By Gustavo M. de Athayde, Renato G. Flôres Jr. (auth.), Christian L. Dunis (eds.)
Advances in Quantitative Asset Management comprises chosen articles which, for the main half, have been offered on the `Forecasting monetary Markets' convention. `Forecasting monetary Markets' is a world convention on quantitative finance that is held in London in could each year. considering the fact that its inception in 1994, the convention has grown in scope and stature to develop into a key overseas assembly aspect for these drawn to quantitative finance, with the participation of prestigious educational and examine associations from around the world, together with significant relevant banks and quantitative fund managers.
The editor has selected to pay attention to advances in quantitative asset administration and, consequently, the papers during this publication are equipped round significant issues: advances in asset allocation and portfolio administration, and modelling chance, go back and correlation.
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Additional resources for Advances in Quantitative Asset Management
FAT TAlLS AND THE CAPITAL ASSET PRICING MODEL 5. 27 PORTFOLIO SELECTION From the treatment in section 2 above, it is clear that there are no obstacles to using quadratic utility which only requires expected returns, variances and covariances. Abbreviating portfolio Rport to Rp, the expected utility function is: E[UQ(Rp)] = W\L - -1 P 2 OJ (OJ - 2) wTVw This may be maximised in the usual way, subject to the budget constraint and any relevant inequality constraints and transactions costs. When the degrees of freedom (0 is large, this is equivalent to conventional quadratic programming (QP) based on p, the degree of risk aversion.
It is generally viewed as one of the cornerstones of modem portfolio theory. Markowitz's approach is essentially based on the efficient frontier concept. e. a set of portfolios such that their expected returns may not increase unless their variance increases. Later, ShaIpe (1964) introduced the so-called capital asset pricing model (CAPM) through an equilibrium model assuming that all agents have similar expectations of the market. In such a case, the efficient frontier represents the convex combination between the riskless asset and the market portfolio.
There are various counter arguments to this (see Levy and Markowitz (1979) for example). However, when returns are normal, these criticisms are irrelevant since the expectations of quadratic and exponential utility functions lead to the same optimal portfolio. This equivalence is not widely known, but was established formally by Kallberg and Ziemba (1983). In the multivariate Student world, this criticism of quadratic utility cannot be avoided. This is because the expected value of the exponential utility does not exist if returns follow a multivariate Student distribution.
Advances in Quantitative Asset Management by Gustavo M. de Athayde, Renato G. Flôres Jr. (auth.), Christian L. Dunis (eds.)