Three moving averages
A systematic stocks approach—Three moving averages—defined by explicit rules, testable on history, and fragile when costs or regimes change.
Overview
In some cases, using 3 moving averages with lengths T1 < T2 < T3 (e.g., T1 = 3, T2 = 10, T3 = 21) can help filter false signals: Establish long position if MA(T1)> MA(T2)> MA(T3) Liquidate long position if MA(T1)≤ MA(T2) Establish short position if MA(T1)< MA(T2)< MA(T3) Liquidate short position if MA(T1)≥ MA(T2)
Three moving averages sits in the Stocks chapter of the systematic catalog. On QUSXFI we treat it as a testable hypothesis: specify entries, exits, sizing, and costs—then ask whether edge survives out-of-sample scrutiny.
Discretionary traders often arrive at similar ideas intuitively; the quantitative version forces you to write the rule before you see the next bar. That discipline is what makes results reproducible—or exposes them as luck.
Based on the research catalog 151 Trading Strategies (Kakushadze & Serur, 2018), section 3.13. Educational summary—not a replication of the full formal definition.
How the Strategy Works
Three moving averages in Stocks is defined by explicit positions and transition rules—translate each clause into code or a checklist.
The published definition of Three moving averages (catalog §3.13) specifies when exposure changes; discretionary overrides invalidate systematic claims.
Implementation and Research Process
Walk-forward or hold-out test Three moving averages; report turnover, max drawdown, and exposure—not CAGR alone.
Log regime tags beside Three moving averages performance slices—vol level, rate cycle, liquidity stress.
Archive Three moving averages failure modes with dates—research firms learn from documented breaks, not from erased losing months.
Risk: What Breaks This Strategy
Single-name or factor exposure in Three moving averages concentrates idiosyncratic shock risk even when the signal is 'systematic.'
Universe selection and survivorship in historical databases flatter backtests versus live investable sets.
Borrow and short availability change the short leg economics without changing the code.
Common Mistakes to Avoid
- Erasing losing Three moving averages months instead of documenting regime breaks—that is how research firms stop learning.
- Changing Three moving averages parameters after each losing week—implicit discretion destroys reproducibility.
- Reporting Three moving averages backtests without fees, slippage, and realistic fill rules.
- Using academic §3.13 definitions for Three moving averages while ignoring borrow, margin, or contract specs.
How to Study This Strategy
- Compare Three moving averages to one sidebar alternative net of costs—document why you chose this structure.
- Map Three moving averages to Basic Trading chart concepts you will use as filters—not as substitutes for rules.
- Restate Three moving averages (§3.13) as numbered rules another researcher could implement cold.
- List every data field Three moving averages needs in Stocks; verify point-in-time integrity.
- Run a paper book on Three moving averages for a full signal cycle; export trades and tag regimes manually.
Key Takeaways
- Three moving averages in Stocks is a testable rule set—a systematic stocks approach—three moving averages—defined by explicit rules, testable on history, and fragile when costs or regimes change.
- Translate every clause of Three moving averages into code or a checklist; judgment steps are not yet quantitative.
- Capacity for Three moving averages appears only when you simulate participation against average volume.
- Erasing losing Three moving averages months instead of documenting regime breaks—that is how research firms stop learning.
- Related strategies in the sidebar may share hidden exposures with Three moving averages—compare before stacking.
Learning Tip
Explain Three moving averages to someone who only knows Basic Trading charts—if you need unexplained jargon, the spec is not ready.
Explore related strategies in the sidebar or return to the full catalog.