Institutions now dominate trading in equities around the world. Mutual funds are the most prominent, and doubly important as custodians of retirement savings. Despite this, there is no comprehensive description of fund manager behaviour, much less a matching theory. This is troubling because one of the most economically significant puzzles in finance is why experienced, well-resourced fund managers cannot outperform the market. Applied Investment Theory: How Equity Markets Behave, and Why brings together academic research, empirical evidence and real market experience to provide new insights into equity markets and their behaviours. The book draws upon the author’s rich industry experience and academic research, plus over 40 interviews with fund managers on three continents and across different markets. The result is an innovative model that explains the puzzle of poor performance by mutual funds in terms of structural features of markets, the managed investment industry, and the conduct of fund managers. This book provides a fully integrated depiction of what markets and investors do, and why – insights that will resonate with the needs of investors, wealth managers and industry regulators. It is fully documented, but free of jargon and arcane math, and provides a grounded theory that is relevant to anyone who wants to pierce the opacity of mutual fund operations. Applied Investment Theory sets out a new paradigm in investment that is at the forefront of what should be an industrial-scale development of new finance theory following two decades of almost back-to-back financial crises.

We cover two main parts in this textbook: how to model price movement and trading process. Prices are studied under fundamental analysis (Chapter 1), technical analysis (Chapter 2), time series analysis (Chapter 3) and factor pricing model (Chapter 4). For application, we consider event study and difference-and-difference estimation to examine various maker anomalies (Chapter 5). For trading process, we first study how to characterize the outcome (Chapter 6). Then we study Roll model that shows how trading cost affects price movement (Chapter 7). Using inventory model, we show that the imbalance of buy and sell orders as a source of bid-ask spread (Chapter 8). By sequential trade model, we demonstrate how information asymmetry leads to bid ask spread and how trade impacts the price moving process as the market learns the underlying state of the world (Chapter 9). Then, we study how strategic behaviour of informed traders changes the trading outcomes in a strategic trade model (Chapter 11). Finally, we examine how behavioural model can be used to explain short-run momentum and long-run reversal of price (Chapter 12).

This volume provides the definitive treatment of fortune's formula or the Kelly capital growth criterion as it is often called. The strategy is to maximize long run wealth of the investor by maximizing the period by period expected utility of wealth with a logarithmic utility function. Mathematical theorems show that only the log utility function maximizes asymptotic long run wealth and minimizes the expected time to arbitrary large goals. In general, the strategy is risky in the short term but as the number of bets increase, the Kelly bettor's wealth tends to be much larger than those with essentially different strategies. So most of the time, the Kelly bettor will have much more wealth than these other bettors but the Kelly strategy can lead to considerable losses a small percent of the time. There are ways to reduce this risk at the cost of lower expected final wealth using fractional Kelly strategies that blend the Kelly suggested wager with cash. The various classic reprinted papers and the new ones written specifically for this volume cover various aspects of the theory and practice of dynamic investing. Good and bad properties are discussed, as are fixed-mix and volatility induced growth strategies. The relationships with utility theory and the use of these ideas by great investors are featured.Contents: "The Early Ideas and Contributions: "Introduction to the Early Ideas and ContributionsExposition of a New Theory on the Measurement of Risk (translated by Louise Sommer) "(D Bernoulli)"A New Interpretation of Information Rate "(J R Kelly, Jr)"Criteria for Choice among Risky Ventures "(H A Latan‚)"Optimal Gambling Systems for Favorable Games "(L Breiman)"Optimal Gambling Systems for Favorable Games "(E O Thorp)"Portfolio Choice and the Kelly Criterion "(E O Thorp)"Optimal Investment and Consumption Strategies under Risk for a Class of Utility Functions "(N H Hakansson)"On Optimal Myopic Portfolio Policies, with and without Serial Correlation of Yields "(N H Hakansson)"Evidence on the ?Growth-Optimum-Model? "(R Roll)""Classic Papers and Theories: "Introduction to the Classic Papers and TheoriesCompetitive Optimality of Logarithmic Investment "(R M Bell and T M Cover)"A Bound on the Financial Value of Information "(A R Barron and T M Cover)"Asymptotic Optimality and Asymptotic Equipartition Properties of Log-Optimum Investment "(P H Algoet and T M Cover)"Universal Portfolios "(T M Cover)"The Cost of Achieving the Best Portfolio in Hindsight "(E Ordentlich and T M Cover)"Optimal Strategies for Repeated Games "(M Finkelstein and R Whitley)"The Effect of Errors in Means, Variances and Co-Variances on Optimal Portfolio Choice "(V K Chopra and W T Ziemba)"Time to Wealth Goals in Capital Accumulation "(L C MacLean, W T Ziemba, and Y Li)"Survival and Evolutionary Stability of Rule the Kelly "(I V Evstigneev, T Hens, and K R Schenk-Hopp‚)"Application of the Kelly Criterion to Ornstein-Uhlenbeck Processes "(Y Lv and B K Meister)""The Relationship of Kelly Optimization to Asset Allocation: "Introduction to the Relationship of Kelly Optimization to Asset AllocationSurvival and Growth with a Liability: Optimal Portfolio Strategies in Continuous Time "(S Browne)"Growth versus Security in Dynamic Investment Analysis "(L C MacLean, W T Ziemba, and G Blazenko)"Capital Growth with Security "(L C MacLean, R Sanegre, Y Zhao, and W T Ziemba)"

A unique perspective on applied investment theory and risk management from the Senior Risk Officer of a major pension fund Investment Theory and Risk Management is a practical guide to today's investment environment. The book's sophisticated quantitative methods are examined by an author who uses these methods at the Virginia Retirement System and teaches them at the Virginia Commonwealth University. In addition to showing how investment performance can be evaluated, using Jensen's Alpha, Sharpe's Ratio, and DDM, he delves into four types of optimal portfolios (one that is fully invested, one with targeted returns, another with no short sales, and one with capped investment allocations). In addition, the book provides valuable insights on risk, and topics such as anomalies, factor models, and active portfolio management. Other chapters focus on private equity, structured credit, optimal rebalancing, data problems, and Monte Carlo simulation. Contains investment theory and risk management spreadsheet models based on the author's own real-world experience with stock, bonds, and alternative assets Offers a down-to-earth guide that can be used on a daily basis for making common financial decisions with a new level of quantitative sophistication and rigor Written by the Director of Research and Senior Risk Officer for the Virginia Retirement System and an Associate Professor at Virginia Commonwealth University's School of Business Investment Theory and Risk Management empowers both the technical and non-technical reader with the essential knowledge necessary to understand and manage risks in any corporate or economic environment.

This book combines the study of rhetoric, history, philosophy, philosophy of statistics and the culture of investing to discuss the foundations of stochastical predictability in investment theory. Besides discussing the problem of stochastical prediction, the book also covers alternative investment theories. Ideas from uncertainty economics, expressed by the likes of Keynes, Knight, von Mises, Taleb and McCloskey are also discussed. This book will be of interest to researchers and academics in the field of investment theory, as well as investment practitioners.

This book is an introduction-level text that reviews, discusses, and integrates both theoretical and practical corporate analysis and planning. The field can be divided into five parts: (1) Information and Methodology for Financial Analysis; (2) Alternative Finance Theories and Cost of Capital; (3) Capital Budgeting and Leasing Decisions; (4) Corporate Policies and their Interrelationships; (5) Financial Planning and Forecasting.The theories used and discussed in this book can be grouped into the following classical theoretical areas of corporate finance: (1) Pre-M&M Theory, (2) M&M Theory, (3) CAPM, and (4) Option Pricing Theory (OPT). The interrelationships among these theories are carefully analyzed. Real world examples are used to enrich the learning experience; and alternative planning and forecasting models are used to show how the interdisciplinary approach can be used to make meaningful financial-management decisions.In this third edition, we have extensively updated and expanded the topics of financial analysis, planning and forecasting. New chapters were added, and some chapters combined to present a holistic view of the subject and much of the data revised and updated.

Nowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance. Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other. Draw upon mathematics to learn the foundations of financial theory and Python programming Learn about financial theory, financial data modeling, and the use of Python for computational finance Leverage simple economic models to better understand basic notions of finance and Python programming concepts Use both static and dynamic financial modeling to address fundamental problems in finance, such as pricing, decision-making, equilibrium, and asset allocation Learn the basics of Python packages useful for financial modeling, such as NumPy, pandas, Matplotlib, and SymPy

Risk control and derivative pricing have become of major concern to financial institutions, and there is a real need for adequate statistical tools to measure and anticipate the amplitude of the potential moves of the financial markets. Summarising theoretical developments in the field, this 2003 second edition has been substantially expanded. Additional chapters now cover stochastic processes, Monte-Carlo methods, Black-Scholes theory, the theory of the yield curve, and Minority Game. There are discussions on aspects of data analysis, financial products, non-linear correlations, and herding, feedback and agent based models. This book has become a classic reference for graduate students and researchers working in econophysics and mathematical finance, and for quantitative analysts working on risk management, derivative pricing and quantitative trading strategies.

The term Financial Derivative is a very broad term which has come to mean any financial transaction whose value depends on the underlying value of the asset concerned. Sophisticated statistical modelling of derivatives enables practitioners in the banking industry to reduce financial risk and ultimately increase profits made from these transactions. The book originally published in March 2000 to widespread acclaim. This revised edition has been updated with minor corrections and new references, and now includes a chapter of exercises and solutions, enabling use as a course text. Comprehensive introduction to the theory and practice of financial derivatives. Discusses and elaborates on the theory of interest rate derivatives, an area of increasing interest. Divided into two self-contained parts ? the first concentrating on the theory of stochastic calculus, and the second describes in detail the pricing of a number of different derivatives in practice. Written by well respected academics with experience in the banking industry. A valuable text for practitioners in research departments of all banking and finance sectors. Academic researchers and graduate students working in mathematical finance.

V.1 Capital theory and investment behavior -- V.2 Tax policy and the cost of capital.