http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
financial signal processing and electronic trading
This book bridges the fields of finance, mathematical finance and engineering, and is suitable for engineers and computer scientists who are looking to apply engineering principles to financial markets.
Front Cover; A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading; Copyright; Dedication; Contents; Preface; Chapter 1: Introduction; 1.1 Disclaimer; Chapter 2: Financial Markets and Instruments; 2.1 Structure of the Markets; 2.2 Financial Instruments; 2.2.1 Stocks; 2.2.2 Options; 2.2.3 Futures Contracts; 2.2.4 Exchange Traded Funds (ETFs); 2.2.5 Currency Pairs; 2.2.6 Fixed Income Securities; 2.3 Summary; Chapter 3: Fundamentals of Quantitative Finance; 3.1 Stock Price Models; 3.1.1 Geometric Brownian Motion Model
3.1.2 Models with Local and Stochastic Volatilities3.1.3 Discrete-Time Price Models and Return; 3.2 Asset Returns; 3.2.1 Expected Return, Volatility, and Cross-Correlation of Returns; 3.2.2 Effect of Sampling Frequency on Volatility; 3.2.3 Jumps in the Returns; 3.3 Modern Portfolio Theory; 3.3.1 Portfolio Return and Risk; 3.3.1.1 Two-Asset Portfolio; 3.3.1.2 Multi-asset Portfolio; 3.3.2 Portfolio Optimization; 3.4 Capital Asset Pricing Model; 3.4.1 Capital Market Line; 3.4.2 Market Portfolio; 3.4.3 Beta of an Asset; 3.4.4 Volatility in CAPM; 3.4.5 Expected Return in CAPM
3.4.6 Security Market Line3.5 Relative Value and Factor Models; 3.5.1 Two Assets; 3.5.2 Multiple Assets; 3.5.3 Factor Models; 3.5.4 Eigenportfolios; 3.6 Summary; Chapter 4: Trading Strategies; 4.1 Trading Terminology; 4.2 Long and Short Positions; 4.3 Cost of Trading; 4.4 Backtesting; 4.4.1 Profit and Loss of a Trading Strategy; 4.4.2 Performance Measures; 4.4.3 Backtesting a Trading Strategy; 4.4.4 Leverage; 4.5 Pairs Trading and Mean Reversion; 4.5.1 Model Based Pairs Trading; 4.5.2 Market Neutrality; 4.5.3 A Recipe for Pairs Trading; 4.6 Statistical Arbitrage
4.6.1 A Recipe for Statistical Arbitrage4.7 Trend Following; 4.7.1 Moving Averages; 4.7.2 Signal Generation Methods for Trend Following; 4.7.3 Moving Averages as Discrete-Time Filters; 4.7.4 A Recipe for Trend Following; 4.8 Trading in Multiple Frequencies; 4.9 Summary; Chapter 5: Risk Estimation and Management; 5.1 Eigenfiltering of Noise in Empirical Correlation Matrix; 5.1.1 Asymptotic Eigenvalue Distribution of a Random Matrix; 5.1.2 Noise in the Empirical Correlation Matrix; 5.1.3 Eigenfiltering of Built-in Market Noise
5.1.4 Estimation of Portfolio Risk in Statistical Arbitrage and Eigenfiltering of Market Noise5.2 Risk Estimation for Trading in MultipleFrequencies; 5.3 Fast Eigenfiltering for Risk Estimation; 5.3.1 AR(1) Signal Model; 5.3.2 Motivation; 5.3.3 AR(1) Approximation to Empirical Correlation Matrix; 5.3.4 Portfolio Risk Estimation with Toeplitz Approximation to Empirical Correlation Matrix; 5.3.5 Noise Filtering with Discrete Cosine Transform; 5.4 Portfolio Risk Management; 5.4.1 Stay in the Ellipsoid Method; 5.4.2 Stay on the Ellipsoid Method; 5.4.3 Stay Around the Ellipsoid Method