Portfolio Optimization With Different Information Flow

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Portfolio Optimization With Different Information Flow

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Author : Caroline Hillairet
language : en
Publisher: Elsevier
Release Date : 2017-02-10

Portfolio Optimization With Different Information Flow written by Caroline Hillairet and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-10 with Business & Economics categories.

Portfolio Optimization with Different Information Flow recalls the stochastic tools and results concerning the stochastic optimization theory and the enlargement filtration theory.The authors apply the theory of the enlargement of filtrations and solve the optimization problem. Two main types of enlargement of filtration are discussed: initial and progressive, using tools from various fields, such as from stochastic calculus and convex analysis, optimal stochastic control and backward stochastic differential equations. This theoretical and numerical analysis is applied in different market settings to provide a good basis for the understanding of portfolio optimization with different information flow. - Presents recent progress of stochastic portfolio optimization with exotic filtrations - Shows you how to apply the tools of the enlargement of filtrations to resolve the optimization problem - Uses tools from various fields from enlargement of filtration theory, stochastic calculus, convex analysis, optimal stochastic control, and backward stochastic differential equations

Mathematical Foundations For Deep Learning

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Author : Mehdi Ghayoumi
language : en
Publisher: CRC Press
Release Date : 2025-08-05

Mathematical Foundations For Deep Learning written by Mehdi Ghayoumi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-05 with Computers categories.

Mathematical Foundations for Deep Learning bridges the gap between theoretical mathematics and practical applications in artificial intelligence (AI). This guide delves into the fundamental mathematical concepts that power modern deep learning, equipping readers with the tools and knowledge needed to excel in the rapidly evolving field of artificial intelligence. Designed for learners at all levels, from beginners to experts, the book makes mathematical ideas accessible through clear explanations, real-world examples, and targeted exercises. Readers will master core concepts in linear algebra, calculus, and optimization techniques; understand the mechanics of deep learning models; and apply theory to practice using frameworks like TensorFlow and PyTorch. By integrating theory with practical application, Mathematical Foundations for Deep Learning prepares you to navigate the complexities of AI confidently. Whether you’re aiming to develop practical skills for AI projects, advance to emerging trends in deep learning, or lay a strong foundation for future studies, this book serves as an indispensable resource for achieving proficiency in the field. Embark on an enlightening journey that fosters critical thinking and continuous learning. Invest in your future with a solid mathematical base, reinforced by case studies and applications that bring theory to life, and gain insights into the future of deep learning.

Data Driven Modeling And Optimization Applications To Social Computing

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Author : Chao Gao
language : en
Publisher: Frontiers Media SA
Release Date : 2022-09-14

Data Driven Modeling And Optimization Applications To Social Computing written by Chao Gao and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-14 with Science categories.

Enlargement Of Filtration With Finance In View

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Author : Anna Aksamit
language : en
Publisher: Springer
Release Date : 2017-11-18

Enlargement Of Filtration With Finance In View written by Anna Aksamit and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-18 with Mathematics categories.

This volume presents classical results of the theory of enlargement of filtration. The focus is on the behavior of martingales with respect to the enlarged filtration and related objects. The study is conducted in various contexts including immersion, progressive enlargement with a random time and initial enlargement with a random variable. The aim of this book is to collect the main mathematical results (with proofs) previously spread among numerous papers, great part of which is only available in French. Many examples and applications to finance, in particular to credit risk modelling and the study of asymmetric information, are provided to illustrate the theory. A detailed summary of further connections and applications is given in bibliographic notes which enables to deepen study of the topic. This book fills a gap in the literature and serves as a guide for graduate students and researchers interested in the role of information in financial mathematics and in econometric science. A basic knowledge of the general theory of stochastic processes is assumed as a prerequisite.

Mathematics Going Forward

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Author : Jean-Michel Morel
language : en
Publisher: Springer Nature
Release Date : 2023-05-13

Mathematics Going Forward written by Jean-Michel Morel and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-13 with Mathematics categories.

This volume is an original collection of articles by 44 leading mathematicians on the theme of the future of the discipline. The contributions range from musings on the future of specific fields, to analyses of the history of the discipline, to discussions of open problems and conjectures, including first solutions of unresolved problems. Interestingly, the topics do not cover all of mathematics, but only those deemed most worthy to reflect on for future generations. These topics encompass the most active parts of pure and applied mathematics, including algebraic geometry, probability, logic, optimization, finance, topology, partial differential equations, category theory, number theory, differential geometry, dynamical systems, artificial intelligence, theory of groups, mathematical physics and statistics.

Multi Period Trading Via Convex Optimization

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Author : Stephen P. Boyd
language : en
Publisher:
Release Date : 2017

Multi Period Trading Via Convex Optimization written by Stephen P. Boyd and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Electronic books categories.

We consider a basic model of multi-period trading, which can be used to evaluate the performance of a trading strategy. We describe a framework for single-period optimization, where the trades in each period are found by solving a convex optimization problem that trades off expected return, risk, transaction cost and holding cost such as the borrowing cost for shorting assets. We then describe a multi-period version of the trading method, where optimization is used to plan a sequence of trades, with only the first one executed, using estimates of future quantities that are unknown when the trades are chosen. The single period method traces back to Markowitz; the multi-period methods trace back to model predictive control. Our contribution is to describe the single-period and multi-period methods in one simple framework, giving a clear description of the development and the approximations made. In this paper, we do not address a critical component in a trading algorithm, the predictions or forecasts of future quantities. The methods we describe in this paper can be thought of as good ways to exploit predictions, no matter how they are made. We have also developed a companion open-source software library that implements many of the ideas and methods described in the paper.

Statistical Decision Problems

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Author : Michael Zabarankin
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-16

Statistical Decision Problems written by Michael Zabarankin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-16 with Business & Economics categories.

Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.

Evolutionary Multi Criterion Optimization

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Author : Carlos M. Fonseca
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-04-07

Evolutionary Multi Criterion Optimization written by Carlos M. Fonseca and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-04-07 with Business & Economics categories.

This book constitutes the refereed proceedings of the Second International Conference on Evolutionary Multi-Criterion Optimization, EMO 2003, held in Faro, Portugal, in April 2003. The 56 revised full papers presented were carefully reviewed and selected from a total of 100 submissions. The papers are organized in topical sections on objective handling and problem decomposition, algorithm improvements, online adaptation, problem construction, performance analysis and comparison, alternative methods, implementation, and applications.

Portfolio Theory And Management

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Author : H. Kent Baker
language : en
Publisher: Oxford University Press
Release Date : 2013-01-07

Portfolio Theory And Management written by H. Kent Baker and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-07 with Business & Economics categories.

Portfolio management is an ongoing process of constructing portfolios that balances an investor's objectives with the portfolio manager's expectations about the future. This dynamic process provides the payoff for investors. Portfolio management evaluates individual assets or investments by their contribution to the risk and return of an investor's portfolio rather than in isolation. This is called the portfolio perspective. Thus, by constructing a diversified portfolio, a portfolio manager can reduce risk for a given level of expected return, compared to investing in an individual asset or security. According to modern portfolio theory (MPT), investors who do not follow a portfolio perspective bear risk that is not rewarded with greater expected return. Portfolio diversification works best when financial markets are operating normally compared to periods of market turmoil such as the 2007-2008 financial crisis. During periods of turmoil, correlations tend to increase thus reducing the benefits of diversification. Portfolio management today emerges as a dynamic process, which continues to evolve at a rapid pace. The purpose of Portfolio Theory and Management is to take readers from the foundations of portfolio management with the contributions of financial pioneers up to the latest trends emerging within the context of special topics. The book includes discussions of portfolio theory and management both before and after the 2007-2008 financial crisis. This volume provides a critical reflection of what worked and what did not work viewed from the perspective of the recent financial crisis. Further, the book is not restricted to the U.S. market but takes a more global focus by highlighting cross-country differences and practices. This 30-chapter book consists of seven sections. These chapters are: (1) portfolio theory and asset pricing, (2) the investment policy statement and fiduciary duties, (3) asset allocation and portfolio construction, (4) risk management, (V) portfolio execution, monitoring, and rebalancing, (6) evaluating and reporting portfolio performance, and (7) special topics.

Handbook Of Statistical Analysis

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Author : Robert Nisbet
language : en
Publisher: Elsevier
Release Date : 2024-09-16

Handbook Of Statistical Analysis written by Robert Nisbet and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-16 with Mathematics categories.

Handbook of Statistical Analysis: AI and ML Applications, third edition, is a comprehensive introduction to all stages of data analysis, data preparation, model building, and model evaluation. This valuable resource is useful to students and professionals across a variety of fields and settings: business analysts, scientists, engineers, and researchers in academia and industry. General descriptions of algorithms together with case studies help readers understand technical and business problems, weigh the strengths and weaknesses of modern data analysis algorithms, and employ the right analytical methods for practical application. This resource is an ideal guide for users who want to address massive and complex datasets with many standard analytical approaches and be able to evaluate analyses and solutions objectively. It includes clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques; offers accessible tutorials; and discusses their application to real-world problems. - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data analytics to build successful predictive analytic solutions - Provides in-depth descriptions and directions for performing many data preparation operations necessary to generate data sets in the proper form and format for submission to modeling algorithms - Features clear, intuitive explanations of standard analytical tools and techniques and their practical applications - Provides a number of case studies to guide practitioners in the design of analytical applications to solve real-world problems in their data domain - Offers valuable tutorials on the book webpage with step-by-step instructions on how to use suggested tools to build models - Provides predictive insights into the rapidly expanding "Intelligence Age" as it takes over from the "Information Age," enabling readers to easily transition the book's content into the tools of the future