Portfolio Insurance

Portfolio insurance has become a craze among institutional investors: over the past ten years, the value of assets managed under this strategy has grown from zero to more than -50 billion. This guide offers complete coverage and practical advice on every aspect of the subject. It clearly defines the characteristics of portfolio insurance, providing background on its history and the theory of hedging, going on to describe how to implement a hedging strategy, how to fit portfolio insurance into long-term financial planning, using index and financial futures and options in hedging, and techniques for measuring performance. Also included is a discussion of how portfolio insurance operates in the international arena.

Scientific Essay from the year 2021 in the subject Business economics - Investment and Finance, , language: English, abstract: Investments in money and capital markets involve different loss potentials that market participants should be able to manage. Below follows an overview and comparison of selected strategies to manage these risks. Portfolio insurance (PI) strategies were developed in the 1980s. They are used to hedge portfolios or individual investments against price losses. The volume of assets hedged with these strategies is significant. Different forms of individual strategies have developed over the years. Risk quantification and Value at Risk (VAR) strategies emerged around the same time. Risks of individual investments or portfolios were measured and different strategies were developed to take them into account in Value at Risk optimised portfolios (VaRoP). VaRoP is a strategy that calculates an optimal portfolio taking into account a given or permissible maximum VAR. Both strategies are intended to protect portfolios from losses in value. Their similarities and differences as well as their successes are presented and summarised in this paper. Their applicability in practice is also examined.

Dieses essential gibt einen Überblick zu aktuellen Erscheinungsformen der Portfolio Insurance sowie zur Anwendbarkeit der Constant-Proportion-Portfolio-Insurance mit vielfältigen Finanztiteln auf unterschiedlichen Geld- und Kapitalmärkten. Die empirische Untersuchung mit historischen Daten dazu umfasst einen Zeitraum von über sechs Jahren und ist in diesem Umfang ohne Vergleich. Die Darstellung und Vorgehensweise im Rahmen der Strategie erfolgt detailliert und wird mit Beispielen zur Replizierbarkeit unterstützt. Gleiches gilt für die empirischen Ergebnisse der unterschiedlichen Ergebnisse und der jeweiligen Finanztitel, die mit der Portfolio Insurance geschützt werden. Als Ergebnis wird deutlich, dass Transaktionskosten keinen wesentlichen Einfluss auf das Ergebnis der Strategien haben, negative Zinssätze jedoch den Erfolg maßgeblich negativ beeinflussen können.

Bachelor Thesis from the year 2016 in the subject Business economics - General, grade: 1.7, University of Frankfurt (Main), language: English, abstract: Risk aversion is a common trait among investors. While it is possible to reduce risk attributed to specific industries and regions by diversifying among different securities, market risk affects all securities on the market. Even a perfectly diversified portfolio is subject to systematic or market risk. It can be managed through diversification across asset classes, for example by shifting some of the funds invested into risk-free assets. For some investors, this yields unsatisfactory results as the expected return directly decreases linearly with an increase in the position in the risk-free asset. Portfolio insurance (PI) describes an alternative set of strategies that allows investors to reduce their exposure to market risk by guaranteeing the value of the portfolio to be above a certain value at the end of the investment period while allowing for participation in rising stock markets. Option-based portfolio insurance (OBPI) refers to a set of strategies in which either a conventional put option (protective put) or a replicated put option (synthetic put) is used to insure a portfolio against adverse price movements. In theory and assuming perfect market conditions, protective put (PP) and synthetic put (SP) yield identical payoffs and have the same cost. In practice, there are several important differences between the two strategies. On the one hand, PP seems to be an easy and uncomplicated strategy to implement, but the unavailability of listed options with desired maturities and strike prices are major issues. SP strategies, on the other hand, can suffer from obstacles like high transaction costs and jumps in stock prices.

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

A guide to the growing importance of extreme value risk theory, methods, and applications in the financial sector Presenting a uniquely accessible guide, Extreme Events in Finance: A Handbook of Extreme Value Theory and Its Applications features a combination of the theory, methods, and applications of extreme value theory (EVT) in finance and a practical understanding of market behavior including both ordinary and extraordinary conditions. Beginning with a fascinating history of EVTs and financial modeling, the handbook introduces the historical implications that resulted in the applications and then clearly examines the fundamental results of EVT in finance. After dealing with these theoretical results, the handbook focuses on the EVT methods critical for data analysis. Finally, the handbook features the practical applications and techniques and how these can be implemented in financial markets. Extreme Events in Finance: A Handbook of Extreme Value Theory and Its Applications includes: Over 40 contributions from international experts in the areas of finance, statistics, economics, business, insurance, and risk management Topical discussions on univariate and multivariate case extremes as well as regulation in financial markets Extensive references in order to provide readers with resources for further study Discussions on using R packages to compute the value of risk and related quantities The book is a valuable reference for practitioners in financial markets such as financial institutions, investment funds, and corporate treasuries, financial engineers, quantitative analysts, regulators, risk managers, large-scale consultancy groups, and insurers. Extreme Events in Finance: A Handbook of Extreme Value Theory and Its Applications is also a useful textbook for postgraduate courses on the methodology of EVTs in finance.

Investment Management for Insurers details all phases of the investment management process for insurers as well as fixed income instruments and derivatives and state-of-the-art analytical tools for valuing securities and measuring risk. Complete coverage includes: a general overview of issues, fixed income products, valuation, measuring and controlling interest rate risk, and equity portfolio management.