infonet-economy

This thesis considers two main subjects divided in four problems in the broad field of mathematical finance. The first chapter treats option pricing followed by three chapters on the application of the machine learning algorithm of Random Forests to finance, specifically to risk capital aggregation, portfolio optimization and macro stress testing. In all four chapters new...

An overwhelmingly large number of research studies in corporate Finance span the basis formed by chiefly three corporate policies - Financial policy (leverage), dividend policy, and investment policy. The two most oft-cited frictions, agency issues and asymmetric information, add complexities to the nexus formed by the policies. My empirical dissertation, "Three essays in real...

In this a paper a non-linear macro-stress testing methodology with focus on early warning is developed. The methodology builds on a variant of Random Forests and its proximity measures. It develops a framework in which naturally defined contagion and feedback effects transfer the impact of stressing a relatively small part of the observations on the whole dataset and thus allow to...

Most articles on sports economics presume the well-known Nash equilibrium concept. In this article, however, we apply evolutionary game theory in a sports-contest model. If clubs follow evolutionarily stable strategies (ESS), then ESS generate greater investments and smaller profits than predicted by Nash’s strategies, independent of whether a club is win-maximizing or profit-...

An infinite-horizon asset-pricing model with heterogeneous agents and collateral constraints can explain why adjustments in stock market margins under US Regulation T had an economically insignificant impact on market volatility. In the model, raising the margin requirement for one asset class may barely affect its volatility if investors have access to another, unregulated class of...