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Author : 林鼎鈞
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (143 download)
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:
Author : Hans Buehler
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (118 download)
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:
Author : Hans Buehler
Publisher :
ISBN 13 :
Total Pages : 32 pages
Book Rating : 4.:/5 (13 download)
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.
Author : Saeed Marzban
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)
Download or read book Deep Reinforcement Learning for Option Pricing and Hedging Under Dynamic Expectile Risk Measures written by Saeed Marzban and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Saeed Marzban
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (131 download)
Download or read book Deep Reinforcement Learning for Dynamic Expectile Risk Measures written by Saeed Marzban and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jens Carsten Jackwerth
Publisher : Research Foundation Publications
ISBN 13 : 9780943205663
Total Pages : 86 pages
Book Rating : 4.2/5 (56 download)
Download or read book Option-implied Risk-neutral Distributions and Risk Aversion written by Jens Carsten Jackwerth and published by Research Foundation Publications. This book was released on 2004-01-01 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Matthew F. Dixon
Publisher : Springer Nature
ISBN 13 : 3030410684
Total Pages : 565 pages
Book Rating : 4.0/5 (34 download)
Download or read book Machine Learning in Finance written by Matthew F. Dixon and published by Springer Nature. This book was released on 2020-07-01 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
Author : M. Ayhan Kose
Publisher : World Bank Publications
ISBN 13 : 1464815453
Total Pages : 403 pages
Book Rating : 4.4/5 (648 download)
Download or read book Global Waves of Debt written by M. Ayhan Kose and published by World Bank Publications. This book was released on 2021-03-03 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: The global economy has experienced four waves of rapid debt accumulation over the past 50 years. The first three debt waves ended with financial crises in many emerging market and developing economies. During the current wave, which started in 2010, the increase in debt in these economies has already been larger, faster, and broader-based than in the previous three waves. Current low interest rates mitigate some of the risks associated with high debt. However, emerging market and developing economies are also confronted by weak growth prospects, mounting vulnerabilities, and elevated global risks. A menu of policy options is available to reduce the likelihood that the current debt wave will end in crisis and, if crises do take place, will alleviate their impact.
Author : Laura Graesser
Publisher : Addison-Wesley Professional
ISBN 13 : 0135172489
Total Pages : 625 pages
Book Rating : 4.1/5 (351 download)
Download or read book Foundations of Deep Reinforcement Learning written by Laura Graesser and published by Addison-Wesley Professional. This book was released on 2019-11-20 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games—such as Go, Atari games, and DotA 2—to robotics. Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM Lab, and finishes with the practical details of getting deep RL to work. This guide is ideal for both computer science students and software engineers who are familiar with basic machine learning concepts and have a working understanding of Python. Understand each key aspect of a deep RL problem Explore policy- and value-based algorithms, including REINFORCE, SARSA, DQN, Double DQN, and Prioritized Experience Replay (PER) Delve into combined algorithms, including Actor-Critic and Proximal Policy Optimization (PPO) Understand how algorithms can be parallelized synchronously and asynchronously Run algorithms in SLM Lab and learn the practical implementation details for getting deep RL to work Explore algorithm benchmark results with tuned hyperparameters Understand how deep RL environments are designed Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Author : Hans Föllmer
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110463458
Total Pages : 608 pages
Book Rating : 4.1/5 (14 download)
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
Author : Dani Rodrik
Publisher : Oxford University Press
ISBN 13 : 0199603332
Total Pages : 369 pages
Book Rating : 4.1/5 (996 download)
Download or read book The Globalization Paradox written by Dani Rodrik and published by Oxford University Press. This book was released on 2011-03-24 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: For a century, economists have driven forward the cause of globalization in financial institutions, labour markets, and trade. Yet there have been consistent warning signs that a global economy and free trade might not always be advantageous. Where are the pressure points? What could be done about them?Dani Rodrik examines the back-story from its seventeenth-century origins through the milestones of the gold standard, the Bretton Woods Agreement, and the Washington Consensus, to the present day. Although economic globalization has enabled unprecedented levels of prosperity in advanced countries and has been a boon to hundreds of millions of poor workers in China and elsewhere in Asia, it is a concept that rests on shaky pillars, he contends. Its long-term sustainability is not a given.The heart of Rodrik>'s argument is a fundamental 'trilemma': that we cannot simultaneously pursue democracy, national self-determination, and economic globalization. Give too much power to governments, and you have protectionism. Give markets too much freedom, and you have an unstable world economy with little social and political support from those it is supposed to help. Rodrik argues for smart globalization, not maximum globalization.
Author : Álvaro Cartea
Publisher : Cambridge University Press
ISBN 13 : 1316453650
Total Pages : 360 pages
Book Rating : 4.3/5 (164 download)
Download or read book Algorithmic and High-Frequency Trading written by Álvaro Cartea and published by Cambridge University Press. This book was released on 2015-08-06 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.
Author : Ali N. Akansu
Publisher : John Wiley & Sons
ISBN 13 : 1118745639
Total Pages : 312 pages
Book Rating : 4.1/5 (187 download)
Download or read book Financial Signal Processing and Machine Learning written by Ali N. Akansu and published by John Wiley & Sons. This book was released on 2016-04-21 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.
Author : Thomas E. Copeland
Publisher :
ISBN 13 : 9781292021584
Total Pages : 924 pages
Book Rating : 4.0/5 (215 download)
Download or read book Financial Theory and Corporate Policy written by Thomas E. Copeland and published by . This book was released on 2013-07-17 with total page 924 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic textbook in the field, now completely revised and updated, provides a bridge between theory and practice. Appropriate for the second course in Finance for MBA students and the first course in Finance for doctoral students, the text prepares students for the complex world of modern financial scholarship and practice. It presents a unified treatment of finance combining theory, empirical evidence and applications.
Author : Elisa Luciano
Publisher : MDPI
ISBN 13 : 3039216244
Total Pages : 224 pages
Book Rating : 4.0/5 (392 download)
Download or read book Risk Analysis and Portfolio Modelling written by Elisa Luciano and published by MDPI. This book was released on 2019-10-16 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Risk Measurement is a challenging task, because both the types of risk and the techniques evolve very quickly. This book collects a number of novel contributions to the measurement of financial risk, which address either non-fully explored risks or risk takers, and does so in a wide variety of empirical contexts.
Author : Michael Kearns
Publisher : Oxford University Press
ISBN 13 : 0190948213
Total Pages : 288 pages
Book Rating : 4.1/5 (99 download)
Download or read book The Ethical Algorithm written by Michael Kearns and published by Oxford University Press. This book was released on 2019-10-04 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions reflect racial and gender bias. Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services, and navigation apps. Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while continuing to inspire wondrous advances in technology.
Author : Yuri Kabanov
Publisher : Springer Science & Business Media
ISBN 13 : 3540681213
Total Pages : 306 pages
Book Rating : 4.5/5 (46 download)
Download or read book Markets with Transaction Costs written by Yuri Kabanov and published by Springer Science & Business Media. This book was released on 2009-12-04 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is the first monograph on this highly important subject.
