Advanced Stochastic Portfolio Theory In Mathematical Finance
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Advanced Stochastic Portfolio Theory in Mathematical Finance
His lecture notes summarizes standard machinery of an advanced course on Stochastic Portfolio Theory, presents techniques for analysis of portfolio dynamics and equity market structure. This notes is based on material developed in a series of papers published in recent years by Prof. Ioannis Karatzas and his lectures regularly given at Columbia University in the city of New York.It gives introduction to a number of questions of market structure and arbitrage, used to construct portfolios controlled behaviour. The Stochastic Portfolio theory has been applied to analysis and optimization of portfolio performance and denotes a benchmark portfolio performance and successful investment strategies.
Mathematical Finance with Applications
Mathematical finance plays a vital role in many fields within finance and provides the theories and tools that have been widely used in all areas of finance. Knowledge of mathematics, probability, and statistics is essential to develop finance theories and test their validity through the analysis of empirical, real-world data. For example, mathematics, probability, and statistics could help to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities.
A Probability Metrics Approach to Financial Risk Measures
Author: Svetlozar T. Rachev
language: en
Publisher: John Wiley & Sons
Release Date: 2011-03-10
A Probability Metrics Approach to Financial Risk Measures relates the field of probability metrics and risk measures to one another and applies them to finance for the first time. Helps to answer the question: which risk measure is best for a given problem? Finds new relations between existing classes of risk measures Describes applications in finance and extends them where possible Presents the theory of probability metrics in a more accessible form which would be appropriate for non-specialists in the field Applications include optimal portfolio choice, risk theory, and numerical methods in finance Topics requiring more mathematical rigor and detail are included in technical appendices to chapters