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• Cover
• Introduction
• About This Book
• Foolish Assumptions
• Icons Used in This Book
• Where to Go from Here
• Part 1: Getting Started with Quantitative Finance
• Chapter 1: Quantitative Finance Unveiled
• Defining Quantitative Finance
• Wielding Financial Weapons of Mass Destruction
• Analysing and Describing Market Behaviour
• Managing Risk
• Computing, Algorithms and Markets
• Chapter 2: Understanding Probability and Statistics
• Figuring Probability by Flipping a Coin
• Defining Random Variables
• Introducing Some Important Distributions
• Chapter 3: Taking a Look at Random Behaviours
• Setting Up a Random Walk
• Averaging with the Central Limit Theorem
• Moving Like the Stock Market
• Generating Random Numbers on a Computer
• Simulating Random Walks
• Moving Up a Gear
• Reverting to the Mean
• Part 2: Tackling Financial Instruments
• Chapter 4: Sizing Up Interest Rates, Shares and Bonds
• Explaining Interest
• Sharing in Profits and Growth
• Taking the Pulse of World Markets
• Defining Bonds and Bond Jargon
• Swapping between Fixed and Floating Rates
• Chapter 5: Exploring Options
• Examining a Variety of Options
• Reading Financial Data
• Getting Paid when Your Option Expires
• Using Options in Practice
• Trading Options On and Off Exchanges
• Relating the Price of Puts and Calls
• Chapter 6: Trading Risk with Futures
• Surveying Future Contracts
• Seeing into the Future
• Rolling a Position
• Converging Futures to the Spot Price
• Using Futures Creatively
• Seasonality in Futures Prices
• Part 3: Investigating and Describing Market Behaviour
• Chapter 7: Reading the Market’s Mood: Volatility
• Defining Volatility
• Using Historical Data
• Shrinking Time Using a Square Root
• Comparing Volatility Calculations
• Estimating Volatility by Statistical Means
• Going Beyond Simple Volatility Models
• Estimating Future Volatility with Term Structures
• Chapter 8: Analysing All the Data
• Data Smoothing
• Estimating More Distributions
• Modelling Non-Normal Returns
• Chapter 9: Analysing Data Matrices: Principal Components
• Reducing the Amount of Data
• Applying PCA to Yield Curves
• Using PCA to Build Models
• Part 4: Option Pricing
• Chapter 10: Examining the Binomial and Black-Scholes Pricing Models
• Looking at a Simple Portfolio with No Arbitrage
• Pricing in a Single Step
• Branching Out in Pricing an Option
• Making Assumptions about Option Pricing
• Introducing Black-Scholes – The Most Famous Equation in Quantitative Finance
• Solving the Black-Scholes Equation
• Properties of the Black-Scholes Solutions
• Generalising to Dividend-Paying Stocks
• Defining other Options
• Valuing Options Using Simulations
• Chapter 11: Using the Greeks in the Black-Scholes Model
• Using the Black-Scholes Formulae
• Hedging Class
• That’s Greek to Me: Explaining the Greek Maths Symbols
• Rebalancing a Portfolio
• Troubleshooting Model Risk
• Chapter 12: Gauging Interest-Rate Derivatives
• Looking at the Yield Curve and Forward Rates
• Modelling the Interest-Rate
• Part 5: Risk and Portfolio Management
• Chapter 13: Managing Market Risk
• Investing in Risky Assets
• Stopping Losses and other Good Ideas
• Hedging Schemes
• Betting without Losing Your Shirt
• Evaluating Outcomes with Utility Functions
• Using the Covariance Matrix to Measure Market Risk
• Chapter 14: Comprehending Portfolio Theory
• Diversifying Portfolios
• Minimising Portfolio Variance
• Capital Asset Pricing Model
• Assessing Portfolio Performance
• Chapter 15: Measuring Potential Losses: Value at Risk (VaR)
• Controlling Risk in Your Portfolio
• Defining Volatility and the VaR Measure
• Constructing VaR using the Covariance Matrix
• Estimating Volatilities and Correlations
• Simulating the VaR
• Validating Your Model
• Including the Average VaR
• Estimating Tail Risk with Extreme Value Theory
• Part 6: Market Trading and Strategy
• Chapter 16: Forecasting Markets
• Measuring with Technical Analysis
• Making Predictions Using Market Variables
• Predicting from Past Values
• Chapter 17: Fitting Models to Data
• Maximising the Likelihood
• Fitting and Overfitting
• Applying Occam’s Razor
• Detecting Outliers
• The Curse of Dimensionality
• Seeing into the Future
• Chapter 18: Markets in Practice
• Auctioning Assets
• Looking at the Price Impact of a Trade
• Being a Market Maker and Coping with Bid-Ask Spreads
• Trading Factors and Distributions
• Part 7: The Part of Tens
• Chapter 19: Ten Key Ideas of Quantitative Finance
• If Markets Were Truly Efficient Nobody Would Research Them
• The Gaussian Distribution is Very Helpful but Doesn’t Always Apply
• Don’t Ignore Trading Costs
• Know Your Contract
• Understanding Volatility is Key
• You Can Price Options by Building Them from Cash and Stock
• Finance Isn’t Like Physics
• Diversification is the One True Free Lunch
• Find Tools to Help Manage All the Data
• Don’t Get Fooled by Complex Models
• Chapter 20: Ten Ways to Ace Your Career in Quantitative Finance
• Follow Financial Markets
• Read Some Classic Technical Textbooks
• Read Some Non-technical Books
• Take a Professional Course
• Attend Networking Meetings and Conferences
• Participate in Online Communities
• Study a Programming Language
• Go Back to School
• Apply for that Hedge Fund or Bank Job
• Take Time to Rest Up and Give Back
• Glossary
• About the Author
• Advertisement Page
• Connect with Dummies
• End User License Agreement