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Watchlist

Curriculum

46 lessons in prerequisite order. Read anywhere; mark read at the end to add its cards to your deck.

A1 · Probability

A1-01Probability as quantified uncertaintyintro14m3 cards A1-02Random variables — returns are random variablesintro15m3 cards A1-03Distributions — normal, and why returns aren'tintro18m4 cards A1-04Expected value and varianceintro17m5 cards A1-05Conditional probability and independenceintro15m4 cards A1-06Bayes' theorem — updating beliefs with evidenceintro16m4 cards A1-07The Law of Large Numbers and the Central Limit Theoremintro20m4 cards

B1 · Markets & Instruments

B1-01What is a market?intro15m3 cards B1-02The menu of instrumentsintro16m4 cards B1-03How prices actually formintro19m5 cards B1-04A trade's lifecycleintro16m4 cards B1-07The time value of moneyintro17m5 cards B1-08ETFs and fundsintro16m4 cards

B2 · Trading Mechanics

B2-01Short selling, margin, and leverageintermediate19m5 cards

C1 · NumPy

C1-01NumPy through computing returnsintro22m4 cards

A2 · Statistics

A2-01The mean — what "average return" actually isintro16m4 cards A2-02Volatility — the standard deviation of returnsintro16m4 cards A2-03The empirical distribution of daily returnsintro18m4 cards A2-05Hypothesis testing — is this strategy real or luck?intermediate19m5 cards A2-08Covariance and correlation — the math of diversificationintro20m5 cards A2-06Linear regression — fitting a line through returnsintermediate20m5 cards A2-07Regression diagnostics — when OLS liesintermediate19m5 cards A2-09Sampling distributions and confidence intervalsintermediate19m4 cards A2-04The Sharpe ratiointro17m4 cards

B1 · Markets & Instruments

B1-05What is "alpha"? Returns vs. a benchmarkintro16m5 cards

C2 · pandas

C2-01pandas for time-indexed financial dataintro22m4 cards C2-02pandas groupby, merge, and reshapingintro22m4 cards

C3 · Visualization

C3-01Plotting market data honestlyintro21m4 cards

D1

D1-01Autocorrelation — does yesterday tell you anything about today?intermediate21m4 cards D1-02White noise and random walks — the null model every strategy must beatintermediate19m5 cards D1-03Stationarity and unit roots — when statistics on a time series mean anythingintermediate20m4 cards D1-04AR models — the math under mean reversionintermediate22m5 cards D1-05MA and ARMA — shocks with echoes, and an honest scoreboardintermediate18m4 cards D1-06Model selection and forecasting — the humbling benchmarkintermediate21m5 cards D1-07Volatility clustering, ARCH and GARCH — forecasting the forecastableintermediate23m5 cards D1-08EWMA and practical volatility — from forecast to position sizeintermediate21m4 cards D1-09Cointegration and pairs trading — mean reversion you can hunt foradvanced23m5 cards D1-10Regimes and structural breaks — models describe, regimes decideadvanced22m5 cards

D2 · Factor Models

D2-01CAPM — risk and return in one equationintermediate18m5 cards

B1 · Markets & Instruments

B1-06Why CAPM isn't enough — the factor zoo previewintermediate15m5 cards

D4 · Backtesting

D4-01Backtesting — first principles and how to fool yourselfintermediate20m5 cards D4-02Building an honest backtest — anatomy, equity curve, drawdown, turnoverintermediate20m5 cards D4-03Transaction cost modeling — the edge that costs eatintermediate20m4 cards D4-04Walk-forward testing and out-of-sample disciplineintermediate22m5 cards D4-05Deflated Sharpe and the probability of backtest overfittingadvanced21m4 cards D4-06Robustness checks — does the edge degrade gracefully?advanced21m4 cards