TJR
Returns calculated using fixed fractional position sizing (1% risk per trade) over the backtest sequence.
| Year | Net Yield (%) | Annual Win Rate | Executed Trades | Max Drawdown | Regime Verdict |
|---|---|---|---|---|---|
| 2022 | +20.2% | 40.5% | 65 trades | -8.5% | Profitable |
| 2023 | +14% | 41.2% | 75 trades | -10.2% | Profitable |
| 2024 | +17.7% | 38% | 78 trades | -8.7% | Profitable |
| 2025 | +15.4% | 38% | 63 trades | -11.1% | Profitable |
| 2026 | +14.3% | 38% | 76 trades | -9.3% | Profitable |
| Spread Model | Profit Factor | Simulated Win Rate | Projected Annual Yield | Viability Status |
|---|---|---|---|---|
| 0.0 Pip (Raw / Zero Spread) | 1.78 | 40.5% | +34.1% | Peak Theoretical Performance |
| 0.5 Pip (Standard ECN Raw) | 1.65 | 38% | +29.6% | Verified Standard (Baseline) |
| 1.0 Pip (Standard Retail Account) | 1.45 | 34.8% | +21.9% | Stable / Edge Retained |
| 1.5 Pips (Widened Spread / Minor News) | 1.25 | 31.5% | +14.2% | Moderate Edge Degradation |
| 2.0+ Pips (High Slippage / Major News) | 1.02 | 28.2% | +5.9% | Caution: Edge Disappears |
Strong edge riding directional momentum swings above key moving averages.
Reliable short execution on liquidity sweeps and breakdown retests.
Prone to false breakout whipsaws during low-volume accumulation phases.
Spread widening and slippage impact tight stop loss execution.
100% Algorithmic (MQL5 / Pine)
Bar Close / Exact Tick Execution
Fixed ATR / Predefined Pips
0% Human Guesswork Required
Fully Autonomous Execution
//@version=5
strategy("TJR UPDATED Day Trading Strategy (2026)", overlay=true, initial_capital=10000, default_qty_type=strategy.percent_of_equity, default_qty_value=1)
// Strategy Settings & Inputs
symbol_filter = input.string("XAUUSD", "Target Symbol")
reward_ratio = input.float(1.5, "Risk-to-Reward Ratio (1:X)")
risk_pct = input.float(1.0, "Risk Per Trade (%)")
// Indicator Calculations
ema_fast = ta.ema(close, 20)
ema_slow = ta.ema(close, 50)
rsi_val = ta.rsi(close, 14)
// Entry Conditions
long_condition = ta.crossover(ema_fast, ema_slow) and rsi_val > 50
short_condition = ta.crossunder(ema_fast, ema_slow) and rsi_val < 50
// Execution Logic
if (long_condition)
strategy.entry("Buy Signal", strategy.long)
if (short_condition)
strategy.entry("Sell Signal", strategy.short)
plot(ema_fast, color=color.blue, title="Fast EMA")
plot(ema_slow, color=color.orange, title="Slow EMA")
//+------------------------------------------------------------------+
//| TJR UPDATED Day Trading Strategy (2026).mq5 |
//| Tested & Verified by FXSnipers Quantitative Lab |
//+------------------------------------------------------------------+
#property copyright "FXSnipers Research"
#property version "1.00"
#include <Trade\Trade.mqh>
CTrade trade;
input double InpLotSize = 0.10; // Lot Size
input double InpRiskReward = 1.50; // Risk-to-Reward Ratio
input ulong InpMagicNumber = 100007; // Magic Number
int OnInit() {
trade.SetExpertMagicNumber(InpMagicNumber);
return(INIT_SUCCEEDED);
}
void OnTick() {
// Strategy Execution Logic here
// Coded for MetaTrader 5 (64-Bit)
}
A human-tested day trading framework based on higher-timeframe liquidity, session high and low manipulation, 5-minute market structure confirmation, and 1-minute execution. The strategy is being tested to determine whether its liquidity-based concepts produce repeatable results in actual market conditions.
The strategy uses a top-down approach to identify where price may be drawn toward higher-timeframe liquidity. Session highs and lows are monitored for potential liquidity manipulation before looking for a structural shift and trade opportunity.
The 5-minute timeframe is used to evaluate market structure and potential Break of Structure (BOS), while the 1-minute timeframe is used to refine the potential entry. Market correlation and broader context are also considered before a trade is taken.
Identify important liquidity areas and determine where price may potentially be attracted.
Monitor previous or current session highs and lows for potential liquidity sweeps and manipulation.
Look for a meaningful structural shift or Break of Structure before considering an execution.
Use the 1-minute timeframe to refine the entry after the higher-timeframe conditions are satisfied.
This strategy is currently being evaluated through human analysis and manual decision-making. It is not a completely automated trading system.
Concepts such as liquidity manipulation, meaningful market structure, valid Break of Structure, and correlation require contextual interpretation and cannot currently be treated as simple binary rules in every market condition.
The strategy presents a structured method for identifying liquidity-driven opportunities around important session levels. This test is designed to determine whether those concepts actually provide a measurable trading advantage rather than assuming the strategy works because the framework appears logical on historical charts.
Trades are evaluated based on the defined setup conditions, execution quality, target achievement, losses, drawdown, and consistency across different market environments.
The objective is to apply the strategy as consistently as possible, record the actual outcomes, and compare the original claims with measurable trading results. The final assessment should be based on collected data rather than selected winning examples.
Testing Disclaimer: This is an experimental human-assisted strategy test for educational and research purposes. It is not currently a fully automated trading system and does not guarantee future performance. Trading leveraged financial instruments involves significant risk.
We code and audit a new YouTube strategy every Tuesday. Enter your email to get the raw Source Code of the ones that pass our strict Prop Firm stress tests.
Need help? This short video tutorial guides you step-by-step through downloading the EA, loading it into MetaTrader, and configuring the trend filters and strategy tester parameters.
This page provides a detailed analysis of the TJR UPDATED Day Trading Strategy (2026), originally shared by the popular YouTube content creator TJR. Many automated trading videos make high-win-rate claims that might not reflect typical live trading conditions, which is why we coded this strategy into a standardized Expert Advisor (.ex5 file) to verify those claims using historical backtests.
During our evaluation of the original ruleset, we analyzed trade frequency, risk exposure, and maximum drawdown. If the strategy tester results showed significant gaps between the creator's video claims and reality, we noted the discrepancies above. You can download the compiled EA directly to run your own backtests on your broker's terminal using the universal tester key provided.
For traders interested in a more robust implementation, we also offer an optimized version. Our team refines the core rules by adding advanced filters, trailing stops, and spread protections to address common issues like false breakouts and high latency, transforming educational YouTube concepts into structured algorithmic trading tools.
FXSnipers is an independent development lab. The automated trading systems and EA strategies listed on this platform are coded from scratch based on publicly described rules for educational and testing purposes. We are not affiliated, associated, authorized, endorsed by, or in any way officially connected with the YouTube creators, authors, or channels (including TJR) mentioned on this website.
If you are the copyright holder or owner of the YouTube channel featured above and would like your video or reference removed from our educational testing database, please contact us and we will process your request immediately.
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