Option Strategies for Forecast Density Errors in Mean, Volatility, and Tails
Summary
The document maps views about forecast return distributions to simple option positions. A belief that expected returns are understated or overstated is associated with buying a call or put, respectively. Views on dispersion are paired with long or short straddles and strangles, while views about underpriced or overpriced tail risk are mapped to out-of-the-money puts or calls.
These examples organize potential trades by the part of the distribution they target: location, scale, or a particular tail. The post is conceptual and gives no pricing framework, payoff analysis, sizing rules, or evidence that any position is profitable. A forecast error alone does not determine whether an option is cheap: implied volatility, skew, maturities, premiums, and the distribution of realized outcomes also matter. The suggested positions therefore need valuation and risk analysis before use.
Key ideas
- Calls and puts are suggested for directional views on the forecast distribution’s location.
- Straddles or strangles can express views that realized dispersion will differ from expectations.
- Out-of-the-money puts and calls target views about left-tail and right-tail probabilities.
- The post offers position examples but no pricing, sizing, or performance evidence.
- Option premiums and implied volatility must be considered when assessing a density forecast error.
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Full text
# Trading strategy for a misspecified density # Trading strategy for a misspecified density I am trying to implement a strategy that exploits potential misspecifications in density predictions (e.g.: long states with too-low probability; short states with too-high probability). In particular, I am looking for an option-based strategy that exploits: - The location of the forecast density (i.e.: misspecified mean): Which strategy could be used to benefit from a density prediction that is displaced to the left/right? - The scale of the forecast density (i.e.: missspecified volatility): Which strategy could be used to benefit from a density prediction that exhibit excessive dispersion/concentration? - Asymmetric tail estimates: Which strategy could be used to benefit from densities that assign too-low probability to the left tail compared to the right tail, or vice versa? Since the strategy concern different payoff regions, I am initially looking at an option-based approach that employs calls and puts with different strikes. ## Answer by Mild_Thornberry (score 3) https://quant.stackexchange.com/a/62001 Maybe this is too simple, but here’s what I think of when you ask for option strategies given a view on forecasted price densities: -Think returns are going to be higher than expected? Buy a call. -Think returns are going to be lower than expected? Buy a put -Think scale is going to be higher than than expected? Long straddle or long strangle. -Think scale is going to be lower than expected? Short straddle or short strangle. -Think left tail weight too low/high? Buy/sell an OTM put -Think right tail weight too low/high? Buy/sell an OTM call
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