Yehuda Izhakian

The Uncertainty Premium in an Ambiguous Economy

Theuncertainty premiumis the premium that is derived from not knowing the sure outcome (risk premium) and from not knowing the precise odds of outcomes (ambiguity premium). We generalize Pratts risk premium to uncertainty premium based on Klibanoffet al.s (2005) smooth model of ambiguity. We show that the uncertainty premium can decrease with an increase in decision makers risk aversion. This happens because increasing risk aversion always results in a lower ambiguity premium. The positive ambiguity premium may provide an additional explanation to the equity premium puzzle.

Bailout Uncertainty in a Microfounded General Equilibrium Model of the Financial System

This paper develops a micro-founded general equilibrium model of the financial system composed of ultimate borrowers, ultimate lenders and financial intermediaries. The model is used to investigate the impact of uncertainty about the likelihood of governmental bailouts on leverage, interest rates, the volume of defaults and the real economy. The distinction between risk and uncertainty is implemented by applying the multiple priors framework to beliefs about the probability of bailout.

Expected utility with uncertain probabilities theory

This paper introduces a model of decision making under ambiguity by extending the Bayesian approach to uncertain probabilities. In this model, preferences for ambiguity pertain directly to probabilities such that attitude toward ambiguity is defined as attitude toward mean-preserving spreads in probabilities—analogous to the Rothschild–Stiglitz risk attitude toward mean-preserving spreads in outcomes. The model refines the separations between tastes and beliefs, and between risk and ambiguity. These separations are crucial for the measurement of the degree of ambiguity and for the elicitation and characterization of attitudes toward ambiguity, thereby providing an empirically and experimentally applicable framework.

Capital Asset Pricing Under Ambiguity

This paper generalizes the mean–variance preferences to mean–variance–ambiguity preferences by relaxing the standard assumption that probabilities are known and assuming that probabilities are themselves random. It introduces a new measure of uncertainty, one that consolidates risk and ambiguity, which is employed for extending the CAPM from risk to uncertainty by incorporating ambiguity. This model makes the distinction between systematic ambiguity and idiosyncratic ambiguity and proves that the ambiguity premium is proportional to the systematic ambiguity. The merit of this model is twofold: first, it can be tested empirically; second, it can serve for measuring the performance of portfolios relative to their uncertainty.

Ambiguity and Overconfidence

There are two phenomena in behavioral finance and economics which are seemingly unrelated and have been studied separately; overconfidence and ambiguity aversion. In this paper we are trying to link these two phenomena providing a theoretical foundation supported by evidence from an experimental study. We derive a model, based on the max-min ambiguity framework that links overconfidence to ambiguity aversion. In the experimental study we find that overconfidence is decreasing in ambiguity, as predicted by our model.

Ambiguity, Volatility, and Credit Risk

We explore the implications of ambiguity, or Knightian uncertainty, for the pricing of credit default swaps (CDS). We find that ambiguity, as opposed to risk, has a negative impact on spreads, and its economic significance is as important as that of risk. A one standard deviation increase in the level of ambiguity is associated with a decrease in spreads of at least six percent. Our analysis provides broader insights for the impact of ambiguity on the pricing of other classes of insurance claims and equity options.

Shadow Probability Theory for Asset Pricing under Ambiguity

Assuming that probabilities (capacities) of events are random, this paper introduces a novel model of decision making under ambiguity, called Shadow probability theory, a generalization of the Choquet expected utility. In this model, probabilities of observable events in a subordinated outcome-space are dominated by second-order unobservable events in a directing probability space. The level of ambiguity, and the decision maker’s attitude toward it, are measured with respect to the directing space. Risk and risk attitude, on the other hand, apply to the subordinated space, as in classical expected utility theory. The desired distinction between preferences and beliefs and between risk and ambiguity is then obtained. A measure of ambiguity is naturally carried over on these settings. The present paper proves that in most cases ambiguity cannot be diversified. Counterintuitively, adding an ambiguous lottery to a portfolio of lotteries usually increases its ambiguity. This result, which implies that full diversification is not always optimal, challenges the common notion in the financial literature that investors should hold a fully diversified portfolio. Using this model of choice, the current paper generalizes the classical asset pricing theory by incorporating ambiguous probabilities. It proposes a well defined ambiguity premium that can be measured empirically.

Ambiguity, Risk, and Dividend Payout Policy

We study the effect of ambiguity — Knightian uncertainty — on payout policy. We find that firm-level ambiguity increases and accelerates payout, via both dividends and share repurchases. This positive effect of ambiguity is distinct from the known negative effect of risk on payout policy. Ambiguity leads ambiguity-averse investors to overweight the likelihoods of bad outcomes and underweight the likelihoods of good outcomes, so the attractiveness of investment opportunities decreases in ambiguity, which may increase investors’ preferences for cash payout. Consistent with this positive effect of ambiguity on payout, we find that dividend initiation announcement returns increase in ambiguity.

Ambiguity and the Tradeoff Theory of Capital Structure

We examine the importance of ambiguity, or Knightian uncertainty, in the capital structure decision. We develop a static tradeoff theory model in which agents are both risk averse and ambiguity averse. The model confirms the usual idea that increased risk—the uncertainty over known possible outcomes—leads firms to use less leverage. Conversely, greater ambiguity—the uncertainty over the probabilities associated with the outcomes—leads firms to increase leverage. Using a theoretically motivated measure of ambiguity, our empirical analysis provides results consistent with these predictions.

Ambiguity and Disclosure in The Principal-Agent Model

A Principal-Agent model is examined in which the principal and the agent are ambiguity averse. With a risk neutral principal and a risk averse agent the presence of ambiguity aversion implies that the principal will not always fully insure the agent when effort is observable. Instead, risk may be introduced into the incentive scheme to take advantage of differences in ambiguity aversion. When effort is unobservable, depending on the relative ambiguity aversion of the principal and the agent, ambiguity aversion may increase or decrease the strength of the pay for performance relation relative to the standard model. A superiorly informed principal has an incentive to disclose information to the agent in order to alter the level of ambiguity perceived by the agent. Depending on the agents risk aversion and on the relative levels of ambiguity aversion, the principal may have an interest in decreasing or increasing the ambiguity the agent perceives.