Research and Backtesting
38 lessons in this track so far, in the order we suggest reading them.
The Research Process
IntermediateThe Trading Research ProcessA disciplined research process turns ideas into tested strategies. Learn each step, from hypothesis and data to backtests, validation and paper trading.IntermediateThe Strategy LifecycleTrading strategies are born, mature and decay. Learn the stages of a strategy's life, how to scale up, how to monitor decay and when to retire a strategy.IntermediateWhy Strategies FailMost strategies that look good in backtests fail live. Learn the main causes, from overfitting and costs to regime changes, and how to guard against each.
Backtesting
IntermediateBacktesting MethodologyA backtest simulates a strategy on historical data. Learn the steps, the key performance metrics, common biases and a checklist for backtests you can trust.IntermediateHistorical Data for BacktestingBacktests are only as good as their data. Learn data types and sources, quality checks, corporate action adjustments and how to avoid survivorship traps.IntermediateIn-Sample vs Out-of-Sample TestingOut of sample testing checks a strategy on data not used to build it. Learn train, validation and holdout splits, common mistakes and how to read results.IntermediateWalk-Forward AnalysisWalk forward analysis repeatedly optimises a strategy on past data and tests it on the next period. Learn how it works, window choices, efficiency ratios and limits.IntermediateOverfitting and Curve FittingOverfitting means a strategy fits noise instead of a real pattern. Learn the warning signs, why it happens, how to measure it and practical ways to avoid it.IntermediateLook-Ahead BiasLook ahead bias happens when a backtest uses information that was not available at the time. Learn common sources, real examples and how to prevent it in code.IntermediateSurvivorship and Selection BiasSurvivorship bias ignores failures; selection bias picks unrepresentative samples. Learn how both inflate backtests, fund returns and advice, and how to fix them.IntermediateData LeakageData leakage lets information from test data or the future slip into model training. Learn common leaks in trading and machine learning and how to prevent them.IntermediateP-Hacking and Multiple TestingTesting many strategy variations guarantees some look good by chance. Learn how p hacking happens, how to adjust for multiple tests and the deflated Sharpe ratio.IntermediateMonte Carlo SimulationMonte Carlo simulation generates thousands of possible outcomes to show the range of results. Learn trade resampling, drawdown estimates and the limits.IntermediateParameter OptimizationChoosing strategy parameters by optimisation risks overfitting. Learn grid and random search, robustness surfaces, walk forward optimisation and sensible defaults.IntermediateRobustness and Stress TestingRobustness tests check whether a strategy survives changes in parameters, markets, costs and conditions. Learn the main tests and how to read the results.IntermediateCosts and Slippage in BacktestsIgnoring costs is the fastest way to fool yourself in a backtest. Learn the costs to include, how to estimate slippage and market impact, and conservative rules.
Backtesting Engines
AdvancedEvent-Driven vs Vectorized BacktestingVectorised backtests compute signals and returns for all dates at once using arrays. Learn how they work, a pandas example, their speed advantages and their traps.AdvancedFill Models, Partial Fills and Order QueuesA fill model decides when and at what price backtest orders execute. Learn market, limit and stop fill assumptions, queue position and adverse selection.AdvancedPortfolio and Multi-Asset BacktestingPortfolio backtests simulate many positions with capital limits, sizing and rebalancing. Learn the key design choices, constraints, metrics and pitfalls.AdvancedCorporate Actions, Delistings and Rolls in BacktestsSplits, dividends, mergers, spin offs and delistings change prices and holdings. Learn how each affects backtests, how to adjust data and the errors to avoid.AdvancedBacktest ReproducibilityA reproducible backtest gives the same results every time from the same code and data. Learn version control, data snapshots, research logs and good habits.
Alpha Research
AdvancedWhat Is Alpha?Alpha is return beyond what market and factor exposure explain. Learn how alpha is measured, the difference between alpha and beta, and why true alpha is rare.AdvancedSignal DiscoverySignal discovery is the search for variables that predict returns. Learn where ideas come from, how to test signals with information coefficients and decay curves.AdvancedSignal and Alpha DecaySignal decay is how fast a signal's predictive power fades; alpha decay is how edges shrink over years. Learn both, the evidence and how traders adapt.AdvancedCombining SignalsCombining several weak signals often beats relying on one strong one. Learn standardisation, weighting methods, correlation between signals and pitfalls to avoid.AdvancedAlpha Capacity and CrowdingCapacity is how much capital a strategy can trade before returns shrink; crowding is when too many traders chase the same edge. Learn to estimate and manage both.AdvancedSignal Turnover, Breadth and NeutralizationTurnover measures how much a portfolio trades. Learn how to calculate it, how it links signal decay to costs, and techniques to cut turnover without losing alpha.
Factor Investing
AdvancedFactor Investing ExplainedFactor investing targets traits linked to long run returns, such as value, momentum and quality. Learn the main factors, the evidence and how they are traded.AdvancedValue FactorThe value factor buys cheap stocks and avoids expensive ones using ratios like book to market. Learn the evidence, the long drawdown and how to build it.AdvancedMomentum FactorThe momentum factor buys recent winners and sells recent losers. Learn how it is built, the evidence across markets, momentum crashes and how to manage them.AdvancedQuality and Profitability FactorsThe quality factor favours profitable, stable, conservatively financed companies. Learn how quality is measured, the evidence and how it pairs with value.AdvancedSize FactorThe size factor says small companies outperform large ones over time. Learn the original evidence, why the effect weakened, the role of quality and how to trade it.AdvancedLow Volatility and Defensive FactorsThe low volatility anomaly is the finding that less volatile stocks have delivered better risk adjusted returns. Learn the evidence, explanations and its risks.AdvancedCarry FactorThe carry factor buys higher yielding assets and sells lower yielding ones across currencies, bonds, commodities and stocks. Learn how carry is measured.AdvancedLiquidity FactorThe liquidity factor captures the extra return investors demand for holding hard to trade assets. Learn how illiquidity is measured, the evidence and its risks.AdvancedGrowth and Dividend FactorsGrowth, investment and dividend factors look at how firms grow, invest and pay shareholders. Learn the evidence, including why aggressive investors lag.AdvancedShort and Long-Term ReversalReversal effects describe recent losers beating recent winners over very short and very long horizons. Learn the evidence, the causes and the link to momentum.AdvancedFactor Timing, Crowding and CrashesFactor crowding happens when too much capital chases the same factor. Learn how crowding affects returns and crash risk, how to measure it and how to cope.