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Author: Giorgio Costa
Publisher:
ISBN:
Category :
Languages : en
Pages : 33
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Book Description
We formulate a novel Markov regime-switching factor model to describe the cyclical nature of asset returns in modern financial markets. Maintaining a factor model structure allows us to easily derive the asset expected returns and their corresponding covariance matrix. By design, these two parameters are calibrated to better describe the properties of the different market regimes. In turn, these regime-dependent parameters serve as the inputs during mean-variance optimization, thereby constructing portfolios adapted to the current market environment. Through this formulation, the proposed model allows for the construction of large, realistic portfolios at no additional computational cost during optimization. Moreover, the viability of this model can be significantly improved by periodically re-balancing the portfolio, ensuring proper alignment between the estimated parameters and the transient market regimes. An out-of-sample computational experiment over a long investment horizon shows that the proposed regime-dependent portfolios are better aligned with the market environment, yielding a higher ex post rate of return and lower volatility than competing portfolios.
Author: Giorgio Costa
Publisher:
ISBN:
Category :
Languages : en
Pages : 33
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Book Description
We formulate a novel Markov regime-switching factor model to describe the cyclical nature of asset returns in modern financial markets. Maintaining a factor model structure allows us to easily derive the asset expected returns and their corresponding covariance matrix. By design, these two parameters are calibrated to better describe the properties of the different market regimes. In turn, these regime-dependent parameters serve as the inputs during mean-variance optimization, thereby constructing portfolios adapted to the current market environment. Through this formulation, the proposed model allows for the construction of large, realistic portfolios at no additional computational cost during optimization. Moreover, the viability of this model can be significantly improved by periodically re-balancing the portfolio, ensuring proper alignment between the estimated parameters and the transient market regimes. An out-of-sample computational experiment over a long investment horizon shows that the proposed regime-dependent portfolios are better aligned with the market environment, yielding a higher ex post rate of return and lower volatility than competing portfolios.
Author: Saurabh Gokhale
Publisher:
ISBN:
Category :
Languages : en
Pages : 58
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Book Description
We propose to separate returns and macro-indicators into regimes and use regime-specific mean returns and covariances for better portfolio construction. We fit a multivariate Gaussian mixture process to observable regime indicators along with a Hidden Markov Model for the unobservable state. We then use the fitted regimes and transition matrix to construct different portfolios based on a probability-weighted average of returns and covariances. Our backtesting uses long-short factor returns as well as industry returns. We find the evidence that regime aware optimizations perform better than the popular mean-variance optimization without assumptions of regimes and has higher out-of-sample expected return and lower skewness, kurtosis, and drawdowns.
Author: Sarthak Garg
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The aim of this thesis is to develop a Markov Regime Switching framework that can be used in asset allocation in conjunction with Modern Portfolio Theory. Modern Portfolio Theory has long been a popular tool among big financial institutions. However, one of its major limitations is assumption of stationary market volatility. In this paper, we develop a single period Mean Variance Optimization model that minimizes the variance of a portfolio subject to a specified expected return by combining Modern Portfolio Theory with a Markov Regime Switching framework. Then, we extend the above developed framework to be used in conjunction with a robust optimization framework as proposed by Goldfarb Iyengar in which regards we were partially successful. The portfolios constructed by the Markov Regime-Switching framework were tested out of sample to outperform those suggested by a Simple MVO One Factor model and the Robust MVO One Factor Model.
Author: Stephen Boyd
Publisher:
ISBN: 9781680833287
Category : Mathematics
Languages : en
Pages : 92
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Book Description
This monograph collects in one place the basic deļ¬nitions, a careful description of the model, and discussion of how convex optimization can be used in multi-period trading, all in a common notation and framework.
Author: Houmin Yan
Publisher: Springer Science & Business Media
ISBN: 0387338152
Category : Technology & Engineering
Languages : en
Pages : 397
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Book Description
This edited volume contains 16 research articles. It presents recent and pressing issues in stochastic processes, control theory, differential games, optimization, and their applications in finance, manufacturing, queueing networks, and climate control. One of the salient features is that the book is highly multi-disciplinary. The book is dedicated to Professor Suresh Sethi on the occasion of his 60th birthday, in view of his distinguished career.
Author: Greg N. Gregoriou
Publisher: CRC Press
ISBN: 1420099558
Category : Business & Economics
Languages : en
Pages : 654
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Book Description
Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel
Author: G. George Yin
Publisher: Springer Science & Business Media
ISBN: 1461443466
Category : Mathematics
Languages : en
Pages : 442
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Book Description
This book gives a systematic treatment of singularly perturbed systems that naturally arise in control and optimization, queueing networks, manufacturing systems, and financial engineering. It presents results on asymptotic expansions of solutions of Komogorov forward and backward equations, properties of functional occupation measures, exponential upper bounds, and functional limit results for Markov chains with weak and strong interactions. To bridge the gap between theory and applications, a large portion of the book is devoted to applications in controlled dynamic systems, production planning, and numerical methods for controlled Markovian systems with large-scale and complex structures in the real-world problems. This second edition has been updated throughout and includes two new chapters on asymptotic expansions of solutions for backward equations and hybrid LQG problems. The chapters on analytic and probabilistic properties of two-time-scale Markov chains have been almost completely rewritten and the notation has been streamlined and simplified. This book is written for applied mathematicians, engineers, operations researchers, and applied scientists. Selected material from the book can also be used for a one semester advanced graduate-level course in applied probability and stochastic processes.
Author: Emmanuel Jurczenko
Publisher: Elsevier
ISBN: 0081008112
Category : Business & Economics
Languages : en
Pages : 488
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Book Description
This book is a compilation of recent articles written by leading academics and practitioners in the area of risk-based and factor investing (RBFI). The articles are intended to introduce readers to some of the latest, cutting edge research encountered by academics and professionals dealing with RBFI solutions. Together the authors detail both alternative non-return based portfolio construction techniques and investing style risk premia strategies. Each chapter deals with new methods of building strategic and tactical risk-based portfolios, constructing and combining systematic factor strategies and assessing the related rules-based investment performances. This book can assist portfolio managers, asset owners, consultants, academics and students who wish to further their understanding of the science and art of risk-based and factor investing. Contains up-to-date research from the areas of RBFI Features contributions from leading academics and practitioners in this field Features discussions of new methods of building strategic and tactical risk-based portfolios for practitioners, academics and students
Author: Massih-Reza Amini
Publisher: Springer Nature
ISBN: 3031264223
Category : Computers
Languages : en
Pages : 712
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Book Description
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; . Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.
Author: Tim Siu-tang Leung
Publisher: World Scientific
ISBN: 9814725935
Category : Business & Economics
Languages : en
Pages : 221
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Book Description
Optimal Mean Reversion Trading: Mathematical Analysis and Practical Applications provides a systematic study to the practical problem of optimal trading in the presence of mean-reverting price dynamics. It is self-contained and organized in its presentation, and provides rigorous mathematical analysis as well as computational methods for trading ETFs, options, futures on commodities or volatility indices, and credit risk derivatives.This book offers a unique financial engineering approach that combines novel analytical methodologies and applications to a wide array of real-world examples. It extracts the mathematical problems from various trading approaches and scenarios, but also addresses the practical aspects of trading problems, such as model estimation, risk premium, risk constraints, and transaction costs. The explanations in the book are detailed enough to capture the interest of the curious student or researcher, and complete enough to give the necessary background material for further exploration into the subject and related literature.This book will be a useful tool for anyone interested in financial engineering, particularly algorithmic trading and commodity trading, and would like to understand the mathematically optimal strategies in different market environments.
