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Learn backtesting and strategy development—from building rules and running historical tests to reading metrics, avoiding overfitting, and turning validated edges into a trading plan.
What strategy development covers—from idea to rules, testing, and live deployment with discipline.
Read article →Step-by-step framework for defining entries, exits, sizing, and filters before you backtest.
Read article →Core concepts of historical simulation, required assumptions, and what backtests can and cannot prove.
Read article →A practical workflow for data prep, simulation, cost modeling, and out-of-sample validation.
Read article →Worked examples of ORB, MA pullback, and mean reversion backtests with metrics and pitfalls.
Read article →Profit factor, drawdown, Sharpe, win rate, expectancy, and which metrics matter most for your style.
Read article →Essential trading KPIs, how to track them live, and how to compare against backtest benchmarks.
Read article →Overfitting, look-ahead and survivorship bias, fill assumptions, and why past performance can mislead.
Read article →Parameter grids, walk-forward analysis, and how to optimize without curve-fitting noise into rules.
Read article →Structure a plan covering markets, setups, risk, routines, and review cadence tied to your strategy.
Read article →Framework for judging robustness, sample size, regime fit, and live versus backtest alignment.
Read article →How to use Trade Ideas OddsMaker to backtest alert strategies on historical intraday data.
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