Option pricing using high-frequency futures prices
We extract the variance from futures prices instead of the underlying asset price
We calculate the variance in different frequencies with intraday data instead of daily closing prices
We perform the valuation of call and put options for six volatility measures
We realize that the implied volatility exhibits the lowest deviation from the market price
Abstract
Option pricing depends heavily on the volatility measure used. We examine two potential routes to improve the outcome of option pricing: extracting the variance from futures prices instead of the underlying asset prices, and calculating the variance in different frequencies with intraday data instead of daily closing prices. We perform a valuation of call and put options for six volatility measures, namely unconditional volatility, historical volatility, conditional volatility, realized volatility and implied volatility, to examine which one gives the optimal result versus
Risk.net
Quant team’s options-based approach avoids pitfalls of historical data dependence Print this page
As analysts warn about euphoria in US markets and the Cape ratio – economist Robert Shiller’s widely watched metric of stock market frothiness – nears all-time highs, investors could do with a reliable way to detect and measure asset bubbles.
As a matter of course, buy-siders weigh prices against model-derived reference points of fundamental value. But their reliance on historic data can leave these models open to question – especially when conditions change rapidly, as they have this past year
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