5 Critical Backtesting Mistakes Every Trader Makes | AlgoTest

Описание: Curve Fitting in Algo Trading? In/Out Sample Explained | Options Backtesting | AlgoTest
Your backtest shows a perfect equity curve — but the strategy bombs in live markets. Why? Curve fitting — the #1 trap that makes strategies look profitable on historical data but fail when conditions change.

This video explains what curve fitting is in algo trading, why it destroys strategy performance, and how in/out sample testing on AlgoTest helps you catch it before you deploy live.

🔑 What You'll Learn:
• What is curve fitting in backtesting — and why over-optimized strategies always fail live
• How to split your data into in-sample (training) and out-sample (validation) periods
• Live demonstration: a Bank Nifty short straddle that looks profitable in-sample but loses money out-sample
• Why equal-period splits (e.g., 3 years in-sample + 3 years out-sample) give the most reliable results
• How to use AlgoTest's built-in in/out sample split date feature to run both tests simultaneously

💡 Why This Matters:
Most retail traders run a single backtest across all available data, see a positive CAGR, and go live. That's like memorizing exam answers without understanding the questions. In/out sample testing is the validation step that separates robust strategies from curve-fit illusions.
If you're learning algo trading for beginners, running options backtesting on Nifty or Bank Nifty, or looking for a backtesting software that includes built-in validation tools — this is the video that saves you from deploying a strategy that only works on past data.

Test first, then trade. 🧪
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⏱ Chapters
00:00 - Coming Up
00:21 - What is Curve Fitting in Backtesting?
00:54 - Why Over-Optimized Strategies Fail Live
01:49 - Demo: Building a Bank Nifty Short Straddle
02:27 - Full Backtest Results (2017–2023)
03:04 - In-Sample vs Out-Sample: Splitting Your Data
04:10 - In-Sample Backtest Results (2017–2022)
04:35 - Out-Sample Backtest Results (2023) — Strategy Fails!
05:35 - Using AlgoTest's In/Out Sample Split Date Feature
06:33 - Why Equal-Period Splits Give Better Validation
07:37 - Final Demo: Profitable In-Sample, Unprofitable Out-Sample
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⚠️ Disclaimer: This video was created by AlgoTest for the sole purpose of education and demonstration of the AlgoTest futures and options backtesting platform as well as the live/paper deployment service that it provides. This is NOT financial advice and is also NOT a strategy recommendation. Please do your own backtesting, research and thorough due diligence before investing or trading in the stock market. Options are leveraged financial instruments and can lead to financial loss of varying levels if trading is attempted without the requisite knowledge, research and/or experience. AlgoTest will not be responsible for the aforementioned loss or profit that is gained by the use of its platform.
Past performance does NOT guarantee future results. For more information, visit algotest.in