In my previous blog, I covered the very basics of the volatility topic. However, it is even difficult to highlight how important volatility is in the world of trading, particularly when discussing options and derivatives. Traders and investors rely on volatility to gauge risk, price derivatives, and identify trading opportunities. Among the types of volatility most commonly discussed are historical volatility and implied volatility. This blog will explore these two concepts, their differences, and how they are used in financial markets.
What Is Historical Volatility?
Historical volatility (HV) is a measure of the past price fluctuations of an asset. It looks at the statistical changes in an asset’s price over a specific time period, typically expressed as an annualised percentage. Historical volatility is backward-looking, as it is calculated based on historical price data.
How Is Historical Volatility Calculated?
The most common method to calculate historical volatility is by taking the standard deviation of the asset’s daily returns over a given period (e.g., 20, 50, or 100 days). Here’s a simplified process; I will cover this topic on how to calculate volatility in more detail in future blogs:
- Collect the asset’s historical price data.
- Calculate daily returns (percentage changes in price).
- Compute the standard deviation of these returns.
- Annualise the result to express it in the time horizon which suits your analysis.
For example, if an asset’s historical volatility is 30%, it suggests that the asset’s price has historically fluctuated by 30% in a given time frequency.
What Does Historical Volatility Tell Us?
- Market Risk: Higher historical volatility implies greater price swings, suggesting higher market risk.
- Trend Analysis: Comparing historical volatility over different periods can provide insights into how market conditions are evolving.
- Baseline for Expectations: HV serves as a benchmark to compare with implied volatility.
What Is Implied Volatility?
Implied volatility (IV), on the other hand, is a forward-looking metric. It reflects the market’s expectations for future price fluctuations, as inferred from options prices. IV is not derived from historical data but rather from the prices at which options are trading in the market.
How Is Implied Volatility Calculated?
Implied volatility is embedded in an option’s price. Traders use models like the Black-Scholes model to back-solve for IV. Here’s the idea briefly. I will also cover how to calculate this “sort” of volatility in future blogs.
- The option price is determined by several factors, including the underlying asset price, strike price, time to expiration, risk-free interest rate, and volatility.
- By inputting the observed market price of the option and solving for the volatility component, traders extract the implied volatility.
What Does Implied Volatility Indicate?
- Market Sentiment: High IV often indicates greater uncertainty or fear in the market, while low IV suggests calmness.
- Options Pricing: IV directly influences the premium of options. Higher IV leads to more expensive options.
- Expectations vs. Reality: Comparing IV with HV helps traders assess whether the market’s expectations are realistic.
Key Differences Between Implied and Historical Volatility
| Aspect | Historical Volatility (HV) | Implied Volatility (IV) |
|---|---|---|
| Nature | Backward-looking, based on past prices | Forward-looking, based on market expectations |
| Source | Historical price data | Options market prices |
| Use Case | Risk analysis, trend identification | Options pricing, gauging market sentiment |
| Fixed vs. Dynamic | Fixed for a given time period | Dynamic, changes with market conditions |
Applications of Historical and Implied Volatility
Trading and Investing
- Options Strategies: Traders use IV to identify options that are overpriced or underpriced. For instance, selling options in a high-IV environment may be advantageous if IV decreases.
- Identifying Trading Opportunities: By manipulating the Black-Scholes model to back-solve for IV, traders may use this result as a forward-looking measure for future opportunities in a given time horizon. It basically tells you what the market expects for a given asset over a given time horizon. I will cover this topic in more detail when showing how to manipulate the Black-Scholes equation to solve for IV.
- Risk Management: Historical volatility helps traders to understand how much an asset’s price has varied, which aids in setting risk parameters. It tells the trader how the “animal” he or she is about to trade actually behaves. In my trading methodology, this is the first-ever study I carry out. I try to understand how a given asset class and/or a financial derivative behaves prior to attempting to model it.
Volatility Comparisons
- Implied vs. Realised Volatility: Comparing IV to the actual volatility (realised volatility) after the fact can reveal whether the market over- or underestimated risk.
Volatility Arbitrage
Volatility arbitrage strategies attempt to exploit discrepancies between implied and historical volatility. For example, if IV is significantly higher than HV, a trader might sell options, expecting volatility to revert to historical norms.
Limitations to Consider
- Historical Volatility: Since HV only reflects past data, it might not accurately predict future movements, especially during abrupt market regime changes.
- Implied Volatility: IV is not a guarantee of future price action; it is merely the market’s collective expectation, which can be wrong.
Conclusion
Both historical and implied volatility are essential tools in understanding and navigating financial markets. Historical volatility provides insights into how an asset has behaved in the past, while implied volatility offers a window into the market’s expectations for the future. By understanding and comparing these metrics, traders and investors can make more informed decisions about risk, pricing, and strategy.
Whether you’re a novice trader or a seasoned investor, mastering these volatility concepts is a step towards achieving greater success in the complex and dynamic world of financial markets.
– Caio Marchesani