A Beta Return Efficient Portfolio Optimisation Following The Capm
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A Beta-return Efficient Portfolio Optimisation Following the CAPM
Investors are trying to generate excess returns through active investment strategies. Since the outbreak of the financial crisis, investors face a situation where increased risks are accompanied by falling key interest rates. An optimal portfolio in terms of risk and return becomes a perpetual motion machine. Markus Vollmer answers the question how the seemingly impossible could still be achieved by an empirical analysis of historical data of 1’800 stocks listed at equity markets in 24 countries covering all 19 super sectors. The author offers valid and reliable findings by using the previously mentioned data proxy. He reveals purposefully the need for further research and simultaneously he derives specific and applicable guidelines for the design of investment strategies which are extremely exciting for both the institutional expert and the private investor.
Introduction to Risk Parity and Budgeting
Although portfolio management didn't change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management. Risk parity then became a popular financial model of investment after the global fina
Quantitative Portfolio Optimization
Author: Miquel Noguer Alonso
language: en
Publisher: John Wiley & Sons
Release Date: 2025-01-29
Expert guidance on implementing quantitative portfolio optimization techniques In Quantitative Portfolio Optimization: Theory and Practice, renowned financial practitioner Miquel Noguer, alongside physicists Alberto Bueno Guerrero and Julian Antolin Camarena, who possess excellent knowledge in finance, delve into advanced mathematical techniques for portfolio optimization. The book covers a range of topics including mean-variance optimization, the Black-Litterman Model, risk parity and hierarchical risk parity, factor investing, methods based on moments, and robust optimization as well as machine learning and reinforcement technique. These techniques enable readers to develop a systematic, objective, and repeatable approach to investment decision-making, particularly in complex financial markets. Readers will gain insights into the associated mathematical models, statistical analyses, and computational algorithms for each method, allowing them to put these techniques into practice and identify the best possible mix of assets to maximize returns while minimizing risk. Topics explored in this book include: Specific drivers of return across asset classes Personal risk tolerance and it#s impact on ideal asses allocation The importance of weekly and monthly variance in the returns of specific securities Serving as a blueprint for solving portfolio optimization problems, Quantitative Portfolio Optimization: Theory and Practice is an essential resource for finance practitioners and individual investors It helps them stay on the cutting edge of modern portfolio theory and achieve the best returns on investments for themselves, their clients, and their organizations.