Quantitative Methods for Portfolio Analysis

Quantitative Methods for Portfolio Analysis
Author: T. Kariya
Publisher: Springer Science & Business Media
Total Pages: 321
Release: 2012-12-06
Genre: Business & Economics
ISBN: 9401117217

Quantitative Methods for Portfolio Analysis provides practical models and methods for the quantitative analysis of financial asset prices, construction of various portfolios, and computer-assisted trading systems. In particular, this book is required reading for: (1) `Quants' (quantitatively-inclined analysts) in financial industries; (2) financial engineers in investment banks, securities companies, derivative-trading companies, software houses, etc., who are developing portfolio trading systems; (3) graduate students and specialists in the areas of finance, business, economics, statistics, financial engineering; and (4) investors who are interested in Japanese financial markets. Throughout the book the emphasis is placed on the originality and usefulness of models and methods for the construction of portfolios and investment decision making, and examples are provided to demonstrate, with practical analysis, models for Japanese financial markets.

Quantitative Equity Portfolio Management

Quantitative Equity Portfolio Management
Author: Ludwig B Chincarini
Publisher: McGraw Hill Professional
Total Pages: 658
Release: 2010-08-18
Genre: Business & Economics
ISBN: 9780071492386

Quantitative Equity Portfolio Management brings the orderly structure of fundamental asset management to the often-chaotic world of active equity management. Straightforward and accessible, it provides you with nuts-and-bolts details for selecting and aggregating factors, building a risk model, and much more.

Quantitative Investment Analysis

Quantitative Investment Analysis
Author: Richard A. DeFusco
Publisher: John Wiley & Sons
Total Pages: 635
Release: 2015-10-15
Genre: Business & Economics
ISBN: 1119104602

Your complete guide to quantitative analysis in the investment industry Quantitative Investment Analysis, Third Edition is a newly revised and updated text that presents you with a blend of theory and practice materials to guide you through the use of statistics within the context of finance and investment. With equal focus on theoretical concepts and their practical applications, this approachable resource offers features, such as learning outcome statements, that are targeted at helping you understand, retain, and apply the information you have learned. Throughout the text's chapters, you explore a wide range of topics, such as the time value of money, discounted cash flow applications, common probability distributions, sampling and estimation, hypothesis testing, and correlation and regression. Applying quantitative analysis to the investment process is an important task for investment pros and students. A reference that provides even subject matter treatment, consistent mathematical notation, and continuity in topic coverage will make the learning process easier—and will bolster your success. Explore the materials you need to apply quantitative analysis to finance and investment data—even if you have no previous knowledge of this subject area Access updated content that offers insight into the latest topics relevant to the field Consider a wide range of subject areas within the text, including chapters on multiple regression, issues in regression analysis, time-series analysis, and portfolio concepts Leverage supplemental materials, including the companion Workbook and Instructor's Manual, sold separately Quantitative Investment Analysis, Third Edition is a fundamental resource that covers the wide range of quantitative methods you need to know in order to apply quantitative analysis to the investment process.

Quantitative Methods for Investment Analysis

Quantitative Methods for Investment Analysis
Author: Richard Armand DeFusco
Publisher: Ingram
Total Pages: 776
Release: 2004
Genre: Business & Economics
ISBN:

Designed for use in the CFA program or by investment professionals, this textbook provides a guide to applying quantitative analysis to the investment process. From the perspective of an investment generalist, it covers the knowledge, skills, and abilities needed to utilize quantitative methods. Chapters address the time value of money, discounted cash flow applications, market returns, statistical concepts, probability concepts, probability distributions, sampling and estimation, hypothesis testing, correlation and regression, time series analysis, and portfolio concepts. The authors are CFAs affiliated with universities or private companies. c. Book News Inc.

Quantitative Portfolio Management

Quantitative Portfolio Management
Author: Pierre Brugière
Publisher: Springer Nature
Total Pages: 212
Release: 2020-03-28
Genre: Mathematics
ISBN: 3030377407

This self-contained book presents the main techniques of quantitative portfolio management and associated statistical methods in a very didactic and structured way, in a minimum number of pages. The concepts of investment portfolios, self-financing portfolios and absence of arbitrage opportunities are extensively used and enable the translation of all the mathematical concepts in an easily interpretable way. All the results, tested with Python programs, are demonstrated rigorously, often using geometric approaches for optimization problems and intrinsic approaches for statistical methods, leading to unusually short and elegant proofs. The statistical methods concern both parametric and non-parametric estimators and, to estimate the factors of a model, principal component analysis is explained. The presented Python code and web scraping techniques also make it possible to test the presented concepts on market data. This book will be useful for teaching Masters students and for professionals in asset management, and will be of interest to academics who want to explore a field in which they are not specialists. The ideal pre-requisites consist of undergraduate probability and statistics and a familiarity with linear algebra and matrix manipulation. Those who want to run the code will have to install Python on their pc, or alternatively can use Google Colab on the cloud. Professionals will need to have a quantitative background, being either portfolio managers or risk managers, or potentially quants wanting to double check their understanding of the subject.

Dynamic Portfolio Strategies: quantitative methods and empirical rules for incomplete information

Dynamic Portfolio Strategies: quantitative methods and empirical rules for incomplete information
Author: Nikolai Dokuchaev
Publisher: Springer Science & Business Media
Total Pages: 232
Release: 2002-01-31
Genre: Business & Economics
ISBN: 9780792376484

An investigation of optimal investment problems for stochastic financial market models, this book is addressed to academics and students who are interested in the mathematics of finance, stochastic processes and optimal control. It should also be useful to practitioners in risk management and quantitative analysis who are interested in new strategies and methods of stochastic analysis.

Quantitative Equity Portfolio Management

Quantitative Equity Portfolio Management
Author: Edward E. Qian
Publisher: CRC Press
Total Pages: 462
Release: 2007-05-11
Genre: Business & Economics
ISBN: 1420010794

Quantitative equity portfolio management combines theories and advanced techniques from several disciplines, including financial economics, accounting, mathematics, and operational research. While many texts are devoted to these disciplines, few deal with quantitative equity investing in a systematic and mathematical framework that is suitable for

Portfolio Analysis

Portfolio Analysis
Author: Xiaoxia Huang
Publisher: Springer Science & Business Media
Total Pages: 188
Release: 2010-02-18
Genre: Computers
ISBN: 3642112137

The most salient feature of security returns is uncertainty. The purpose of the book is to provide systematically a quantitative method for analyzing return and risk of a portfolio investment in di?erent kinds of uncertainty and present the ways for striking a balance between investment return and risk such that an optimal portfolio can be obtained. In classical portfolio theory, security returns were assumed to be random variables, and probability theory was the main mathematical tool for h- dling uncertainty in the past. However,the world is complex and uncertainty is varied. Randomnessis nottheonly typeofuncertaintyinreality,especially when human factors are included. Security market, one of the most complex marketsintheworld,containsalmostallkindsofuncertainty. Thesecurity- turns are sensitive to various factors including economic, social, political and very importantly, people’s psychological factors. Therefore, other than strict probability method, scholars have proposed some other approaches including imprecise probability, possibility, and interval set methods, etc. , to deal with uncertaintyinportfolioselectionsince1990’s. Inthisbook,wewantto addto thetools existingin sciencesomenewandunorthodoxapproachesforanal- ing uncertainty of portfolio returns. When security returns are fuzzy, we use credibility which has self-duality property as the basic measure and employ credibilitytheorytohelpmakeselectiondecisionsuchthatthedecisionresult will be consistent with the laws of contradiction and excluded middle. Being awarethat one tool is not enough for solving complex practical problems, we further employ uncertain measure and uncertainty theory to help select an optimal portfolio when security returns behave neither randomly nor fuzzily. One core of portfolio selection is to ?nd a quantitative risk de?nition of a portfolio investment.