[We develop a simple robust link between deep out-of-the-money American put options on a company's stock and a credit insurance contract on the company's bond. We assume that the stock price stays above a barrier B before default but drops below a lower barrier A after default, thus generating a default corridor [A, B] that the stock price can never enter. Given the presence of this default corridor, a spread between two co-terminal American put options struck within the corridor replicates a pure credit contract, paying off when and only when default occurs prior to the option expiry.]

[We propose a direct and robust method for quantifying the variance risk premium on financial assets. We show that the risk-neutral expected value of return variance, also known as the variance swap rate, is well approximated by the value of a particular portfolio of options. We propose to use the difference between the realized variance and this synthetic variance swap rate to quantify the variance risk premium. Using a large options data set, we synthesize variance swap rates and investigate the historical behavior of variance risk premiums on five stock indexes and 35 individual stocks.]

Options contracts are listed on thousands of stocks with different numbers of contracts per stock. This paper proposes to construct four risk-targeting portfolios to consolidate information in all the option contracts on each stock. A cross-sectional regression identifies the market price of risk on each risk source for each stock at any given date. The market price of risk estimate strongly predicts the excess return of the corresponding risk-targeting portfolio. Long-short portfolio construction on the risk-targeting portfolios in proportion to the market price of risk estimates generates highly positive average excess returns per unit risk across all four risk dimensions.

The Federal Reserve adjusts the federal funds target rate discretely, causing discontinuity in short-term interest rates. Unlike Poisson jumps, these adjustments are well anticipated by the market. We propose a term structure model that incorporates an anticipated jump component with known arrival times but random jump size. We find that doing so improves the model performance in capturing the term structure behavior. The mean jump sizes extracted from the term structure match the realized target rate changes well. Specification analysis indicates that the jump sizes show strong serial dependence and dependence on the interest-rate factors.

Asset pricing tests often replace ex ante return expectation with ex post realization. The large deviation between the two drastically weakens the power of these tests. This paper proposes to use analysts consensus price target for a stock as the market expectation of the stock’s future price to directly construct the stock’s expected excess return. Analyzing the expected excess return behavior both over time and across different stocks shows that classic asset pricing theory works much better on ex ante return expectations than on ex post realizations. The analysis also provides new insights on the pricing of common equity risk factors.

Classic option pricing theory values a derivative contract via dynamic delta hedging and treating the contract as redundant relative to the underlying security. Dynamic delta hedging proves highly effective in practice, but the remaining risk is still large because of the practical limits of arbitrage. Derivatives can play primary roles in risk allocation. This paper quantifies the percentage variance reduction of delta hedging on U.S. stock options, proposes a top-down return attribution framework to identify the remaining risk sources of the delta-hedged option investment, and constructs a statistical return factor model to explain the variations of the delta-hedged option returns.

A major issue with predicting inflation rates using predictive regressions is that estimation errors can overwhelm the information content. This article proposes a new approach that uses a monetary-policy rule as a bridge between inflation rates and short-term interest rates and relies on the forward-interest-rate curve to predict future interest-rate movements. The 2-step procedure estimates the predictive relation not through a predictive regression but far more accurately through the contemporaneous monetary-policy linkage. Historical analysis shows that the approach outperforms random walk out of sample by 30%–50% over horizons from 1 to 5 years.

In this article, we examine the extent to which firm fundamentals can explain the cross-sectional variation in credit default swap (CDS) spreads. We construct a fundamental CDS valuation by combining the Merton distance-to-default measure with a long list of firm fundamentals via a Bayesian shrinkage method. Regressing CDS quotes against the fundamental valuation cross-sectionally generates an average R 2 of 77%. The explanatory power is stable over time and robust in out-of-sample tests. Deviations between market quotes and the valuation predict future market movements. The results highlight the important role played by firm fundamentals in differentiating the credit spreads of different firms.

Dynamic term structure models explain the yield curve variation well but perform poorly in pricing and hedging interest rate options. Most existing option pricing practices take the yield curve as given, thus having little to say about the fair valuation of the underlying interest rates. This paper proposes an m + n model structure that bridges the gap in the literature by successfully pricing both interest rates and interest rate options. The first m factors capture the yield curve variation, whereas the latter n factors capture the interest rate options movements that cannot be effectively identified from the yield curve. We propose a sequential estimation procedure that identifies the m yield curve factors from the LIBOR and swap rates in the first step and the n options factors from interest rate caps in the second step. The three yield curve factors explain over 99% of the variation in the yield curve but account for less than 50% of the implied volatility variation for the caps. Incorporating three additional options factors improves the explained variation in implied volatilities to over 99%.

Classic bond pricing centralizes bond valuation across all maturities by specifying the dynamics of the short-term interest rate. This article develops a decentralized theory that prices each bond based purely on the near-term behavior of the bond’s own yield. The theory levers the domain expertise of an investor on a particular bond and allows the investor to make pricing and investment analysis on the bond without the shackles of an ambitious centralizing mandate. The theory decomposes the short-term return on a bond with respect to the variation of its own yield. Imposing no dynamic arbitrage on the return decomposition leads to a simple pricing equation relating the bond yield to the market pricing and conditional mean and variance forecasts of the yield’s near-term change. The article illustrates the theory’s applications in decentralized investment of a single bond and in the construction and investment of decentralized butterfly bond portfolios.