Reversal Factor
A-share reversal factors: short-term price reversals
Reversal factors look for a bounce after a recent price move. Short holding windows create high turnover and are highly sensitive to implementation rules.
Typical direction
Recent losers are commonly ranked higher in a short-term reversal study; define the holding horizon explicitly.
Data
Adjusted price history, trading status and event filters
Refresh
One to 20 trading days; frequent rebalancing
Research hypothesis
Write the hypothesis before reading the backtest
Very short-term price deviations may partly reverse, but the signal can be overwhelmed by event risk, price limits and costs.
A factor is a testable research hypothesis, not an investment recommendation or return promise.
Factor health card
Pre-backtest checks for this factor
Research purpose
Test whether short-term deviations can be captured after realistic execution assumptions.
Refresh and rebalance
Short cycles require explicit daily or weekly execution rules.
Data timing
Use adjusted prices and a stated treatment of event days.
Neutralisation
Review sector, size and volatility exposures.
Overlapping exposures
Can conflict with momentum depending on the window.
Check before use
Test costs, slippage and limit-hit non-fills before judging the signal.
Definitions
Core measures
Short-horizon return
Adjusted price(t) ÷ adjusted price(t−N) − 1N must match the holding rule.
Reversal spread
Recent-loser return − recent-winner returnAssess after costs and fills.
Turnover
Portfolio traded value ÷ portfolio valueOften dominates net outcomes.
Limit-hit ratio
Limit-hit names ÷ portfolio namesAn A-share implementability diagnostic.
Research protocol
Keep the same research conventions across factors
Data availability
Financial, dividend and share data become available on actual disclosure or implementation dates, not report-period end dates.
Universe and exclusions
Document index membership, listing age, ST, suspensions, delistings and missing-data rules.
Processing and neutralisation
Version winsorisation, standardisation, sector/size neutralisation and missing-value rules.
Tradability
Include price limits, suspensions, participation, fees, slippage and market impact.
Out-of-sample review
Report IC, grouped returns, exposures, turnover and rolling out-of-sample evidence together.
Build and validate
What to test
- 1Keep formation and holding periods separate.
- 2Report net results and fill assumptions.
- 3Test event and price-limit exclusions.
Common pitfalls
- ×Showing gross returns only.
- ×Overlapping reversal and momentum windows without explanation.
- ×Ignoring corporate-action and event effects.
A-share implementation
A-share checks that belong in the backtest
- Use the actual disclosure or implementation date; do not make a field available at the report-period end date.
- State the universe, listing-age, ST, suspension, delisting and missing-data rules before running the backtest.
- Model price limits, suspensions, fees, slippage and participation limits instead of assuming every close can be traded.
- Price limits and one-word boards can prevent intended reversal trades from being executed.
Research prompt
A reviewable starting prompt
“In a liquid A-share universe, test five-day reversal with daily execution rules, price-limit non-fills, participation caps and costs. Report gross and net spreads, turnover, fill rates and out-of-sample stability.”
FAQ
Why is turnover central to reversal?
Short holding periods cause frequent trades. A gross signal can disappear after fees, slippage and non-fills.
Can reversal and momentum be combined?
Yes, but only with clearly separated horizons and a correlation review. Otherwise the signals can offset or duplicate each other.