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Strategy #0000000020 · Trend and time-series momentum

Moving-average crossover
Smooth price direction with a rule; accept lag in exchange for clarity.

Moving averages smooth past prices. A short average above a long average may signal long exposure; below it may signal short or flat. Signals lag and can whipsaw in ranges.

Beginner-friendlyAbout 8 minutesEvidence and practical analysis

Three ways in

Understand the story. Then inspect the risk.

Start with a familiar situation, check the payoff, then test how the numbers change.

The idea · in two minutes

Jack uses a short average as a direction gauge, not a crystal ball

Jack calculates 10-day and 30-day closing-price averages. When the short line crosses above the long one, he enters at the next tradable time; a cross below reverses or closes the position.

Rose insists on execution timing: if the signal uses today’s close, the strategy cannot assume a fill at that same close. She also fixes SMA or EMA, always-in-market rules, fees, slippage and dividends.

In a range, the lines can cross repeatedly and incur costs. At a sharp reversal, the average may confirm only after price has moved. Three averages, percentage bands and holding periods change noise and delay, but each rule needs pre-set parameters and out-of-sample testing.

  • 短 MA > 長 MAShort average above long average gives a long signal; +1% assumed next-period return would produce +1% gross.
  • 短 MA < 長 MAShort average below long average gives a short signal; +1% underlying return would produce −1% gross.
  • 扣換倉成本Signal direction times assumed return, less switching cost. This is a scenario input, not observed performance.

Illustrative research examples only. They are not live signals or a recommendation.

Variants · same family, different risk levers

Moving-average rules change the smoothing method, windows or confirmation.

Each added window, band or confirmation day changes the lag/turnover trade-off.

Related strategyRelationshipWhat changesNew cost or risk
Single moving averagePrice versus averageGo long above the average and short or exit below it.Price crossings are sensitive and reverse frequently in ranges.
Dual moving-average crossoverShort/long crossoverGo long when the short average crosses above the long one; reverse or exit below.Both windows require choices and the signal still lags.
Three moving averagesMulti-horizon confirmationRequire short, medium and long averages to align before entry.More confirmation is slower and adds parameters and costs.
Percentage-band MABreakout bufferRequire price to clear a percentage band around the average.A wider band may reduce whipsaws but miss smaller trends.
HP-filtered moving averageFiltered crossoverExtract a slower trend with a Hodrick–Prescott filter before applying a crossover.Endpoint bias and two-sided filtering can leak future information.
Fixed holding / confirmation daysEntry confirmationRequire a crossover to persist or hold the position for a fixed number of days.Stability comes with slower response and exit slippage.
Three-line 3/10/21 ruleFast multi-average ruleUses short, medium and long windows to confirm a shorter-horizon trend.Parameter searches and turnover increase data-mining risk.
Adaptive lookbackState-dependent windowChooses a lookback based on a pre-defined market state.State estimates lag and can accidentally use future information.

Technical-rule research is especially vulnerable to data snooping; disclose the tested rule family and every parameter search.

Read beyond the summary

References

Primary sources and research used to describe the strategy and its limits.

  1. 01Brock, Lakonishok & LeBaron (1992), Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.research
  2. 02Sullivan, Timmermann & White (1999), Data-Snooping, Technical Trading Rule Performance, and the Bootstrap.research
  3. 03Park & Irwin (2005), The Profitability of Technical Trading Rules in US Futures Markets: A Data Snooping Free Test.research
  4. 04Hsu & Kuan (2005), Reexamining the Profitability of Technical Analysis with Data Snooping Checks.research
  5. 05Kakushadze & Serur (2018), 151 Trading Strategies, §§3.11–3.13.source