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Multi-dimensional Gold Friday Anomaly Strategy Analysis System

Author: ChaoZhang, Date: 2024-12-12 16:32:12
Tags: MARSIROCSLTPMACDEMARISKPNLATR

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Overview

This strategy is a trading system based on market anomalies, primarily utilizing market behavior characteristics between Thursday evening close and Friday close. The strategy employs fixed entry and exit times, validating this market pattern through backtesting. It uses 10% of capital per trade and considers slippage and commission factors to ensure realistic backtesting results.

Strategy Principles

The core logic of the strategy is based on several key elements:

  1. Entry Condition: Enter long positions at Thursday’s close, based on historical data analysis.
  2. Exit Condition: Close positions at Friday’s close, with fixed holding periods.
  3. Money Management: Uses 10% of account capital per trade, this conservative position sizing helps control risk.
  4. Trade Execution: Orders are executed at closing prices, avoiding intraday volatility impacts.

Strategy Advantages

  1. Simple and Clear: Trading rules are straightforward, without complex indicator combinations, easy to understand and execute.
  2. Controlled Risk: Fixed holding periods and money management plans make risk easier to assess and control.
  3. High Automation: Simple strategy logic suitable for automated trading implementation.
  4. High Flexibility: Parameters can be adjusted for different market environments, showing good adaptability.

Strategy Risks

  1. Time Dependency: Strategy heavily relies on specific time windows, may be affected by major news during non-trading hours.
  2. Market Environment Changes: Historical statistical patterns may become invalid in the future, requiring continuous strategy performance monitoring.
  3. Execution Risk: Liquidity may be insufficient during closing periods, leading to increased slippage. Risk management suggestions:
  • Set stop-loss and take-profit levels
  • Dynamically adjust holding periods
  • Add filtering conditions

Strategy Optimization Directions

  1. Incorporate Volatility Indicators: Add ATR indicator for dynamic position sizing, making the strategy more adaptive.
  2. Optimize Entry Timing: Combine price patterns and technical indicators to improve entry accuracy.
  3. Enhance Risk Control: Add dynamic stop-loss mechanisms to protect existing profits.
  4. Add Filtering Conditions: Consider adding trend filters to avoid trading in unfavorable market conditions.

Summary

This strategy is a classic trading system based on market anomalies, seeking potential returns through strict time management and conservative money management. While the strategy logic is simple, attention must be paid to risks from changing market environments. It’s recommended to use more conservative position sizing and comprehensive risk management mechanisms in live trading.

/*backtest
start: 2024-11-11 00:00:00
end: 2024-12-10 08:00:00
period: 4h
basePeriod: 4h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © piirsalu

//@version=5
strategy("Gold Friday Anomaly Strategy", 
     default_qty_type=strategy.percent_of_equity,
     slippage = 1, commission_value=0.0005,
     process_orders_on_close = true,
     initial_capital = 50000,
     default_qty_value=500,
     overlay = true)
     

/////////////////////////////////////////////////////////////////////////////////////
//                                 . USER INPUTS .                                 //
/////////////////////////////////////////////////////////////////////////////////////

// Define backtest start and end dates
st_yr_inp = input(defval=2000, title='Backtest Start Year')
st_mn_inp = input(defval=01, title='Backtest Start Month')
st_dy_inp = input(defval=01, title='Backtest Start Day')
en_yr_inp = input(defval=2025, title='Backtest End Year')
en_mn_inp = input(defval=01, title='Backtest End Month')
en_dy_inp = input(defval=01, title='Backtest End Day')

// Set start and end timestamps for backtesting
start = timestamp(st_yr_inp, st_mn_inp, st_dy_inp, 00, 00)
end = timestamp(en_yr_inp, en_mn_inp, en_dy_inp, 00, 00)

/////////////////////////////////////////////////////////////////////////////////////
//                              . STRATEGY LOGIC .                                 //
/////////////////////////////////////////////////////////////////////////////////////

// Check if the current day is Friday
isFriday = (dayofweek == dayofweek.friday)

// Initialize a candle counter
var int barCounter = 0

// Increment the candle counter on each new bar
barCounter := barCounter + 1

// Define trading session time ranges
pre_mkt = time(timeframe.period, '0400-0800:23456')
mkt_hrs = time(timeframe.period, '0800-1600:23456')
eod = time(timeframe.period, '1200-1600:23456')

/////////////////////////////////////////////////////////////////////////////////////
//                          . STRATEGY ENTRY & EXIT .                              //
/////////////////////////////////////////////////////////////////////////////////////

// Enter a long position on the first candle of Friday within the backtest period
if dayofweek == 4 and time >= start and time <= end
    strategy.entry("BuyOnFriday", strategy.long)

// Close the position after holding it for 4 candles
if (barCounter % 1 == 0)
    strategy.close("BuyOnFriday")
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