ABSTRACT
This chapter argues that uncertainty prevails in the economy and hence has to play a main tune in economics. It examines a statistical test procedure that allows discrimination between decision making under risk or ambiguity and under uncertainty. The chapter focuses on financial markets because financial markets are supposed to be close to the ideal market with very small frictions, minimum transaction costs and a high degree of liquidity. It aims to develop a model of decision making in financial markets under uncertainty. This model allows to characterise the second moment of an empirical distribution function. It derives the characteristics of empirical distribution functions under the assumption of risk and ambiguity. The chapter explores key properties of the second empirical moment under the assumption that a statistical distribution function exists by assuming that financial markets operate under risk and ambiguity.
