Making Parametric Portfolio Policies Work

Making Parametric Portfolio Policies Work
Author: Thomas Gehrig
Publisher:
Total Pages: 25
Release: 2018
Genre: Investment analysis
ISBN:

The implementation of parametric portfolio policies as introduced by Brandt, Santa Clara and Valkanov (RFS 2009) may run into empirical problems. For example, expected utility based on monthly returns of S&P-500 data from 1995-2013 turns non-monotonic for moderate levels of (constant) risk aversion. We establish that in the leading case of constant relative risk aversion (CRRA) strong assumptions on the properties of the returns, the variables used to implement the parametric portfolio policy and the parameter space are necessary to obtain a well defined optimization problem. Without such refinements an interior maximum of the expected utility functional may not exist. We provide economic conditions on the domain and/or the utility functions that overcome such empirical problems and that guarantee the effectiveness of the approach. We illustrate the implications of our improvements by applying parametric portfolio policies to a large universe of stocks.

Parametric Portfolio Policies

Parametric Portfolio Policies
Author: Michael W. Brandt
Publisher:
Total Pages: 68
Release: 2004
Genre: Portfolio management
ISBN:

"We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset's characteristics. The coefficients of this function are found by optimizing the investor's average utility of the portfolio's return over the sample period. Our approach is computationally simple, easily modified and extended, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only difficult to implement for a large number of assets but also yields notoriously noisy and unstable results. Our approach also provides a new test of the portfolio choice implications of equilibrium asset pricing models. We present an empirical implementation for the universe of all stocks in the CRSP-Compustat dataset, exploiting the size, value, and momentum anomalies"--National Bureau of Economic Research web site.

Online-Appendix to

Online-Appendix to
Author: Thomas Gehrig
Publisher:
Total Pages: 102
Release: 2019
Genre:
ISBN:

We provide examples of pitfalls for parametric portfolio policies as introduced by Brandt, Santa Clara and Valkanov. For the leading case of constant relative risk aversion (CRRA) strong assumptions on the properties of the returns, the variables used to implement the parametric portfolio policy and the parameter space are necessary to obtain a well defined optimization problem. As possible remedies for practical work various extensions of CRRA Bernoulli utility to the real line are discussed. Also prospect theory is suggested as an alternative approach. We observe that for low levels of relative risk aversion expected utility turns non-monotonic and an interior maximum need not exist. We provide economic conditions that overcome such empirical problems and that guarantee the effectiveness of the approach more broadly. We illustrate our concerns by applying parametric portfolio policies to a large universe of stocks.Full paper is available at: "https://ssrn.com/abstract=3081100" https://ssrn.com/abstract=3081100.

Deep Parametric Portfolio Policies

Deep Parametric Portfolio Policies
Author: Frederik Simon
Publisher:
Total Pages: 0
Release: 2023
Genre:
ISBN:

We directly optimize portfolio weights as a function of firm characteristics via deep neural networks by generalizing the parametric portfolio policy framework. Our results show that network-based portfolio policies result in an increase of investor utility of between 30 and 100 percent over a comparable linear portfolio policy, depending on whether portfolio restrictions on individual stock weights, short-selling or transaction costs are imposed, and depending on an investor's utility function. We provide extensive model interpretation and show that network-based policies better capture the non-linear relationship between investor utility and firm characteristics. Improvements can be traced to both variable interactions and non-linearity in functional form. Both the linear and the network-based approach agree on the same dominant predictors, namely past return-based firm characteristics.

Empirical Asset Pricing

Empirical Asset Pricing
Author: Wayne Ferson
Publisher: MIT Press
Total Pages: 497
Release: 2019-03-12
Genre: Business & Economics
ISBN: 0262039370

An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.

Portfolio Optimization with Alternative Risk Premia

Portfolio Optimization with Alternative Risk Premia
Author: Philipp Müller
Publisher:
Total Pages:
Release: 2019
Genre:
ISBN:

This thesis adds to the literature on portfolio optimisation by analysing how to optimise a portfolio investing solely in equity alternative risk premia. Alternative risk premia feature attractive diversification properties across all market environments. Yet, some of the premia exhibit severe tail risk. In an attempt to reduce the negative impact of extreme events on portfolio performance, portfolio optimisation methods incorporating tail risk are examined. Empirical analysis over a period of close to 50 years reveals that tail risk based top-down optimisation methods do not deliver significantly improved risk and return properties compared to top-down optimisation methods focusing on the first two moments only. In contrast, traditional optimisation approaches like risk parity and inverse volatility weighting proof to be of high relevance. Further, bottom-up optimisation in the form of parametric portfolio policies with predictor variables on the market environment yield portfolios with highly improved downside risk measures compared to all topdown optimisation methods considered.