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Quant Systems Lab · Control Systems for Quantitative Finance

Volatility (Realised vs Implied)

Realised volatility comes from past price moves; implied volatility is the market’s quote for future uncertainty.

Explanation

Realised volatility is computed from historical returns, for example as the annualised standard deviation over a recent window.

Implied volatility is the σ that, plugged into Black–Scholes, matches the current market price of an option.

They differ because markets embed risk premia, jump risk, and supply–demand imbalances for options into implied volatility.

In calm periods, realised volatility can sit well below implied; in stress, both can spike, but not necessarily by the same amount or timing.


volatilityrealisedimpliedoptionsuncertainty
Interactive visualisation

Realised volatility σrealised comes from past price moves; you estimate it from a return series. Implied volatility σimplied is the input to a pricing model (here Black–Scholes) that makes the model price match the market option price.

Day index tDaily return rₜ0%±σ₍daily₎ ≈ 1.3%σ_realised ≈ 20.0% (annual)Realised σ = annualised std of these daily returns rₜ
Volatility σ (annual)Call price C(σ)10%20%40%60%51020C(σ_realised)C(σ_implied)σ_realised from returnsσ_implied from optionsC(σ) for S₀ = 100, K = 100, T = 0.5 years, r = 0
Numbers
Target slider volatility σtarget: 20%
Realised volatility σrealised from this path: 20.0% (annual)
Corresponding daily σ: 1.3% (≈ σ_realised / √252)
Implied volatility σimplied: 25.0% (annual)
Call price at σrealised: 5.64
Call price at σimplied: 7.04 (higher premium)
Parameters: S₀ = 100, K = 100, T = 0.5 years, r = 0.
Interpretation

The upper panel is the realised volatility engine: take daily returns rₜ, compute their sample standard deviation, and annualise it. Moving the “Target path volatility” slider stretches or compresses these bars; σrealised follows.

The lower panel is the option pricing engine: feed a volatility σ into Black–Scholes and read off C(σ). Marking σrealised and σimplied on the same curve shows how far the market’s volatility input can sit from what actually happened in the path. That gap is where volatility risk premium, jump risk and order-flow effects live in practice.