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The aim of this paper is to show the expected utility theory over time and its evolution onto what is now known as the risk aversion theory. This paper also highlights the importance of the link between the relative risk aversion and the selection of an optimum investment portfolio (Relative Risk Aversion v/s Portfolio Choice).This document also encompasses the basic axioms or maxims applicable to the utility functions developed in microeconomics. It also includes topics such as making a choice under conditions of uncertainty and analysis of the existing expected utility models checking their consistency.Furthermore, in the same context, it carried out an analysis of the risk aversion theory developed by Pratt and Arrow by using the relative risk aversion as the main was of measuring risk. The consistency of the main existing models quoted in the current textbooks and related literature which links the risk tolerance with the portfolio choice is put to the test through a sample transacted at Santiago stock exchange.The paper goes on to suggest, on the basis of the theoretical development described in it, a new approach aimed atthe identification of optimum portfolios by means of the relative risk aversion approach.
This brief offers a broad, yet concise, coverage of portfolio choice, containing both application-oriented and academic results, along with abundant pointers to the literature for further study. It cuts through many strands of the subject, presenting not only the classical results from financial economics but also approaches originating from information theory, machine learning and operations research. This compact treatment of the topic will be valuable to students entering the field, as well as practitioners looking for a broad coverage of the topic.
Academic finance has had a remarkable impact on many financial services. Yet long-term investors have received curiously little guidance from academic financial economists. Mean-variance analysis, developed almost fifty years ago, has provided a basic paradigm for portfolio choice. This approach usefully emphasizes the ability of diversification to reduce risk, but it ignores several critically important factors. Most notably, the analysis is static; it assumes that investors care only about risks to wealth one period ahead. However, many investors—-both individuals and institutions such as charitable foundations or universities—-seek to finance a stream of consumption over a long lifetime. In addition, mean-variance analysis treats financial wealth in isolation from income. Long-term investors typically receive a stream of income and use it, along with financial wealth, to support their consumption. At the theoretical level, it is well understood that the solution to a long-term portfolio choice problem can be very different from the solution to a short-term problem. Long-term investors care about intertemporal shocks to investment opportunities and labor income as well as shocks to wealth itself, and they may use financial assets to hedge their intertemporal risks. This should be important in practice because there is a great deal of empirical evidence that investment opportunities—-both interest rates and risk premia on bonds and stocks—-vary through time. Yet this insight has had little influence on investment practice because it is hard to solve for optimal portfolios in intertemporal models. This book seeks to develop the intertemporal approach into an empirical paradigm that can compete with the standard mean-variance analysis. The book shows that long-term inflation-indexed bonds are the riskless asset for long-term investors, it explains the conditions under which stocks are safer assets for long-term than for short-term investors, and it shows how labor income influences portfolio choice. These results shed new light on the rules of thumb used by financial planners. The book explains recent advances in both analytical and numerical methods, and shows how they can be used to understand the portfolio choice problems of long-term investors.