Essays on Inference from Option Markets
- Author(s): Dossani, Asad
- Advisor(s): Timmermann, Allan
- et al.
This dissertation consists of three chapters that analyze the economic information contained in option markets. Option markets are forward looking, and thus contain valuable insight into the beliefs of financial market participants. They can be used to study risk premia and to make forecasts. The Chapter 1, Central Bank Tone and Currency Risk Premia, asks how the tone of central bank press conferences impacts risk premia in the currency market. First, I find that option implied risk aversion increases when central banks are hawkish, and decreases when central banks are dovish. Second, I find that hawkish central bank tone predicts higher future variance risk premia, and vice versa. One explanation for this result is that the tone of a press conference indicates to investors the likelihood of central bank intervention, conditional on the state of the economy. Chapter 2, Monetary Stimulus and Perception of Risk, investigates the relationship between monetary stimulus and the perception of risk in financial markets, and how this varies across asset classes. First, I document a positive relationship between monetary stimulus and the perception of risk in equity, commodity, and currency markets. I document a negative relationship between monetary stimulus and the perception of risk in bond markets. Second, I establish a cointegrating relationship between monetary stimulus and implied volatility, indicating a positive long run equilibrium relationship in the levels of monetary stimulus and implied volatility. This relationship is present across asset classes. Third, I document the link between monetary stimulus and expected inflation, a possible mechanism by which monetary stimulus affects the perception of risk across financial markets. Chapter 3, Option Augmented Density Forecasts of Market Return with Monotone Pricing Kernel, considers consider an option augmented density forecast of the market return obtained by transforming a baseline density forecast estimated from past excess returns so as to monotonize its ratio with a risk neutral density estimated from current option prices. We find that monotonizing the pricing kernel leads to a modest improvement in the calibration of density forecasts.