Position Sizer (Share Qty)
This indicator enables fast & accurate position sizing for traders using (user defined) fixed dollar risk, eliminating the need for manual calculations and supporting disciplined risk management directly on the chart
Calculates precise share quantity for fixed-risk trades using the formula Shares = Risk Amount / (Current Price – Stop Price), rounded to the nearest whole share, updating in real time on every bar
Offers two dynamic stop-loss options: Low of Day (LoD) — tracked only during Regular Trading Hours (9:30 AM – 4:00 PM ET) with automatic daily reset — or Low of Week (LoW) via weekly timeframe data
Displays all critical trade data in a clean, customizable on-screen table showing: Risk Amount, Stop Loss type (LoD/LoW), Stop Price, and calculated Shares Qty
Allows full table placement control with four corner positions with optional Top Offset and Bottom Offset (0–20 blank rows each) to prevent overlap with price action or other indicators
Provides complete visual styling control for header text/background, value text/background, and share quantity text/background
Ensures efficient rendering by recreating the table only when position, row count, or layout changes, deleting the prior instance to avoid flicker or memory issues
Handles edge cases safely: shows 0 shares if stop is 'na' or above current price, and initializes LoD only on the first RTH bar of each session
For use on equities only (table will not display on futures instruments)
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Future improvements:
Visual Stop Loss line for either LoD or LoW
Functionality and toggle to include Extended hours (PM /AH) for LoD stop pricing
Share
The Z-score The Z-score, also known as the standard score, is a statistical measurement that describes a value's relationship to the mean of a group of values. It's measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
The concept of Z-score was introduced by statistician Carl Friedrich Gauss as part of his "method of the least squares," which was an important step in the development of the normal distribution and Z-score tables. It's a key concept in statistics and is used in various statistical tests.
In financial analysis, Z-scores are used to determine whether a data point is usual or unusual. You can think of it as a measure of how many standard deviations an element is from the mean. For instance, a Z-score of 1.0 would denote a value that is one standard deviation from the mean. Z-scores are also used to predict probabilities, with Z-scores having a distribution that is expected to be normal.
In trading, a Z-score is used to determine how often a trading system may produce a string of winners or losers. It can help a trader to understand whether the losses or profits they see are something that the system would most likely produce, or if it's a once in a blue moon situation. This helps traders make decisions about when to start or stop a system.
I just wanted to play a bit with the Z-score I guess.
Feel free to share your findings if you discover additional applications for this strategy or identify timeframes where it appears to perform more optimally.
How it works:
This strategy is based on a statistical concept called Z-score, which measures the number of standard deviations a data point is from the mean. In other words, it helps determine how unusual or usual a data point is.
In the context of this strategy, Z-score is applied to a 10-period EMA (Exponential Moving Average) of Heikin-Ashi candlestick close prices. The Z-score is calculated over a look-back period of 25 bars.
The EMA of the Z-score is then calculated over a 20-bar period, and the upper and lower thresholds (bounds for buy and sell signals) are defined using the 90th and 10th percentiles of this EMA score.
Long positions are taken when the Z-score crosses above the lower threshold or crosses above the mid-line (50th percentile). An additional long entry is made when the Z-score crosses above the highest value the EMA has been in the past 100 periods.
Short positions are initiated when the EMA crosses below the upper threshold, lower threshold or the highest value the EMA has been in the past 100 periods.
Positions are closed when opposing entry conditions are met, for example, a long position is closed when the short entry condition is true, and vice versa.
Set your desired start date for the strategy. This can be modified in the timestamp("YYYY MM DD") function at the top of the script.
