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Deep Hedging Hedging Derivatives Under Generic Market Frictions Using Reinforcement Learning
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Book Synopsis Deep Hedging: Hedging Derivatives Under Generic Market Frictions Using Reinforcement Learning by : Hans Buehler
Download or read book Deep Hedging: Hedging Derivatives Under Generic Market Frictions Using Reinforcement Learning written by Hans Buehler and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep Hedging written by Hans Buehler and published by . This book was released on 2019 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, market impact, liquidity constraints or risk limits using modern deep reinforcement machine learning methods.We discuss how standard reinforcement learning methods can be applied to non-linear reward structures, i.e. in our case convex risk measures. As a general contribution to the use of deep learning for stochastic processes, we also show in section 4 that the set of constrained trading strategies used by our algorithm is large enough to ∈-approximate any optimal solution.Our algorithm can be implemented efficiently even in high-dimensional situations using modern machine learning tools. Its structure does not depend on specific market dynamics, and generalizes across hedging instruments including the use of liquid derivatives. Its computational performance is largely invariant in the size of the portfolio as it depends mainly on the number of hedging instruments available.We illustrate our approach by showing the effect on hedging under transaction costs in a synthetic market driven by the Heston model, where we outperform the standard “complete market” solution.This is the "stochastic analysis" version of the paper. A version in machine learning notation is available here "https://ssrn.com/abstract=3355706" https://ssrn.com/abstract=3355706.
Book Synopsis Risk-averse Deep Distributional Reinforcement Learning for Option Hedging Under Market Frictions by : 林鼎鈞
Download or read book Risk-averse Deep Distributional Reinforcement Learning for Option Hedging Under Market Frictions written by 林鼎鈞 and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pricing and Hedging Financial Derivatives with Reinforcement Learning Methods by : Alexandre Carbonneau
Download or read book Pricing and Hedging Financial Derivatives with Reinforcement Learning Methods written by Alexandre Carbonneau and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis studies the problem of pricing and hedging financial derivatives with reinforcement learning. Throughout all four papers, the underlying global hedging problems are solved using the deep hedging algorithm with the representation of global hedging policies as neural networks. The first paper, "Equal Risk Pricing of Derivatives with Deep Hedging'', shows how the deep hedging algorithm can be applied to solve the two underlying global hedging problems of the equal risk pricing framework for the valuation of European financial derivatives. The second paper, "Deep Hedging of Long-Term Financial Derivatives'', studies the problem of global hedging very long-term financial derivatives which are analogous, under some assumptions, to options embedded in guarantees of variable annuities. The third paper, "Deep Equal Risk Pricing of Financial Derivatives with Multiple Hedging Instruments'', studies derivative prices generated by the equal risk pricing framework for long-term options when shorter-term options are used as hedging instruments. The fourth paper, "Deep equal risk pricing of financial derivatives with non-translation invariant risk measures'', investigates the use of non-translation invariant risk measures within the equal risk pricing framework.
Book Synopsis Multi-agent Deep Reinforcement Learning and GAN-based Market Simulation for Derivatives Pricing and Dynamic Hedging by : Samson Qian
Download or read book Multi-agent Deep Reinforcement Learning and GAN-based Market Simulation for Derivatives Pricing and Dynamic Hedging written by Samson Qian and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in computing capabilities have enabled machine learning algorithms to learn directly from large amounts of data. Deep reinforcement learning is a particularly powerful method that uses agents to learn by interacting with an environment of data. Although many traders and investment managers rely on traditional statistical and stochastic methods to price assets and develop trading and hedging strategies, deep reinforcement learning has proven to be an effective method to learn optimal policies for pricing and hedging. Machine learning removes the need for various parametric assumptions about underlying market dynamics by learning directly from data. This research examines the use of machine learning methods to develop a data-driven method of derivatives pricing and dynamic hedging. Nevertheless, machine learning methods like reinforcement learning require an abundance of data to learn. We explore the implementation of a generative adversarial network-based approach to generate realistic market data from past historical data. This data is used to train the reinforcement learning framework and evaluate its robustness. The results demonstrate the efficacy of deep reinforcement learning methods to price derivatives and hedge positions in the proposed systematic GAN-based market simulation framework.
Book Synopsis Machine Learning and Data Sciences for Financial Markets by : Agostino Capponi
Download or read book Machine Learning and Data Sciences for Financial Markets written by Agostino Capponi and published by Cambridge University Press. This book was released on 2023-04-30 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leveraging the research efforts of more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence. The text is structured around three main areas: 'Interactions with investors and asset owners,' which covers robo-advisors and price formation; 'Risk intermediation,' which discusses derivative hedging, portfolio construction, and machine learning for dynamic optimization; and 'Connections with the real economy,' which explores nowcasting, alternative data, and ethics of algorithms. Accessible to a wide audience, this invaluable resource will allow practitioners to include machine learning driven techniques in their day-to-day quantitative practices, while students will build intuition and come to appreciate the technical tools and motivation for the theory.
Book Synopsis Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023) by : Jerome Yen
Download or read book Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023) written by Jerome Yen and published by Springer Nature. This book was released on 2023-07-25 with total page 1595 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book.With the rapid development of modern economy and Internet technology, the traditional financial industry has to develop Internet finance to provide better services and meet the needs of the times. It is against this background that the blockchain, relying on its special advantages (collective maintenance, reliable databases, and decentralization), provides the reliability to solve the credit risk of Internet finance, has an impact on institutions, trust mechanisms, risk control, etc. in the Internet finance industry, and has derived more new application scenarios, thus paving the way for the development of finance in the Internet era. Applying blockchain technology to the financial field can promote data information sharing, improve value transmission efficiency, and enhance database security. The financial market based on the decentralized system of blockchain technology can reduce the operating costs of financial institutions, improve economic efficiency, and solve problems such as information asymmetry. The new financial business model of "blockchain+finance" is conducive to improving the Internet credit reporting system, preventing and controlling Internet financial risks, and further realizing "financial disintermediation". At present, in China's financial field, blockchain technology has been applied and innovated in supply chain finance, cross-border payment, trade finance, asset securitization and other scenarios. To promote the exchange and development of blockchain, information technology and financial experts and scholars. The 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023) will be held in Hangzhou from February 17 to 19, 2023. This conference mainly focuses on the latest research on "blockchain, information technology and smart finance". This conference brings together experts, scholars, researchers and relevant practitioners in this field from all over the world to share research results, discuss hot issues, and provide participants with cutting-edge scientific and technological information, so that you can timely understand the development trends of the industry and master the latest technologies, broaden research horizons and promote academic progress.
Book Synopsis Hedging Derivatives by : Thorsten Rheinlander
Download or read book Hedging Derivatives written by Thorsten Rheinlander and published by World Scientific. This book was released on 2011 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Valuation and hedging of financial derivatives are intrinsically linked concepts. Choosing appropriate hedging techniques depends on both the type of derivative and assumptions placed on the underlying stochastic process. This volume provides a systematic treatment of hedging in incomplete markets. Mean-variance hedging under the risk-neutral measure is applied in the framework of exponential L(r)vy processes and for derivatives written on defaultable assets. It is discussed how to complete markets based upon stochastic volatility models via trading in both stocks and vanilla options. Exponential utility indifference pricing is explored via a duality with entropy minimization. Backward stochastic differential equations offer an alternative approach and are moreover applied to study markets with trading constraints including basis risk. A range of optimal martingale measures are discussed including the entropy, Esscher and minimal martingale measures. Quasi-symmetry properties of stochastic processes are deployed in the semi-static hedging of barrier options. This book is directed towards both graduate students and researchers in mathematical finance, and will also provide an orientation to applied mathematicians, financial economists and practitioners wishing to explore recent progress in this field."
Book Synopsis Artificial Intelligence in Finance by : Yves Hilpisch
Download or read book Artificial Intelligence in Finance written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2020-10-14 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about
Book Synopsis Advanced Portfolio Management by : Giuseppe A. Paleologo
Download or read book Advanced Portfolio Management written by Giuseppe A. Paleologo and published by John Wiley & Sons. This book was released on 2021-08-03 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: You have great investment ideas. If you turn them into highly profitable portfolios, this book is for you. Advanced Portfolio Management: A Quant’s Guide for Fundamental Investors is for fundamental equity analysts and portfolio managers, present, and future. Whatever stage you are at in your career, you have valuable investment ideas but always need knowledge to turn them into money. This book will introduce you to a framework for portfolio construction and risk management that is grounded in sound theory and tested by successful fundamental portfolio managers. The emphasis is on theory relevant to fundamental portfolio managers that works in practice, enabling you to convert ideas into a strategy portfolio that is both profitable and resilient. Intuition always comes first, and this book helps to lay out simple but effective "rules of thumb" that require little effort to implement and understand. At the same time, the book shows how to implement sophisticated techniques in order to meet the challenges a successful investor faces as his or her strategy grows in size and complexity. Advanced Portfolio Management also contains more advanced material and a quantitative appendix, which benefit quantitative researchers who are members of fundamental teams. You will learn how to: Separate stock-specific return drivers from the investment environment’s return drivers Understand current investment themes Size your cash positions based on Your investment ideas Understand your performance Measure and decompose risk Hedge the risk you don’t want Use diversification to your advantage Manage losses and control tail risk Set your leverage Author Giuseppe A. Paleologo has consulted, collaborated, taught, and drank strong wine with some of the best stock-pickers in the world; he has traded tens of billions of dollars hedging and optimizing their books and has helped them navigate through big drawdowns and even bigger recoveries. Whether or not you have access to risk models or advanced mathematical background, you will benefit from the techniques and the insights contained in the book—and won't find them covered anywhere else.
Book Synopsis Stochastic Finance by : Hans Föllmer
Download or read book Stochastic Finance written by Hans Föllmer and published by Walter de Gruyter GmbH & Co KG. This book was released on 2016-07-25 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to financial mathematics. It is intended for graduate students in mathematics and for researchers working in academia and industry. The focus on stochastic models in discrete time has two immediate benefits. First, the probabilistic machinery is simpler, and one can discuss right away some of the key problems in the theory of pricing and hedging of financial derivatives. Second, the paradigm of a complete financial market, where all derivatives admit a perfect hedge, becomes the exception rather than the rule. Thus, the need to confront the intrinsic risks arising from market incomleteness appears at a very early stage. The first part of the book contains a study of a simple one-period model, which also serves as a building block for later developments. Topics include the characterization of arbitrage-free markets, preferences on asset profiles, an introduction to equilibrium analysis, and monetary measures of financial risk. In the second part, the idea of dynamic hedging of contingent claims is developed in a multiperiod framework. Topics include martingale measures, pricing formulas for derivatives, American options, superhedging, and hedging strategies with minimal shortfall risk. This fourth, newly revised edition contains more than one hundred exercises. It also includes material on risk measures and the related issue of model uncertainty, in particular a chapter on dynamic risk measures and sections on robust utility maximization and on efficient hedging with convex risk measures. Contents: Part I: Mathematical finance in one period Arbitrage theory Preferences Optimality and equilibrium Monetary measures of risk Part II: Dynamic hedging Dynamic arbitrage theory American contingent claims Superhedging Efficient hedging Hedging under constraints Minimizing the hedging error Dynamic risk measures
Book Synopsis Derivatives in Financial Markets with Stochastic Volatility by : Jean-Pierre Fouque
Download or read book Derivatives in Financial Markets with Stochastic Volatility written by Jean-Pierre Fouque and published by Cambridge University Press. This book was released on 2000-07-03 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, first published in 2000, addresses pricing and hedging derivative securities in uncertain and changing market volatility.
Book Synopsis Frontiers in Quantitative Finance by : Rama Cont
Download or read book Frontiers in Quantitative Finance written by Rama Cont and published by John Wiley & Sons. This book was released on 2009-03-09 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Petit D'euner de la Finance–which author Rama Cont has been co-organizing in Paris since 1998–is a well-known quantitative finance seminar that has progressively become a platform for the exchange of ideas between the academic and practitioner communities in quantitative finance. Frontiers in Quantitative Finance is a selection of recent presentations in the Petit D'euner de la Finance. In this book, leading quants and academic researchers cover the most important emerging issues in quantitative finance and focus on portfolio credit risk and volatility modeling.
Book Synopsis How I Became a Quant by : Richard R. Lindsey
Download or read book How I Became a Quant written by Richard R. Lindsey and published by John Wiley & Sons. This book was released on 2011-01-11 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for How I Became a Quant "Led by two top-notch quants, Richard R. Lindsey and Barry Schachter, How I Became a Quant details the quirky world of quantitative analysis through stories told by some of today's most successful quants. For anyone who might have thought otherwise, there are engaging personalities behind all that number crunching!" --Ira Kawaller, Kawaller & Co. and the Kawaller Fund "A fun and fascinating read. This book tells the story of how academics, physicists, mathematicians, and other scientists became professional investors managing billions." --David A. Krell, President and CEO, International Securities Exchange "How I Became a Quant should be must reading for all students with a quantitative aptitude. It provides fascinating examples of the dynamic career opportunities potentially open to anyone with the skills and passion for quantitative analysis." --Roy D. Henriksson, Chief Investment Officer, Advanced Portfolio Management "Quants"--those who design and implement mathematical models for the pricing of derivatives, assessment of risk, or prediction of market movements--are the backbone of today's investment industry. As the greater volatility of current financial markets has driven investors to seek shelter from increasing uncertainty, the quant revolution has given people the opportunity to avoid unwanted financial risk by literally trading it away, or more specifically, paying someone else to take on the unwanted risk. How I Became a Quant reveals the faces behind the quant revolution, offering you?the?chance to learn firsthand what it's like to be a?quant today. In this fascinating collection of Wall Street war stories, more than two dozen quants detail their roots, roles, and contributions, explaining what they do and how they do it, as well as outlining the sometimes unexpected paths they have followed from the halls of academia to the front lines of an investment revolution.
Book Synopsis Modern Computational Finance by : Antoine Savine
Download or read book Modern Computational Finance written by Antoine Savine and published by John Wiley & Sons. This book was released on 2018-11-20 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Arguably the strongest addition to numerical finance of the past decade, Algorithmic Adjoint Differentiation (AAD) is the technology implemented in modern financial software to produce thousands of accurate risk sensitivities, within seconds, on light hardware. AAD recently became a centerpiece of modern financial systems and a key skill for all quantitative analysts, developers, risk professionals or anyone involved with derivatives. It is increasingly taught in Masters and PhD programs in finance. Danske Bank's wide scale implementation of AAD in its production and regulatory systems won the In-House System of the Year 2015 Risk award. The Modern Computational Finance books, written by three of the very people who designed Danske Bank's systems, offer a unique insight into the modern implementation of financial models. The volumes combine financial modelling, mathematics and programming to resolve real life financial problems and produce effective derivatives software. This volume is a complete, self-contained learning reference for AAD, and its application in finance. AAD is explained in deep detail throughout chapters that gently lead readers from the theoretical foundations to the most delicate areas of an efficient implementation, such as memory management, parallel implementation and acceleration with expression templates. The book comes with professional source code in C++, including an efficient, up to date implementation of AAD and a generic parallel simulation library. Modern C++, high performance parallel programming and interfacing C++ with Excel are also covered. The book builds the code step-by-step, while the code illustrates the concepts and notions developed in the book.
Book Synopsis Quantitative Methods for Economics and Finance by : J.E. Trinidad-Segovia
Download or read book Quantitative Methods for Economics and Finance written by J.E. Trinidad-Segovia and published by MDPI. This book was released on 2021-02-12 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice.
Book Synopsis The Handbook of Electronic Trading by : Joseph Rosen
Download or read book The Handbook of Electronic Trading written by Joseph Rosen and published by . This book was released on 2009-06-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive look at the challenges of keeping up with liquidity needs and technology advancements. It is also a sourcebook for understandable, practical solutions on trading and technology.