Robustness and Pricing with Uncertain Growth

Abstract

We study how decision makers' concerns about robustness affect prices and quantities in a stochastic growth model. In the model economy, growth rates in technology are altered by infrequent large shocks and continuous small shocks. An investor observes movements in the technology level but cannot perfectly distinguish their sources. Instead the investor solves a signal extraction problem. We depart from most of the macroeconomics and finance literature by presuming that the investor treats the specification of technology evolution as an approximation. To promote a decision rule that is robust to model misspecification, an investor acts as if a malevolent player threatens to perturb the actual data generating process relative to his approximating model. We study how a concern about robustness alters asset prices. We show that the dynamic evolution of the risk-return tradeoff is dominated by movements in the growth-state probabilities and that the evolution of the dividend-price ratio is driven primarily by the capital-technology ratio.

The Worst Case for Real Options

“…The firm wants to determine the optimal time to pay a sunk cost I to get access to the profit stream described under (1). 1 Suppose that the investment be undertaken at time t. The value of the project installed, W t , equals the expected present value of the profit flow generated by the project during its life-time τ :…”

“…1 Suppose that the investment be undertaken at time t. The value of the project installed, W t , equals the expected present value of the profit flow generated by the project during its life-time τ :…”

“…Motivated by statistical evidence, we assume that, based on the current state of the market, the firm is somehow able to estimate the rate of technological progress, but at the same time the firm suspects that this estimation may turn out to be incorrect in future. For instance, such a situation occurs in today's practice in fast developing industries due to the presence of high frequency shocks linked with forthcoming technological innovations (see [1]). …”

Ambiguity in Asset Markets: Theory and Experiment

“…A related literature, including Epstein & Wang (1994), Uppal & Wang (2003), Cagetti, Hansen, Sargent & Williams (2002), Maenhout (2004), Skiadas (2008), Trojani, Leippold & Vanini (2007), seeks to explain the equity premium puzzle (high average returns on equity and low average riskfree rate) by appealing to ambiguity (which they call "Knightian" or "model" uncertainty) on the basis of a model with an ambiguity averse representative agent. However, we show that ambiguity aversion does not aggregate across a heterogeneous population, so that prices may not be rationalizable by an ambiguity averse representative agent.…”

Real Options With Priced Regime-Switching Risk

“…7 Veronesi (1999) and Cagetti, Hansen, Sargent, and Williams (2002) extend this specification to unobservable states.…”