Practical Methods of Financial Engineering and Risk Management [electronic resource] : Tools for Modern Financial Professionals /
Chatterjee, Rupak.author.
Risk control, capital allocation, and realistic derivative pricing and hedging are critical concerns for major financial institutions and individual traders alike. Events from the collapse of Lehman Brothers to the Greek sovereign debt crisis demonstrate the urgent and abiding need for statistical tools adequate to measure and anticipate the amplitude of potential swings in the financial markets—from ordinary stock price and interest rate moves, to defaults, to those increasingly frequent "rare events" fashionably called black swan events. Yet many on Wall Street continue to rely on standard models based on artificially simplified assumptions that can lead to systematic (and sometimes catastrophic) underestimation of real risks. In Practical Methods of Financial Engineering and Risk Management, Dr. Rupak Chatterjee— former director of the multi-asset quantitative research group at Citi—introduces finance professionals and advanced students to the latest concepts, tools, valuation techniques, and analytic measures being deployed by the more discerning and responsive Wall Street practitioners, on all operational scales from day trading to institutional strategy, to model and analyze more faithfully the real behavior and risk exposure of financial markets in the cold light of the post-2008 realities. Until one masters this modern skill set, one cannot allocate risk capital properly, price and hedge derivative securities realistically, or risk-manage positions from the multiple perspectives of market risk, credit risk, counterparty risk, and systemic risk. The book assumes a working knowledge of calculus, statistics, and Excel, but it teaches techniques from statistical analysis, probability, and stochastic processes sufficient to enable the reader to calibrate probability distributions and create the simulations that are used on Wall Street to valuate various financial instruments correctly, model the risk dimensions of trading strategies, and perform the numerically intensive analysis of risk measures required by various regulatory agencies.
Description based upon print version of record.
""Contents at a Glance""; ""Contents""; ""Series Editorsâ€? Foreword ""; ""About the Author""; ""About the Technical Reviewer""; ""Acknowledgments""; ""Introduction""; ""Chapter 1: Financial Instruments""; ""Bloomberg Market Data Screens""; ""Cash Instruments""; ""Fed Funds""; ""Eurodollar Deposits""; ""US Treasury Bills, Notes, and Bonds""; ""Repo and Reverse Repo""; ""Equity Indices""; ""Dow Jones""; ""S&P 500""; ""NASDAQ Composite Index""; ""Commercial Paper""; ""LIBOR""; ""Spot Forex""; ""Key Rates""; ""Prime Rate""; ""Federal Funds Target Rate""; ""Discount Rate""; ""Gold""
""Futures and Swaps""""Crude Oil""; ""Fed Funds Futures""; ""90-Day Eurodollar Futures""; ""10-Year Treasury Note Futures""; ""Swaps""; ""Swap Valuation""; ""Swap Spreads""; ""Swap Futures""; ""Derivatives and Structured Products""; ""Dynamic Hedging and Replication""; ""Implied Volatility""; ""Caps and Floors""; ""Market Implied Volatility Quotes for Caps and Floors""; ""ATM Strike strike""; ""Swaptions""; ""Mortgage-Backed Securities""; ""Bloomberg Price Quotes: 30Y MBS""; ""Appendix: Daycount Conventions""; ""Problems""; ""Further Reading""; ""Chapter 2: Building a Yield Curve""
""Overview of Yield Curve Construction""""Cash LIBOR Rates""; ""90D Eurodollar Futures""; ""Swaps""; ""Generic Discount Factors""; ""Problems""; ""Problem 2.1: Build a Simple Yield Curve""; ""Further Reading""; ""Chapter 3: Statistical Analysis of Financial Data""; ""Tools in Probability Theory""; ""Moments of a Distribution""; ""Creating Random Variables and Distributions""; ""The Inverse Transform Method""; ""Creating a Density Function: Histograms and Frequencies""; ""Excel Histogram-Creating Method: Static Data""; ""Excel Histogram-Creating Method: Dynamic Data""
""Normalization of a Histogram""""Mixture of Gaussians: Creating a Distribution with High Kurtosis""; ""Random Variable Approach""; ""Density Approach""; ""Skew Normal Distribution: Creating a Distribution with Skewness""; ""Calibrating Distributions through Moment Matching""; ""Calibrating a Mixed Gaussian Distribution to Equity Returns""; ""Fitting by Hand""; ""Chi-Squared Fitting""; ""Calibrating a Generalized Studentâ€?s- t Distribution to Equity Returns""; ""Calibrating a Beta Distribution to Recovery Rates of Defaulted Bonds""; ""Basic Risk Measures""
""Calculating VaR and CVaR from Financial Return Data""""The Term Structure of Statistics""; ""The Term Structure of the Mean""; ""The Term Structure of Skew""; ""The Term Structure of Kurtosis""; ""The Term Structure of Volatility""; ""The Term Structure of â€œUpâ€? Volatility""; ""The Term Structure of â€œDownâ€? Volatility""; ""Autocorrelation""; ""Dynamic Portfolio Allocation""; ""Modern Portfolio Theory""; ""Key Problems with Modern Portfolio Theory""; ""Generic Rules to Dynamic Portfolio Allocation with Volatility Targets""; ""Appendix. Joint Distributions and Correlation""
""Joint Distribution Function""
Includes bibliographical references at the end of each chapters and index.
Risk control, capital allocation, and realistic derivative pricing and hedging are critical concerns for major financial institutions and individual traders alike. Events from the collapse of Lehman Brothers to the Greek sovereign debt crisis demonstrate the urgent and abiding need for statistical tools adequate to measure and anticipate the amplitude of potential swings in the financial markets—from ordinary stock price and interest rate moves, to defaults, to those increasingly frequent "rare events" fashionably called black swan events. Yet many on Wall Street continue to rely on standard models based on artificially simplified assumptions that can lead to systematic (and sometimes catastrophic) underestimation of real risks. In Practical Methods of Financial Engineering and Risk Management, Dr. Rupak Chatterjee— former director of the multi-asset quantitative research group at Citi—introduces finance professionals and advanced students to the latest concepts, tools, valuation techniques, and analytic measures being deployed by the more discerning and responsive Wall Street practitioners, on all operational scales from day trading to institutional strategy, to model and analyze more faithfully the real behavior and risk exposure of financial markets in the cold light of the post-2008 realities. Until one masters this modern skill set, one cannot allocate risk capital properly, price and hedge derivative securities realistically, or risk-manage positions from the multiple perspectives of market risk, credit risk, counterparty risk, and systemic risk. The book assumes a working knowledge of calculus, statistics, and Excel, but it teaches techniques from statistical analysis, probability, and stochastic processes sufficient to enable the reader to calibrate probability distributions and create the simulations that are used on Wall Street to valuate various financial instruments correctly, model the risk dimensions of trading strategies, and perform the numerically intensive analysis of risk measures required by various regulatory agencies.
Business.
Management science.
Business and Management, general.