This chapter gives an overview of current research in evolutionary -nance. We mainly focus on the survival and stability properties ofinvestment strategies associated with the Kelly rule. Our approach tothe study of the wealth dynamics of investment strategies is inspired byDarwinian ideas on...

The paper examines a game-theoretic evolutionary model of a …-nancial market with endogenous equilibrium asset prices. Assetspay dividends that are partially consumed and partially rein-vested. The traders use general, adaptive strategies (portfoliorules), distributing their wealth between...

The paper examines a game-theoretic model of a …nancial market inwhich asset prices are determined endogenously in terms of short-runequilibrium. Investors use general, adaptive strategies depending onthe exogenous states of the world and the observed history of thegame. The main goal is to...

Evolutionary nance studies the dynamic interaction of investment strategies in nancialmarkets. This market interaction generates a stochastic wealth dynamics on aheterogenous population of traders through the uctuation of asset prices and theirrandom payos. Asset prices are endogenously...

The paper examines a game-theoretic evolutionary model of anasset market with endogenous equilibrium asset prices. Assetspay dividends that are partially consumed and partially rein-vested. The investors use general, adaptive strategies (portfo-lio rules), distributing their wealth between...

A considerable theoretical and empirical literature studies the corporation's capital structure. Economists have paid less attention to capital structure in other enterprise forms such as partnerships, which typically operate under different legal constraints and appeal to smaller enterprises....

This paper develops the regime classification algorithm and applies it within a fully-edged pairs trading framework on minute-by-minute data of the S&P 500 constituents from 1998 to 2015. Specifically, the highly flexible algorithm automatically determines the number of regimes for any...

Over the past 15 years,there have been a number of studies using text mining for predicting stock market data. Two recent publications employed support vector machines and second-order Factorization Machines, respectively, to this end. However, these approaches either completely neglect...