Ambiguity Measurement

Ordering alternatives by their degree of ambiguity is a crucial element in decision processes in general and in asset pricing in particular. So far the literature has not provided an applicable measure of ambiguity allowing for such ordering. The current paper addresses this need by introducing a novel empirically applicable ambiguity measure derived from a new model of decision making under ambiguity, called shadow probability theory, in which probabilities of events are themselves random. In this model a complete distinction is attained between preferences and beliefs and between risk and ambiguity that enables the degree of ambiguity to be measured. The merits of the model are demonstrated by incorporating ambiguous probabilities into asset pricing and it is proved that the well defined ambiguity premium that the paper proposes can be measured empirically

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

Pricing Systematic Ambiguity in Capital Markets

Asset pricing models assume that probabilities of future outcomes are known. In reality, however, there is ambiguity with regard to these probabilities. Accounting for ambiguity in asset pricing theory results in a model with two systematic components, beta risk and beta ambiguity. The focus of this paper is to study the empirical implications of ambiguity for the cross section of equity returns. We find that systematic ambiguity is an important determinant of equity returns. We also find that the Fama-French factors contribute to the explanatory power of the two main drivers of returns; namely, systematic risk and systematic ambiguity

Bailout Uncertainty in a Microfounded General EquilibriumModeloftheFinancial 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 Gilboa-Schmeidler (1989) maxmin with multiple priors framework to lenders’ beliefs about the probability of bailout. Events like Lehman’s collapse are conceived of as ”black swan” events that led lenders to put a positive mass on bailout probabilities that were previously assigned zero mass. Results of the analysis include: (i) An unanticipated increase in bailout uncertainty raises interest rates, the volume of defaults in both the real and financial sectors and may lead to a total drying up of credit markets. (ii) Lower exante bailout uncertainty is conducive to higher leverage - which raises moral hazard and makes the economy more vulnerable to expost increases in bailout uncertainty. (iii) Bailout uncertainty raises the likelihood of bubbles, the amplitude of booms and busts as well as the banking and the credit spreads. (iv) Bailout uncertainty is associated with higher returns’ variability in diversified portfolios and systemic risks, (v) Expansionary monetary policy reinforces those effects by inducing higher aggregate leverage levels

Asset Prices and Ambiguity

Modern portfolio theory, developed in the expected utility paradigm, focuses on the relationship between risk and return, assuming away ambiguity, uncertainty over the probability space. In this paper, we assume that ambiguity affects asset prices and we test the relationship between risk, ambiguity and return based on a model developed by Izhakian (2011). Our contribution is twofold; we propose an ambiguity measure that is derived theoretically and computed from intraday stock market prices. Second, we use it in conjunction with risk measures to test the basic relationship between risk, ambiguity and return. We find that our ambiguity measure has a consistently negative effect on returns and that our risk measure has mostly a positive effect. The best evidence, judging by statistical significance, is obtained when we use the change in volatility alongside the measure of ambiguity

Asset Pricing and Ambiguity: Empirical Evidence

Modern portfolio theory focuses on the relationship between risk and return, assuming away ambiguity, uncertainty over the probability space. This paper assumes that ambiguity affects asset prices and tests the relationship between risk, ambiguity and return based on a model developed by Izhakian (2011). Its contribution is twofold; it proposes an ambiguity measure that is derived theoretically and computed from stock market prices. Second, it uses ambiguity in conjunction with risk to test the basic relationship between risk, ambiguity and return. This paper finds that ambiguity has a consistently negative effect on returns and risk mostly has a positive effect