Options Market Ambiguity And Its Application

This thesis enriches the literature by extracting ambiguity from the options market and exploring its information content and applications.Our measurement utilizes the forward-looking features of options markets and is both simpler and more convenient than methods employed in prior studies.Our findings reveal that this measurement plays an important role in the uncertainty premium and can be applied to be a leading indicator of market turbulence or a measure of market-wide overconfidence.Our research indicates that options market ambiguity contains valuable information regarding future market excess returns,both in the U.S.and international markets.Furthermore,we find that the predictive power of options market ambiguity is adjusted by the level of market fear indicated by the implied variance,which is consistent with previous findings in behavioral studies.Additionally,our results suggest that the discount rate is a pivotal channel for the forecasting ability of options market ambiguity.The linkages between options market ambiguity and the bond and CDS spreads provide additional evidence for the relationship between ambiguity and the discount rate.Our research highlights the crucial role that ambiguity plays in asset pricing as another tier of uncertainty.The results also indicate that investors’ attitudes toward ambiguity shift from aversion to seeking in specific situations,suggesting that a more flexible setting of ambiguity attitudes in economic models may improve their accordance with real-world conditions.Moreover,our findings reveal that ambiguity helps clarify the effect of implied variance on discount rate news and establishes a positive relationship between risk and return,providing new validations for the positive risk-return trade-off.We then focus on exploring the relationship between options market ambiguity and the VIX,which has received little attention in existing literature.We observe that these two tiers of uncertainty tend to be positively correlated during periods of market turbulence,while they exhibit a negative correlation during regular periods.To characterize the time-varying ambiguity-risk dependence,we employ the Symmetrized Joe-Clayton(SJC)copula model and extract the expected upper tail dependence using a recursive method.We also consider the expected dependence extracted with the Gumbel copula model for robustness check.From the empirical and statistical perspectives,we primarily concentrate on the change in the expected upper tail dependence to proceed with our investigation.To our knowledge,this is the first attempt to investigate the dependence of ambiguity and risk using statistical models.Our results indicate that the change in the expected upper tail dependence is positively associated with innovations to future financial uncertainty and economic policy uncertainty as measured by extant uncertainty indices.This suggests that the change in the expected upper tail dependence provides incremental information beyond existing uncertainty measures.Furthermore,we find a positive relationship between the change in the expected upper tail dependence and future market variations,particularly the realized jump variation.Including the change in the expected dependence in our analysis enhances the explanation of variations in the market variation,indicating that the change in the expected upper tail dependence serves as a reliable leading indicator of market turbulence.Additionally,our findings suggest that the change in the expected upper tail dependence foreshadows upcoming market declines.A sudden,sharp increase in the expected tail dependence often accompanies a slump in the financial markets.Incorporating this information not only improves the out-of-sample excess market returns prediction but also results in better investment performance than the buy-andhold strategy.Finally,we develop a novel measurement of market-wide overconfidence based on the size of ambiguity(reflecting the confidence of investors in information)in the stock and options markets.Our proposed measure of market-wide overconfidence is consistent with the predictions motivated by prior literature and exhibits a significant negative association with next-month market excess return.Moreover,we observe that the associations between the overconfidence measure and riskier portfolio returns are more pronounced and longer-lasting,indicating a risk-taking tendency among overconfident investors.Our empirical measure of overconfidence provides valuable insights into the influence of overconfidence from an aggregate market perspective.Furthermore,our extraction of overconfidence based on options market data is a meaningful effort to make use of the forward-looking information content of the options market.