Strategy #0000000125 · Intraday trading and time-series momentum
Intraday first-to-last-window momentum
Enter early-session return, signal threshold, final-window return and trading costs.
Intraday-momentum research finds that the first half-hour market return, including overnight information, can predict the final half-hour return; effects may be stronger with high volatility, volume and macro announcements. Dealer gamma hedging is one proposed mechanism, but the signal does not work every day and spreads, opening gaps and execution costs matter.
No intraday index or minute bars are loaded; halts, slippage and announcement timing are omitted.
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 scenario return follows an early-session direction signal into the final window?
Intraday-momentum research finds that the first half-hour market return, including overnight information, can predict the final half-hour return; effects may be stronger with high volatility, volume and macro announcements. Dealer gamma hedging is one proposed mechanism, but the signal does not work every day and spreads, opening gaps and execution costs matter.
Enter early-session return, signal threshold, final-window return and trading costs.
No intraday index or minute bars are loaded; halts, slippage and announcement timing are omitted.
- Input assumptionsEnter early-session return, signal threshold, final-window return and trading costs.
- Model outputNo intraday index or minute bars are loaded; halts, slippage and announcement timing are omitted.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
Position_{last}=sign(r_{first}),\quad R=Position_{last}r_{last}-C
The first-window return sets direction only; the final-window return is a manual scenario, not a model forecast.
Greeks: the directional intuition
- 模型
- Measures sensitivity to implied volatility.
- 合約
- Measures sensitivity to implied volatility.
- 執行
- Measures sensitivity to implied volatility.
Position_{last}=sign(r_{first}),\quad R=Position_{last}r_{last}-C
Practical context · published observations
Intraday first-to-last-window momentum: 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 intraday index or minute bars are loaded; halts, slippage and announcement timing are omitted. 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
Models, contract terms and implementation can change results.
Compare relevant mechanisms and execution assumptions.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Base scenario | Manual inputs | Intraday-momentum research finds that the first half-hour market return, including overnight information, can predict the final half-hour return; effects may be stronger with high volatility, volume and macro announcements. Dealer gamma hedging is one proposed mechanism, but the signal does not work every day and spreads, opening gaps and execution costs matter. | No intraday index or minute bars are loaded; halts, slippage and announcement timing are omitted. |
| Conservative version | Higher cost/loss | Stress higher costs, larger losses or lower liquidity. | May lower scenario returns. |
| Validation version | Data review | Test model inputs with consistent contracts and timestamps. | Needs licensed, representative data. |
No intraday index or minute bars are loaded; halts, slippage and announcement timing are omitted.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.