Historical Volatility
Historical volatility gauges past price fluctuations over a defined period. Calculating historical volatility involves tracking daily closing prices, computing daily returns, finding their standard deviation and annualising the result by multiplying by the square root of 252 (average trading days). For instance, if the standard deviation of daily returns is 1.5%, the annualised historical volatility is approximately 23.8%. A basic volatility calculator involves noting daily prices, calculating percentage returns, computing the standard deviation of those returns and multiplying by √252. Historical volatility helps assess past risk but doesn’t predict future movements.
Implied Volatility
Implied volatility (IV) reflects the market’s expectation of future price movements based on options prices. Unlike historical volatility, which relies on past data, IV is forward‑looking and influenced by supply and demand in options markets. High IV indicates traders expect large price swings, often around corporate earnings or significant news; low IV suggests anticipated stability. IV influences option premiums—higher IV makes options more expensive—and traders compare IV with historical volatility to assess whether options are overpriced or underpriced. Note that IV estimates expected volatility but is not a precise forecast.
Different Measures of Volatility
Investors use several metrics to assess volatility. Historical volatility examines past price movements, as described above. Implied volatility comes from options prices and reflects future expectations. Beta compares a stock’s volatility to the broader market (beta greater than 1 implies higher volatility). The VIX index, often called the fear index, measures expected market volatility based on index option prices. Combining these measures gives a more complete picture of risk and helps investors plan strategies.
What is Volatility Smile?
A volatility smile is a pattern observed in options markets where implied volatility is higher for deep in‑the‑money and out‑of‑the‑money options than for at‑the‑money options. When plotted against strike prices, implied volatility curves upward at both ends, creating a “smile.” The pattern suggests traders expect greater movement in extreme price scenarios.
What is a Volatility Skew?
Volatility skew refers to an uneven distribution of implied volatility across strike prices, resulting in a slanted curve. In equity markets, put options often exhibit higher implied volatility than call options because investors seek downside protection. Volatility skew highlights market expectations of asymmetric risk.
What are the Factors Affecting Volatility?
Volatility is influenced by various factors, including economic data releases (inflation, GDP, interest rates), company‑specific news (earnings, mergers), global events (geopolitical tensions, pandemics), policy changes and investor sentiment. Liquidity levels also impact volatility; stocks with lower trading volume may experience sharper price movements. Understanding these factors helps investors manage risk and select appropriate investment strategies.
