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| Author | : Bernd Scherer |
| Publisher | : Oxford University Press |
| Total Pages | : 530 |
| Release | : 2012 |
| Genre | : Business & Economics |
| ISBN | : 0199553432 |
This book explores the current state of the art in quantitative investment management across seven key areas. Chapters by academics and practitioners working in leading investment management organizations bring together major theoretical and practical aspects of the field.
| Author | : Kenneth J. Winston |
| Publisher | : Cambridge University Press |
| Total Pages | : 647 |
| Release | : 2023-09-21 |
| Genre | : Business & Economics |
| ISBN | : 1009209086 |
A modern introduction to risk and portfolio management for advanced undergraduate and beginning graduate students who will become practitioners in the field of quantitative finance, including extensive live data and Python code as online supplements which allow the application of theory to real-world situations.
| Author | : Christian Dunis |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 345 |
| Release | : 2012-12-06 |
| Genre | : Business & Economics |
| ISBN | : 1461543894 |
Advances in Quantitative Asset Management contains selected articles which, for the most part, were presented at the `Forecasting Financial Markets' Conference. `Forecasting Financial Markets' is an international conference on quantitative finance which is held in London in May every year. Since its inception in 1994, the conference has grown in scope and stature to become a key international meeting point for those interested in quantitative finance, with the participation of prestigious academic and research institutions from all over the world, including major central banks and quantitative fund managers. The editor has chosen to concentrate on advances in quantitative asset management and, accordingly, the papers in this book are organized around two major themes: advances in asset allocation and portfolio management, and modelling risk, return and correlation.
| Author | : Kenneth Winston |
| Publisher | : Cambridge University Press |
| Total Pages | : 647 |
| Release | : 2023-09-30 |
| Genre | : Business & Economics |
| ISBN | : 1009209043 |
A book combining the rigour of academic finance with the pragmatism of hands-on finance.
| Author | : Özalp Özer |
| Publisher | : Oxford University Press (UK) |
| Total Pages | : 977 |
| Release | : 2012-06-07 |
| Genre | : Business & Economics |
| ISBN | : 0199543178 |
A definitive reference to the theory and practice of pricing across industries, environments, and methodologies. It covers all major areas of pricing including, pricing fundamentals, pricing tactics, and pricing management.
| Author | : Karen Wendt |
| Publisher | : Springer Nature |
| Total Pages | : 334 |
| Release | : |
| Genre | : |
| ISBN | : 3031555058 |
| Author | : Ignazio Basile |
| Publisher | : Springer |
| Total Pages | : 469 |
| Release | : 2016-07-27 |
| Genre | : Business & Economics |
| ISBN | : 3319327968 |
This book analyses investment management policies for institutional investors. It is composed of four parts. The first one analyses the various types of institutional investors, institutions which, with different objectives, professionally manage portfolios of financial and real assets on behalf of a wide variety of individuals. This part goes on with an in-depth analysis of the economic, technical and regulatory characteristics of the different types of investment funds and of other types of asset management products, which have a high rate of substitutability with investment funds and represent their natural competitors. The second part of the book identifies and investigates the stages of the investment portfolio management. Given the importance of strategic asset allocation in explaining the ex post performance of any type of investment portfolio, this part provides an in-depth analysis of asset allocation methods, illustrating the different theoretical and operational solutions available to institutional investors. The third part describes performance assessment, its breakdown and risk control, with an in-depth examination of performance evaluation techniques, returns-based style analysis approaches, and performance attribution models. Finally, the fourth part deals with the subject of diversification into alternative asset classes, identifying the common characteristics and their possible role within the framework of investment management policies. This part analyses hedge funds, private equity, real estate, commodities, and currency overlay techniques.
| Author | : Henry Schellhorn |
| Publisher | : SIAM |
| Total Pages | : 267 |
| Release | : 2024-03-26 |
| Genre | : Computers |
| ISBN | : 1611977908 |
This textbook covers the latest advances in machine learning methods for asset management and asset pricing. Recent research in deep learning applied to finance shows that some of the (usually confidential) techniques used by asset managers result in better investments than the more standard techniques. Cutting-edge material is integrated with mainstream finance theory and statistical methods to provide a coherent narrative. Coverage includes an original machine learning method for strategic asset allocation; the no-arbitrage theory applied to a wide portfolio of assets as well as other asset management methods, such as mean-variance, Bayesian methods, linear factor models, and strategic asset allocation; recent techniques such as neural networks and reinforcement learning, and more classical ones, including nonlinear and linear programming, principal component analysis, dynamic programming, and clustering. The authors use technical and nontechnical arguments to accommodate readers with different levels of mathematical preparation. The book is easy to read yet rigorous and contains a large number of exercises. Machine Learning for Asset Management and Pricing is intended for graduate students and researchers in finance, economics, financial engineering, and data science focusing on asset pricing and management. It will also be of interest to finance professionals and analysts interested in applying machine learning to investment strategies and asset management. This textbook is appropriate for courses on asset management, optimization with applications, portfolio theory, and asset pricing.
| Author | : Michael Isichenko |
| Publisher | : John Wiley & Sons |
| Total Pages | : 311 |
| Release | : 2021-08-31 |
| Genre | : Business & Economics |
| ISBN | : 1119821320 |
Discover foundational and advanced techniques in quantitative equity trading from a veteran insider In Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage, distinguished physicist-turned-quant Dr. Michael Isichenko delivers a systematic review of the quantitative trading of equities, or statistical arbitrage. The book teaches you how to source financial data, learn patterns of asset returns from historical data, generate and combine multiple forecasts, manage risk, build a stock portfolio optimized for risk and trading costs, and execute trades. In this important book, you’ll discover: Machine learning methods of forecasting stock returns in efficient financial markets How to combine multiple forecasts into a single model by using secondary machine learning, dimensionality reduction, and other methods Ways of avoiding the pitfalls of overfitting and the curse of dimensionality, including topics of active research such as “benign overfitting” in machine learning The theoretical and practical aspects of portfolio construction, including multi-factor risk models, multi-period trading costs, and optimal leverage Perfect for investment professionals, like quantitative traders and portfolio managers, Quantitative Portfolio Management will also earn a place in the libraries of data scientists and students in a variety of statistical and quantitative disciplines. It is an indispensable guide for anyone who hopes to improve their understanding of how to apply data science, machine learning, and optimization to the stock market.
| Author | : M.A.H. Dempster |
| Publisher | : CRC Press |
| Total Pages | : 488 |
| Release | : 2008-12-22 |
| Genre | : Business & Economics |
| ISBN | : 1420081926 |
The First Collection That Covers This Field at the Dynamic Strategic and One-Period Tactical Levels. Addressing the imbalance between research and practice, Quantitative Fund Management presents leading-edge theory and methods, along with their application in practical problems encountered in the fund management industry. A Current Snapshot of State-of-the-Art Applications of Dynamic Stochastic Optimization Techniques to Long-Term Financial Planning - The first part of the book initially looks at how the quantitative techniques of the equity industry are shifting from basic Markowitz mean-variance portfolio optimization to risk management and trading applications. This section also explores novel aspects of lifetime individual consumption investment problems, fixed-mix portfolio rebalancing allocation strategies, debt management for funding mortgages and national debt, and guaranteed return fund construction. Up-to-Date Overview of Tactical Financial Planning and Risk Management - The second section covers nontrivial computational approaches to tactical fund management. This part focuses on portfolio construction and risk management at the individual security or fund manager level over the period up to the next portfolio rebalance. It discusses non-Gaussian returns, new risk-return tradeoffs, and the robustness of benchmarks and portfolio decisions. The Future Use of Quantitative Techniques in Fund Management - With contributions from well-known academics and practitioners, this volume will undoubtedly foster the recognition and wider acceptance of stochastic optimization techniques in financial practice.
