# Z-Score Price Breakout Strategy

Author: ChaoZhang, Date: 2023-12-07 15:17:43
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### Overview

The Z-Score price breakout strategy uses the z-score indicator of price to determine whether the current price is in an abnormal state, so as to generate trading signals. When the z-score of price is higher or lower than a threshold, it means the price has entered an abnormal state, at which point long or short positions can be taken.

### Strategy Principle

The core indicator of this strategy is the z-score of price, calculated as follows:

``````Z_score = (C - SMA(n)) / StdDev(C,n)
``````

Where C is the closing price, SMA(n) is the simple moving average of n periods, and StdDev(C,n) is the standard deviation of closing price for n periods.

The z-score reflects the degree of deviation of the current price from the average price. When the price z-score is greater than a certain positive threshold (e.g. +2), it means the current price is above the average price by 2 standard deviations, which is a relatively high level. When it is less than a certain negative threshold (e.g. -2), it means the current price is below the average price by 2 standard deviations, which is a relatively low level.

This strategy first calculates the z-score of price, then sets a positive and negative threshold (e.g. 0 and 0). When the z-score is higher than the positive threshold, it generates a buy signal. When lower than the negative threshold, it generates a sell signal.

• Using price z-score to judge price anomalies is a common and effective quantitative method
• Easily achieve both long and short trading
• Flexible parameter settings, adjustable cycle, threshold, etc.
• Can be combined with other indicators to form a trading system

### Risk Analysis

• The z-score strategy is crude and prone to false signals
• Need to set appropriate parameters like cycle and threshold
• Need to consider stop loss strategies to control risk

### Optimization Directions

• Optimize cycle parameters to find the best cycle
• Optimize positive and negative thresholds to reduce false signals
• Add filter conditions, combine with other indicators

### Summary

The z-score price breakout strategy judges whether the current price is in an abnormal state, and trades according to the positive and negative of the price z-score. This strategy is simple and easy to implement, allows two-way trading, but also has some risks. By optimizing parameters, adding stop loss and combining with other indicators, this strategy can be enhanced to form a complete quantitative trading system.

```/*backtest
start: 2023-11-29 00:00:00
end: 2023-12-04 19:00:00
period: 15m
basePeriod: 5m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=2
////////////////////////////////////////////////////////////
//  Copyright by HPotter v1.0 18/01/2017
// The author of this indicator is Veronique Valcu. The z-score (z) for a data
// item x measures the distance (in standard deviations StdDev) and direction
// of the item from its mean (U):
//     z = (x-StdDev) / U
// A value of zero indicates that the data item x is equal to the mean U, while
// positive or negative values show that the data item is above (x>U) or below
// (x Values of +2 and -2 show that the data item is two standard deviations
// above or below the chosen mean, respectively, and over 95.5% of all data
// items are contained within these two horizontal references (see Figure 1).
// We substitute x with the closing price C, the mean U with simple moving
// average (SMA) of n periods (n), and StdDev with the standard deviation of
// closing prices for n periods, the above formula becomes:
//     Z_score = (C - SMA(n)) / StdDev(C,n)
// The z-score indicator is not new, but its use can be seen as a supplement to
// Bollinger bands. It offers a simple way to assess the position of the price
// vis-a-vis its resistance and support levels expressed by the Bollinger Bands.
// In addition, crossings of z-score averages may signal the start or the end of
// a tradable trend. Traders may take a step further and look for stronger signals
// by identifying common crossing points of z-score, its average, and average of average.
//
// You can change long to short in the Input Settings
////////////////////////////////////////////////////////////
strategy(title="Z-Score Strategy", shorttitle="Z-Score Strategy")
Period = input(20, minval=1)
Trigger = input(0)
hline(Trigger, color=purple, linestyle=line)
xStdDev = stdev(close, Period)
xMA = sma(close, Period)
nRes = (close - xMA) / xStdDev
pos = iff(nRes > Trigger, 1,
iff(nRes < Trigger, -1, nz(pos[1], 0)))
possig = iff(reverse and pos == 1, -1,
iff(reverse and pos == -1, 1, pos))
if (possig == 1)
strategy.entry("Long", strategy.long)
if (possig == -1)
strategy.entry("Short", strategy.short)
barcolor(possig == -1 ? red: possig == 1 ? green : blue )
plot(nRes, color=blue, title="Z-Score")
```

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