Detrended Price Oscillator Quantitative Trading Strategy

The strategy is named "Detrended Price Oscillator Quantitative Trading Strategy". It generates trading signals based on the Detrended Price Oscillator indicator, which is a typical technical indicator strategy.

Pine ScriptTrend following SMA

Author: ChaoZhang
Complexity: Starter · 43 lines
Parameters: 3
Backtest bar: 30m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Strategy Overview

Strategy Logic

The core of this strategy is the Detrended Price Oscillator (DPO) indicator. DPO is similar to moving average, which can filter out longer-term trends in prices to make cyclical fluctuations more pronounced. Specifically, DPO compares prices with their N-day simple moving average. When the price is above the moving average, DPO is positive; when the price is below the moving average, DPO is negative. This results in an oscillator fluctuating around the 0 axis. We can use the positive/negative of DPO to judge the rise/fall of prices relative to the trend.

This strategy sets the parameter N to 14 and constructs a 14-day DPO indicator. When DPO is positive, a long signal is issued. When DPO is negative, a short signal is issued.

Advantages

DPO is essentially a filtering indicator that can effectively identify medium-term cycles in prices. This is very helpful for discovering relatively concealed trading opportunities.
DPO has simple construction and is easy to understand. The parameter selection is also relatively flexible.
Compared to the price itself, the DPO indicator pattern is more standardized and easier to judge, making it suitable for formulating rules.

Risks

Like most technical indicator strategies, the DPO strategy tends to generate unnecessary trading signals frequently. This may introduce unnecessary slippage and transaction costs.
DPO is very sensitive to the parameter N. Different parameter selections can lead to very different strategy efficacy. Extensive testing is needed to find the optimal parameter.
In trending markets, the holding period of DPO strategies may be too long to stop loss in time, posing some risk of blood loss.

To mitigate risks, optimization can be considered in the following aspects:

Add stop loss mechanisms to control single loss.
Adjust the value of parameter N to find the optimal parameter.
Incorporate trend indicators to avoid trading against significant trends.

Conclusion

This strategy generates trading signals based on the Detrended Price Oscillator indicator. By comparing with moving averages, this indicator filters out long-term trends in prices to make price cyclic characteristics more pronounced. This helps to discover some concealed trading opportunities. At the same time, it also faces problems like parameter sensitivity, filtering, etc. There is still large room for efficacy improvement through continuous optimization.

Parameters

Name	Default	What it controls
v_input_1	14	Length
v_input_2	close	Price
v_input_3	false	Trade reverse

Source Pine Script

/*backtest
start: 2023-11-16 00:00:00
end: 2023-11-20 08:00:00
period: 30m
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=2
////////////////////////////////////////////////////////////
//  Copyright by HPotter v1.0 31/03/2017
// The Detrend Price Osc indicator is similar to a moving average, 
// in that it filters out trends in prices to more easily identify 
// cycles. The indicator is an attempt to define cycles in a trend 
// by drawing a moving average as a horizontal straight line and 
// placing prices along the line according to their relation to a 
// moving average. It provides a means of identifying underlying 
// cycles not apparent when the moving average is viewed within a 
// price chart. Cycles of a longer duration than the Length (number 
// of bars used to calculate the Detrend Price Osc) are effectively 
// filtered or removed by the oscillator.
//
// You can change long to short in the Input Settings
// Please, use it only for learning or paper trading. Do not for real trading.
////////////////////////////////////////////////////////////
strategy(title="Detrended Price Oscillator", shorttitle="DPO")
Length = input(14, minval=1)
Series = input(title="Price",  defval="close")
reverse = input(false, title="Trade reverse")
hline(0, color=green, linestyle=line)
xPrice = close
xsma = sma(xPrice, Length)
nRes = xPrice - xsma
pos = iff(nRes > 0, 1,
	     iff(nRes < 0, -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=red, title="Detrended Price Oscillator")

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-24. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more

/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/Detrended-Price-Oscillator-Quantitative-Trading-Strategy.md

npx agenkit install engineering-kit in your project
Paste the command into your agent and approve each phase
Get tests, backtest, risk controls and a paper-trading switch

Get AgenKit How /agenkit works

Understand it first

Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.