Part II ยท Chapter 6

Trading Indicators as Filters

MA crossover signals are simple linear filters of price history. They generate buy/sell triggers but always LAG actual price moves.

Educational illustration only โ€” NOT investment advice.

Learning objectives

Compute short/long moving averages and crossover signals.
Interpret MAs as linear filters of price history.
Recognize that signals lag the actual price move.
Understand backtest pitfalls (data snooping, costs).

MA Crossover Lab

Seed:

Backtest readout

Number of trades: โ€”
Buy-and-hold return: โ€” %
Strategy return (no costs): โ€” %

Real backtests must include transaction costs, slippage, and proper train/test splits.

๐Ÿ“ Rules

\[ \text{Signal}_t = \begin{cases} +1 \;\; \text{(long)} & \text{if } \text{MA}^{\text{short}}_t > \text{MA}^{\text{long}}_t \\ 0 \;\; \text{(flat)} & \text{otherwise} \end{cases} \]
Cross-up short MA crosses above long โ†’ buy
Cross-down short MA crosses below long โ†’ sell
Lag signal arrives AFTER move

๐Ÿ” What to look for

โš ๏ธ Pro Tip: What to Avoid

Student says

"My MA crossover Sharpe is 1.8 โ€” proven alpha."

Why this is wrong

Train/test contamination, ignored costs, regime-specific results. Many MAs were tried โ€” multiple-testing inflates the best Sharpe.

Correct interpretation

Report walk-forward OOS Sharpe net of realistic costs vs buy-and-hold benchmark. Most simple MA crossovers do not survive.

๐Ÿ“ Mini-quiz

๐Ÿ“‹ Key Takeaways

ConceptMeaning
MA crossoverShort MA vs Long MA โ€” momentum signal
LagSignal fires AFTER price move
WhipsawMany quick reversals โ†’ losses
Backtest dangerData snooping inflates Sharpe