Market microstructure and volatility forecasting

Abstract

This thesis presents three studies in the field of market microstructure and volatil- ity forecasting. The first and second studies explore issues related to computing forward-looking measures of volatility from option prices and their statistical ac- curacy. The third study focuses on the microstructure of the options market and addresses issues related to informed trading in this market. newline newlineOption markets have significant variation in liquidity across different option series. Illiquidity reduces the informativeness of the price. Price information for illiquid options is more noisy, and thus the implied volatilities (ivs) based on these prices are more noisy. In the first study, we propose weighting schemes to estimate iv, which reduce the importance attached to illiquid options. The two indexes using liquidity weights are svix, which is a spread-adjusted volatility index, and TVVix, which is a traded volume weighted vix. We find svix outperforms TVVix, the conventional schemes such as the traditional vxo, or vega weights, and volatility elasticity weights. newlineConcerns about sampling noise arise when a vix estimator is computed by ag- gregating several imprecise implied volatility estimates. In the second study, we propose a bootstrap strategy to measure the imprecision of a model based vix estimator. We find that the imprecision of vix is economically significant. We propose a model selection strategy, where alternative statistical estimators of vix are evaluated based on this imprecision. newline newlineIn the third study, we investigate the informational role of algorithmic traders in the index option market. We analyse a unique dataset to test for information- based trading by looking at the effect of net buying pressure of options on implied volatilities. According to the direction-learning hypothesis, (directional) informed investors net buying pressure of calls (puts) raises the implied volatilities of calls (puts) and lowers the implied volatilities of puts (calls). In addition, their net buying pressure can also predict