Tim Olson
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80 lines
4.0 KiB
Markdown
80 lines
4.0 KiB
Markdown
---
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description: "Futures mean-reversion strategy that buys recent underperformers and sells recent outperformers relative to an equally-weighted futures market index, with an extension using volume and open interest filters."
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tags: [futures, mean-reversion, contrarian, market-index, dollar-neutral]
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---
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# Contrarian Trading (Mean-Reversion)
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**Section**: 10.3 | **Asset Class**: Futures | **Type**: Mean-Reversion / Contrarian
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## Overview
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Analogous to the equity mean-reversion strategy (Section 3.9), this futures strategy bets that recent losers will rebound and recent winners will give back gains. Returns of individual futures are measured relative to an equally-weighted market index, and capital is allocated inversely to the deviation from that index. The result is a dollar-neutral, automatically constructed contrarian portfolio rebalanced weekly.
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## Construction / Mechanics
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Within a universe of N futures labeled i = 1,...,N, define the "market index" return as the equally-weighted average:
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```
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R_m = (1/N) Σ R_i (469)
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```
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where R_i are individual futures returns, typically measured over the last one week.
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The capital allocation weights are:
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```
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w_i = -γ [R_i - R_m] (470)
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```
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where γ > 0 is fixed via the dollar-neutral normalization condition:
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```
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Σ |w_i| = 1 (471)
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```
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- Futures below the market index (R_i < R_m): positive weight (long)
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- Futures above the market index (R_i > R_m): negative weight (short)
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- The portfolio is automatically dollar-neutral (Σ w_i = 0)
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- The strategy buys losers and sells winners relative to the market index
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**Volatility adjustment**: To mitigate overinvestment in volatile futures, suppress w_i by 1/σ_i or 1/σ_i², where σ_i are the historical volatilities.
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## Return Profile
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Profits when futures returns mean-revert toward the market index over a one-week horizon. Returns are driven by short-term overreaction and subsequent correction. The strategy is market-neutral at the index level.
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## Key Parameters / Signals
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| Parameter | Description |
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|-----------|-------------|
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| R_i | Individual futures return over the last week |
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| R_m | Equally-weighted market index return (Eq. 469) |
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| w_i = -γ[R_i - R_m] | Allocation weight; negative for winners, positive for losers |
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| γ | Scaling parameter fixed by Eq. (471) |
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| σ_i | Historical volatility; used to suppress w_i optionally |
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| Rebalancing | Weekly |
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## Variations
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### 10.3.1 Contrarian Trading — Market Activity
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Volume and open interest filters can improve the basic mean-reversion signal. Define:
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```
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v_i = ln(V_i / V_i') (472)
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u_i = ln(U_i / U_i') (473)
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```
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where V_i is total volume for futures i over the last week, V_i' is total volume over the prior week, and U_i, U_i' are the analogous open interest quantities.
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**Construction:**
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1. Take the upper half of futures by volume factor v_i (higher recent volume relative to prior week).
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2. Within that subset, take the lower half by open interest factor u_i.
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3. Apply the contrarian weights from Eq. (470) to this filtered subset.
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**Rationale:**
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- Larger volume changes indicate greater overreaction (a stronger snap-back is expected).
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- A decrease in open interest (low u_i) signals hedger withdrawal and suggests a deeper market for the mean-reversion to work.
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## Notes
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- The simple weighting scheme (Eq. 470) can overinvest in highly volatile futures; volatility scaling (1/σ_i or 1/σ_i²) is recommended in practice.
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- Weekly rebalancing incurs transaction costs; the net alpha must exceed round-trip costs across all positions.
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- Contrarian strategies can suffer sustained losses during trending regimes; combining with a trend-following overlay (Section 10.4) may reduce drawdowns.
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- The market-index return R_m links this strategy to the broader futures universe; changing the universe composition changes the benchmark and alters all weights.
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