Description

Book Synopsis
This book provides a basic grounding in the use of probability to model random financial phenomena of uncertainty, and is targeted at an advanced undergraduate and graduate level. It should appeal to finance students looking for a firm theoretical guide to the deep end of derivatives and investments. Bankers and finance professionals in the fields of investments, derivatives, and risk management should also find the book useful in bringing probability and finance together.The book contains applications of both discrete time theory and continuous time mathematics, and is extensive in scope. Distribution theory, conditional probability, and conditional expectation are covered comprehensively, and applications to modeling state space securities under market equilibrium are made. Martingale is studied, leading to consideration of equivalent martingale measures, fundamental theorems of asset pricing, change of numeraire and discounting, risk-adjusted and forward-neutral measures, minimal and maximal prices of contingent claims, Markovian models, and the existence of martingale measures preserving the Markov property. Discrete stochastic calculus and multiperiod models leading to no-arbitrage pricing of contingent claims are also to be found in this book, as well as the theory of Markov Chains and appropriate applications in credit modeling. Measure-theoretic probability, moments, characteristic functions, inequalities, and central limit theorems are examined. The theory of risk aversion and utility, and ideas of risk premia are considered. Other application topics include optimal consumption and investment problems and interest rate theory.

Table of Contents
Measure-Theoretic Probability; Moments; Characteristic Functions; Inequalities; Central Limit Theorem; Distribution Theory; Conditional Probability; Conditional Expectation; State Space Securities; Market Equilibrium; Martingales; Equivalent Martingale Measures; Fundamental Theorems of Asset Pricing; Change of Numeraire; Risk-Adjusted and Forward-Neutral Measures; Minimal and Maximal Prices of Contingent Claims; Markovian Models; Stochastic Calculus; No-Arbitrage Pricing of Contingent Claims; Utility Theory; Theory of Risk Aversion; Risk Premia; Theory of Markov Chains; Credit Modeling; Optimal Consumption and Investment; Multi-Period Models; Interest Rate Theory.

Probability And Finance Theory

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A Hardback by Kian Guan Lim

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    View other formats and editions of Probability And Finance Theory by Kian Guan Lim

    Publisher: World Scientific Publishing Co Pte Ltd
    Publication Date: 26/05/2011
    ISBN13: 9789814307932, 978-9814307932
    ISBN10: 9814307939

    Description

    Book Synopsis
    This book provides a basic grounding in the use of probability to model random financial phenomena of uncertainty, and is targeted at an advanced undergraduate and graduate level. It should appeal to finance students looking for a firm theoretical guide to the deep end of derivatives and investments. Bankers and finance professionals in the fields of investments, derivatives, and risk management should also find the book useful in bringing probability and finance together.The book contains applications of both discrete time theory and continuous time mathematics, and is extensive in scope. Distribution theory, conditional probability, and conditional expectation are covered comprehensively, and applications to modeling state space securities under market equilibrium are made. Martingale is studied, leading to consideration of equivalent martingale measures, fundamental theorems of asset pricing, change of numeraire and discounting, risk-adjusted and forward-neutral measures, minimal and maximal prices of contingent claims, Markovian models, and the existence of martingale measures preserving the Markov property. Discrete stochastic calculus and multiperiod models leading to no-arbitrage pricing of contingent claims are also to be found in this book, as well as the theory of Markov Chains and appropriate applications in credit modeling. Measure-theoretic probability, moments, characteristic functions, inequalities, and central limit theorems are examined. The theory of risk aversion and utility, and ideas of risk premia are considered. Other application topics include optimal consumption and investment problems and interest rate theory.

    Table of Contents
    Measure-Theoretic Probability; Moments; Characteristic Functions; Inequalities; Central Limit Theorem; Distribution Theory; Conditional Probability; Conditional Expectation; State Space Securities; Market Equilibrium; Martingales; Equivalent Martingale Measures; Fundamental Theorems of Asset Pricing; Change of Numeraire; Risk-Adjusted and Forward-Neutral Measures; Minimal and Maximal Prices of Contingent Claims; Markovian Models; Stochastic Calculus; No-Arbitrage Pricing of Contingent Claims; Utility Theory; Theory of Risk Aversion; Risk Premia; Theory of Markov Chains; Credit Modeling; Optimal Consumption and Investment; Multi-Period Models; Interest Rate Theory.

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