Strategy #0000000089 · Trend following and technical rules
Percentage filter trend rule
Set recent high/low, current price, filter percentage, assumed exit price and costs to see whether it triggers.
Alexander’s filter rule buys after price rises x% from a recent low and sells or reverses after it falls x% from a recent high. Later studies vary the extreme window, filter size, holding period and market. Filters reduce small-move trades but delay entries and can whipsaw; historical rule tests need data-mining controls.
No historical price series is loaded; gaps, reversals and execution slippage are not modelled.
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
What is scenario P&L after a percentage filter triggers from a recent extreme?
Alexander’s filter rule buys after price rises x% from a recent low and sells or reverses after it falls x% from a recent high. Later studies vary the extreme window, filter size, holding period and market. Filters reduce small-move trades but delay entries and can whipsaw; historical rule tests need data-mining controls.
Set recent high/low, current price, filter percentage, assumed exit price and costs to see whether it triggers.
No historical price series is loaded; gaps, reversals and execution slippage are not modelled.
- Signal inputSet recent high/low, current price, filter percentage, assumed exit price and costs to see whether it triggers.
- Return scenarioNo historical price series is loaded; gaps, reversals and execution slippage are not modelled.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
Buy\ if\ P_t\geq L(1+x),\quad Sell\ if\ P_t\leq H(1-x)
L/H are recent low/high; x is the percentage filter; the exit price is separately user-entered.
Greeks: the directional intuition
- 資料
- Measures sensitivity to implied volatility.
- 門檻
- Measures sensitivity to implied volatility.
- 執行
- Measures sensitivity to implied volatility.
Buy\ if\ P_t\geq L(1+x),\quad Sell\ if\ P_t\leq H(1-x)
Practical context · published observations
Percentage filter trend rule: read the record with its caveats.
The chart uses the published figures or explicitly labelled study inputs below. A historical index or model replay is not the same as an investor’s realised account return.
No historical price series is loaded; gaps, reversals and execution slippage are not modelled. Source ↗ · Methodology ↗
Change assumptions and inspect the scenario
Inputs illustrate the strategy mechanics; they are not live quotes, forecasts or investment advice.
Variants · same family, different risk levers
Signals within a family use different assumptions.
Compare horizon, frequency and trend/fade interpretations.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Base indicator | Technical signal | Alexander’s filter rule buys after price rises x% from a recent low and sells or reverses after it falls x% from a recent high. Later studies vary the extreme window, filter size, holding period and market. Filters reduce small-move trades but delay entries and can whipsaw; historical rule tests need data-mining controls. | No historical price series is loaded; gaps, reversals and execution slippage are not modelled. |
| Confirmation version | Multi-indicator filter | Add trend or volume confirmation. | Confirmation can delay entry. |
| Contrarian version | Mean reversion | Fade extreme deviations. | Can lose while a strong trend persists. |
No historical price series is loaded; gaps, reversals and execution slippage are not modelled.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.