Asset Pricing, Portfolio Choice, Pricing and Hedging of Derivative Instruments, Decisions under Ambiguity (Knightian Uncertainty)
Ambiguous Information, Portfolio Inertia, and Excess Volatility
Journal of Finance, 66(6), 2213-2247, December 2011
Link to Internet Appendix
I study the effects of risk and ambiguity (Knightian uncertainty) on optimal portfolios and equilibrium asset prices when investors receive information that is difficult to link to fundamentals. I show that the desire of investors to hedge ambiguity leads to portfolio inertia and excess volatility. Specifically, when news is surprising, then investors may not react to price changes although there are no transaction costs or other market frictions. Moreover, I show that small shocks to cash flow news, asset betas, or market risk premia may lead to drastic changes in the stock price and hence to excess volatility.
Inflation Risk and Inflation-Protected and Nominal Bonds
I decompose inflation risk into (i) a component that is correlated with real returns on positive-net-supply securities (stocks, real estate, etc.) and factors that determine investors preferences and investment opportunities and (ii) a residual component. In equilibrium, only the first component earns a risk premium. Therefore investors should avoid exposure to the residual component. All nominal bonds, including the nominal money-market account, are equally exposed to the residual component except inflation-protected bonds, which provide a means to hedge it. Every investor should put 100% of his wealth in positive-net-supply securities and inflation-protected bonds and should finance every long/short position in nominal bonds with an equal amount of other nominal bonds or by borrowing/lending in the nominal money market account; i.e. investors should hold a zero-investment portfolio of nominal bonds and the nominal money market account.
Disagreement about Inflation and the Yield Curve
(with Paul Ehling, Michael Gallmeyer, and Christian Heyerdahl-Larsen)
We show theoretically that inflation disagreement drives a wedge between real and nominal yields and raises their levels and volatilities. We demonstrate empirically that an inflation disagreement increase of one standard deviation raises real and nominal yields and their volatilities, break-even inflation, and the inflation risk premium by at least 30% of their respective standard deviations. Inflation disagreement is positively related to consumers’ cross-sectional consumption growth volatility and trading in bonds, interest rate futures, and inflation swaps. Calibrating the model to disagreement, inflation, and yield data reproduces the economically significant impact of inflation disagreement on real and nominal yield curves.
(with Scott Condie and Jayant Ganguli)
We study how information about an asset affects optimal portfolios and equilibrium asset prices when investors are not sure about the model that predicts future asset values and thus treat the information as ambiguous. We show that this ambiguity leads to optimal portfolios that are insensitive to news even though there are no information processing costs or other market frictions. This insensitivity to news occurs even for risky portfolios in contrast to other ambiguity models where it only occurs for the risk-free portfolio. In equilibrium, we show that stock prices may not react to public information that is worse than expected and this mispricing of bad news leads to profitable trading strategies based on public information.
Risk Premia and Sharpe Ratios in a Nonlinear Term Structure Model
(with Peter Feldhuetter and Christian Heyerdahl-Larsen)
We introduce a reduced form term structure model with closed form solutions for yields where the short rate and market prices of risk are nonlinear functions of Gaussian state variables. The nonlinear model with three Gaussian factors matches both the time-variation in expected excess returns and yield volatilities of U.S. Treasury bonds from 1961 to 2014. Yields depend on all three factors, yet the model exhibits features consistent with unspanned risk premia (URP) and unspanned stochastic volatility (USV). The probability of a high volatility scenario increases with the monetary experiment and remains high during the Greenspan area, even though volatilities came back down to normal levels.
Working in Progress:
Expanded Term Structure Models (with Peter Feldhuetter and Christian Heyerdahl-Larsen)
FNCE 206/717 Financial Derivatives