Financial Engineering

In asset pricing models, the uncertainty surrounding firm fundamentals plays a central role, driving expected returns, volatility, and valuation ratios. In this paper, we extract estimates of the uncertainty embedded in earnings announcements using option prices. To do this, we take seriously the fact that the timing of earnings announcements, although not the response of equity prices, is known in advance. We develop a no-arbitrage option pricing model incorporating jumps on earnings announcement dates.

In a contingent claims framework, with a single issue of debt and full information, we show that the presence of a bankruptcy code with automatic stay, absolute priority rules, and potential debt forgiveness, can lead to significant conflicts of interest between the borrowers and lenders. In the first-best outcome, the code can add significant value to both parties by way of higher debt capacity, lower spreads, and improvement in the overall value of the firm.

This paper examines transfer pricing in multinational firms when individual divisions face different income tax rates. Assuming that a firm decouples its internal transfer price from the arm's length price used for tax purposes, we analyze the effectiveness of alternative pricing rules under both cost- and market-based transfer pricing. In a tax-free world, Hirshleifer (1956) advocated that the internal transfer price be set equal to the marginal cost of the supplying division.

We propose that consumers' investment decisions involve processes of promotion and prevention self-regulation that are managed across separate mental accounts, with different financial products seen as representative of promotion versus prevention.

An American option grants the holder the right to select the time at which to exercise the option, so pricing an American option entails solving an optimal stopping problem. Difficulties in applying standard numerical methods to complex pricing problems have motivated the development of techniques that combine Monte Carlo simulation with dynamic programming. One class of methods approximates the option value at each time using a linear combination of basis functions, and combines Monte Carlo with backward induction to estimate optimal coefficients in each approximation.

This paper proves a convergence result for a discretization scheme for simulating jumpdiffusion processes with state-dependent jump intensities. With a bound on the intensity, the point process of jump times can be constructed by thinning a Poisson random measure using state-dependent thinning probabilities. Between the jump epochs of the Poisson random measure, the dynamics of the constructed process are purely diffusive and may be simulated using standard discretization methods.

I propose an intertemporal precautionary saving model in which the agent's labor income is subject to (possibly correlated) shocks with different degrees of persistence and volatility. However, he only observes his total income, not individual components. I show that partial observability of individual components of income gives rise to additional precautionary saving due to estimation risk, the error associated with estimating individual components of income. This additional precautionary saving is higher, when estimation risk is greater.

This paper surveys the literature on option pricing, from its origins to the present. An extensive review of valuation methods for European- and American-style claims is provided. Applications to complex securities and numerical methods are surveyed. Emphasis is placed on recent trends and developments in methodology and modeling.