivot highs and lows on both price and the oscillator. Lookbacks are set by lbL and lbR . • Regular bullish : price lower low, oscillator higher low. Possible downside exhaustion. • Hidden bullish : price higher low, oscillator lower low. Bias to trend continuation up. • Regular bearish : price higher high, oscillator lower high. Possible upside exhaustion. • Hidden bearish : price lower high, oscillator higher high. Bias to trend continuation down. Labels: ℝ for regular, ℍ for hidden. Green for bullish, red for bearish. Candle coloring • Optional bar painting: green when the oscillator is above 0, red when below 0. This is for visual scanning only. Strengths • Adaptive sensitivity via a rolling impulse window that responds to genuine bursts. • Configurable MA core so you can match responsiveness to the instrument. • Zero-centered scale for simple regime reads with 0 as a clear bias line. • Built-in regular and hidden divergence mapping. • Flexible across symbols and timeframes once tuned. Limitations and cautions • Trends can remain extended. Treat extremes as context rather than automatic reversal signals. • Divergence quality depends on pivot lookbacks. Short lookbacks give more signals with more noise. Long lookbacks reduce noise but add lag. • Double smoothing can delay zero-line transitions. Balance smoothness and timeliness. Practical usage ideas • Regime filter : only take long setups from your separate method when the oscillator is above 0, shorts when below 0. • Pullback confirmation : in uptrends, look for dips that hold above 0 or turn up from 0 to 40. Reverse for downtrends. • Divergence as a heads-up : wait for a zero-line cross or a price trigger before acting on divergence. • Sensitivity tuning : start with rsi_sen 2 to 5 on faster timeframes, increase slightly on slower charts. Alerts • MA-A RSI Long : oscillator crosses above 0. • MA-A RSI Short : oscillator crosses below 0. Use these as bias or timing aids, not standalone trade commands. Settings quick reference • Calculation : Price Source, Calculation Type, Calculation Period, Sensitivity. • Smoothing : Smoothing Type, Smoothing Length, Use Extra Smoothing. • UI : Show Oscillator, Paint Candles, Show Static High and Low Levels. • Divergences : Pivot Lookback Left and Right, Div Signal Length, Show Detected Divergences. Final thoughts This tool reframes RSI by extracting strong short-term impulses and averaging them with a moving-average model of your choice, then presenting a zero-centered output for clear regime reads. Pair it with your structure, risk and execution process, and tune sensitivity and smoothing to the market you trade.

Parabolic RSI [ChartPrime]The Parabolic RSI indicator applies the Parabolic SAR directly to the Relative Strength Index (RSI) . This combination helps traders identify trend shifts and potential reversal points within the RSI framework. The indicator provides both regular and strong signals based on whether the Parabolic SAR crosses above or below key RSI thresholds. ⯁ KEY FEATURES Parabolic SAR Applied to RSI – Tracks momentum shifts within the RSI indicator. Dynamic SAR Dots – Plots SAR levels directly on the RSI for visual clarity. Threshold-Based Signal Filtering – Uses upper (70) and lower (30) RSI levels to determine strong signals. Simple and Strong Signal System : Big Diamonds (Strong Signals) – Appear when Parabolic SAR crosses above 70 or below 30 RSI, indicating potential reversals. Small Diamonds (Regular Signals) – Appear when Parabolic SAR flips inside the RSI range, signaling weaker trend shifts. Chart Overlay Signals – Highlights strong RSI-based trend shifts directly on the price chart. Fully Customizable – Modify RSI length, SAR parameters, colors, and signal displays. ⯁ HOW TO USE Look for strong signals (big diamonds) when SAR flips above 70 RSI (overbought) or below 30 RSI (oversold) for potential reversals. Use regular signals (small diamonds) for minor trend shifts within the RSI range. Combine with price action and other indicators to confirm entry and exit points. Adjust the SAR acceleration factors to fine-tune sensitivity based on market conditions. ⯁ CONCLUSION The Parabolic RSI indicator merges trend-following and momentum-based analysis by applying the Parabolic SAR to RSI. This allows traders to detect trend shifts inside the RSI space with an intuitive diamond-based signal system . Whether used alone or as part of a broader trading strategy, this indicator provides a clear and structured approach to identifying momentum reversals and potential trading opportunities.

TEMA OBOS Strategy Pakun TEMA OBOS Strategy Overview This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering. By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision. This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts). Strategy Objectives Identify trend direction using TEMA Use OBOS to filter out overbought/oversold conditions Implement ATR-based dynamic risk management Key Features 1. Trend Analysis Using TEMA Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries. ema4 acts as the primary trend filter. 2. Overbought/Oversold (OBOS) Filtering Long Entry Condition: up > down (bullish trend confirmed) Short Entry Condition: up < down (bearish trend confirmed) Reduces unnecessary trades by filtering extreme market conditions. 3. ATR-Based Take Profit (TP) & Stop Loss (SL) Adjustable ATR multiplier for TP/SL Default settings: TP = ATR × 5 SL = ATR × 2 Fully customizable risk parameters. 4. Customizable Parameters TEMA Length (for trend calculation) OBOS Length (for overbought/oversold detection) Take Profit Multiplier Stop Loss Multiplier EMA Display (Enable/Disable TEMA lines) Bar Color Change (Enable/Disable candle coloring) Trading Rules Long Entry (Buy Entry) ema3 crosses above ema4 (Golden Cross) OBOS indicator confirms up > down (bullish trend) Execute a buy position Short Entry (Sell Entry) ema3 crosses below ema4 (Death Cross) OBOS indicator confirms up < down (bearish trend) Execute a sell position Take Profit (TP) Entry Price + (ATR × TP Multiplier) (Default: 5) Stop Loss (SL) Entry Price - (ATR × SL Multiplier) (Default: 2) TP/SL settings are fully customizable to fine-tune risk management. Risk Management Parameters This strategy emphasizes proper position sizing and risk control to balance risk and return. Trading Parameters & Considerations Initial Account Balance: $7,000 (adjustable) Base Currency: USD Order Size: 10,000 USD Pyramiding: 1 Trading Fees: $0.94 per trade Long Position Margin: 50% Short Position Margin: 50% Total Trades (M5 Timeframe): 128 Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M Total P&L：+1638.20USD Max equity drawdown：694.78USD Total trades：128 Profitable trades:44.53 Profit factor:1.45 These settings aim to protect capital while maintaining a balanced risk-reward approach. Visual Support TEMA Lines (Three EMAs) Trend direction is indicated by color changes (Blue/Orange) ema3 (short-term) and ema4 (long-term) crossover signals potential entries OBOS Histogram Green → Strong buying pressure Red → Strong selling pressure Blue → Possible trend reversal Entry & Exit Markers Blue Arrow → Long Entry Signal Red Arrow → Short Entry Signal Take Profit / Stop Loss levels displayed Strategy Improvements & Uniqueness This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management. Enhanced Trend Identification with TEMA Detects early trend reversals using ema3 & ema4 crossover Reduces market noise for a smoother trend-following approach Improved OBOS Filtering Prevents excessive trading Reduces unnecessary risk exposure Dynamic Risk Management with ATR-Based TP/SL Not a fixed value → TP/SL adjusts to market volatility Fully customizable ATR multiplier settings (Default: TP = ATR × 5, SL = ATR × 2) Summary The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators. TEMA for trend identification OBOS for noise reduction & overbought/oversold filtering ATR-based TP/SL settings for dynamic risk management Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.

Normalised T3 Oscillator [BackQuant]Normalised T3 Oscillator The Normalised T3 Oscillator is an technical indicator designed to provide traders with a refined measure of market momentum by normalizing the T3 Moving Average. This tool was developed to enhance trading decisions by smoothing price data and reducing market noise, allowing for clearer trend recognition and potential signal generation. Below is a detailed breakdown of the Normalised T3 Oscillator, its methodology, and its application in trading scenarios. 1. Conceptual Foundation and Definition of T3 The T3 Moving Average, originally proposed by Tim Tillson, is renowned for its smoothness and responsiveness, achieved through a combination of multiple Exponential Moving Averages and a volume factor. The Normalised T3 Oscillator extends this concept by normalizing these values to oscillate around a central zero line, which aids in highlighting overbought and oversold conditions. 2. Normalization Process Normalization in this context refers to the adjustment of the T3 values to ensure that the oscillator provides a standard range of output. This is accomplished by calculating the lowest and highest values of the T3 over a user-defined period and scaling the output between -0.5 to +0.5. This process not only aids in standardizing the indicator across different securities and time frames but also enhances comparative analysis. 3. Integration of the Oscillator and Moving Average A unique feature of the Normalised T3 Oscillator is the inclusion of a secondary smoothing mechanism via a moving average of the oscillator itself, selectable from various types such as SMA, EMA, and more. This moving average acts as a signal line, providing potential buy or sell triggers when the oscillator crosses this line, thus offering dual layers of analysis—momentum and trend confirmation. 4. Visualization and User Interaction The indicator is designed with user interaction in mind, featuring customizable parameters such as the length of the T3, normalization period, and type of moving average used for signals. Additionally, the oscillator is plotted with a color-coded scheme that visually represents different strength levels of the market conditions, enhancing readability and quick decision-making. 5. Practical Applications and Strategy Integration Traders can leverage the Normalised T3 Oscillator in various trading strategies, including trend following, counter-trend plays, and as a component of a broader trading system. It is particularly useful in identifying turning points in the market or confirming ongoing trends. The clear visualization and customizable nature of the oscillator facilitate its adaptation to different trading styles and market environments. 6. Advanced Features and Customization Further enhancing its utility, the indicator includes options such as painting candles according to the trend, showing static levels for quick reference, and alerts for crossover and crossunder events, which can be integrated into automated trading systems. These features allow for a high degree of personalization, enabling traders to mold the tool according to their specific trading preferences and risk management requirements. 7. Theoretical Justification and Empirical Usage The use of the T3 smoothing mechanism combined with normalization is theoretically sound, aiming to reduce lag and false signals often associated with traditional moving averages. The practical effectiveness of the Normalised T3 Oscillator should be validated through rigorous backtesting and adjustment of parameters to match historical market conditions and volatility. 8. Conclusion and Utility in Market Analysis Overall, the Normalised T3 Oscillator by BackQuant stands as a sophisticated tool for market analysis, providing traders with a dynamic and adaptable approach to gauging market momentum. Its development is rooted in the understanding of technical nuances and the demand for a more stable, responsive, and customizable trading indicator. Thus following all of the key points here are some sample backtests on the 1D Chart Disclaimer: Backtests are based off past results, and are not indicative of the future. INDEX:BTCUSD INDEX:ETHUSD BINANCE:SOLUSD

Wavetrend strategy with trading session for any time chart Hello there Today I am glad to provide you a strategy based on the wave trend oscillator. If you want to use it as an indicator, just disable long and short to not make any shops. It works on all time frames. The way it works its like an RSI . We have overbought and oversold levels, and together with a channel and length we calculate the wave trend. And then like in RSI, when we cross those lines we buy or sell depending on which lines we cross. For risk management, so far its not implemented, but it can be done in many ways. The only thing I applied is to always close a trade at the end of friday day. At the same time it can be applied the rule to sell when % of equity is lost, or at the end of a trading session like london,neywork and so on. For any questions or doubts, let me know. Hope you enjoy it :)