Volatility Mean Reversion Speed

Overview

This pillar measures how quickly an asset's implied volatility (IV) returns to its historical average after a major price shock or event. It's crucial for timing trades in options markets, where volatility is a key component of price.

What It Does

It analyzes historical implied volatility data to calculate a mean reversion speed. Using stochastic models like the Ornstein-Uhlenbeck process, it determines how aggressively volatility tends to decay back towards its long-term baseline. This provides a forecast for how long elevated option premiums are likely to persist.

Why It Matters

The speed of mean reversion provides a significant edge in volatility trading. A fast reversion suggests selling expensive options after a spike is a good strategy, while a slow reversion might signal a new, sustained period of high volatility, creating different opportunities.

How It Works

First, the pillar gathers daily implied volatility data for a specific asset over a set period, like 90 or 180 days. It then calculates the long-term mean and applies a statistical model to estimate the reversion speed parameter. Finally, this parameter is used to compute the 'half-life', which is the expected time for volatility to fall by half towards its average.

Methodology

The core calculation uses the Ornstein-Uhlenbeck (OU) stochastic process, dXt = θ(μ − Xt)dt + σdWt. We estimate the parameter θ (theta), which represents the speed of mean reversion, using historical implied volatility data over a 90-day rolling window. The half-life of a volatility shock is then calculated as ln(2)/θ, providing a concrete measure of decay time.

Edge & Advantage

This provides a quantitative edge for timing volatility-selling strategies by identifying assets where overpriced options premiums are likely to decay the fastest.

Key Indicators

• Ornstein-Uhlenbeck Theta

  high

  The direct statistical measure of the speed of reversion to the mean. A higher theta means faster reversion.

• IV Mean Reversion Half-Life

  high

  The expected time in days for implied volatility to decrease by 50% of the distance back to its long-term average.

• GARCH Forecast

  medium

  A related model that forecasts the magnitude of future volatility, providing context for the reversion analysis.

Data Sources

• CBOE

  Provides data for major volatility indices like the VIX, which serves as a market benchmark.

• OptionMetrics

  A leading provider of historical options and implied volatility data for institutional research.

• Nasdaq Data Link (Quandl)

  API access to historical financial data, including options and volatility datasets from various providers.

Example Questions This Pillar Answers

• → Will the VIX index close below 20 within 5 trading days of a close above 30?
• → Will implied volatility on NVDA stock be lower 3 days after its earnings report than the day before?
• → Which asset will experience a faster IV collapse post-FOMC meeting: SPY or QQQ?

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