| Description |
1 online resource : illustrations |
| Series |
--For dummies.
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| Contents |
Title Page -- Copyright Page -- Table of Contents -- 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 -- Summarising the mathematics -- Pricing, managing and trading -- Meeting the market participants -- Walking like a drunkard -- Knowing that almost nothing isn't completely nothing -- Recognising irrational exuberance -- Wielding Financial Weapons of Mass Destruction -- Going beyond cash -- Inventing new contracts -- Analysing and Describing Market Behaviour -- Measuring jumpy prices -- Keeping your head while using lots of data -- Valuing your options -- Managing Risk -- Hedging and speculating -- Generating income -- Building portfolios and reducing risk -- Computing, Algorithms and Markets -- Seeing the signal in the noise -- Keeping it simple -- Looking at the finer details of markets -- Trading at higher frequency -- Chapter 2 Understanding Probability and Statistics -- Figuring Probability by Flipping a Coin -- Playing a game -- Flipping more coins -- Defining Random Variables -- Using random variables -- Building distributions with random variables -- Introducing Some Important Distributions -- Working with a binomial distribution -- Recognising the Gaussian, or normal, distribution -- Describing real distributions -- Chapter 3 Taking a Look at Random Behaviours -- Setting Up a Random Walk -- Stepping in just two directions -- Getting somewhere on your walk -- Taking smaller and smaller steps -- Averaging with the Central Limit Theorem -- Moving Like the Stock Market -- Generating Random Numbers on a Computer -- Getting random with Excel -- Using the central limit theorem again -- Simulating Random Walks -- Moving Up a Gear |
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Working a stochastic differential equation -- Expanding from the origin -- Reverting to the Mean -- Part 2 Tackling Financial Instruments -- Chapter 4 Sizing Up Interest Rates, Shares and Bonds -- Explaining Interest -- Compounding your interest -- Compounding continuously -- Sharing in Profits and Growth -- Taking the Pulse of World Markets -- Defining Bonds and Bond Jargon -- Coupon-bearing bonds -- Zeroing in on yield -- Cleaning up prices -- Learning to like LIBOR -- Plotting the yield curve -- Swapping between Fixed and Floating Rates -- Chapter 5 Exploring Options -- Examining a Variety of Options -- Starting with plain vanilla options -- Aiming for a simple, binary option -- Branching out with more exotic options -- Reading Financial Data -- Seeing your strike price -- Abbreviating trading information -- Valuing time -- Getting Paid when Your Option Expires -- Using Options in Practice -- Hedging your risk -- Placing bets on markets -- Writing options -- Earning income from options -- Distinguishing European, American and other options -- Trading Options On and Off Exchanges -- Relating the Price of Puts and Calls -- Chapter 6 Trading Risk with Futures -- Surveying Future Contracts -- Trading the futures market -- Marking to market and margin accounts -- Dealing in commodity futures -- Index futures -- Interest rate futures -- Seeing into the Future -- Paying in cash now -- Connecting futures and spot prices -- Checking trading volume -- Looking along the forward curve -- Rolling a Position -- Keeping a consistent position -- Adjusting backwards -- Converging Futures to the Spot Price -- Using Futures Creatively -- Calendar spreads -- Commodity spreads -- Seasonality in Futures Prices -- Part 3 Investigating and Describing Market Behaviour -- Chapter 7 Reading the Market's Mood: Volatility -- Defining Volatility |
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Using Historical Data -- Weighting the data equally -- Weighting returns -- Shrinking Time Using a Square Root -- Comparing Volatility Calculations -- Estimating Volatility by Statistical Means -- The symmetric GARCH model -- The leverage effect -- Going Beyond Simple Volatility Models -- Stochastic volatility -- Regime switching -- Estimating Future Volatility with Term Structures -- Chapter 8 Analysing All the Data -- Data Smoothing -- Putting data in bins -- Smoothing data with kernels -- Using moving averages as filters -- Estimating More Distributions -- Mixing Gaussian distributions -- Going beyond one dimension -- Modelling Non-Normal Returns -- Testing and visualising non-normality -- Maximising expectations -- Reducing the Amount of Data -- Understanding collinearity -- Standardising data -- Brushing up some maths -- Decomposing data matrices into principal components -- Calculating principal components -- Checking your model with cross- validation -- Applying PCA to Yield Curves -- Using PCA to Build Models -- Identifying clusters of data -- Principal components regression -- 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 -- Entering the world of risk neutral -- Calculating the parameters -- Branching Out in Pricing an Option -- Building a tree of asset prices -- Building a tree of option prices by working backwards -- Pricing an American 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 |
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Using the Black-Scholes Formulae -- Hedging Class -- That's Greek to Me: Explaining the Greek Maths Symbols -- Delta -- Dynamic hedging and gamma -- Theta -- Rho -- Vega -- Relating the Greeks -- Rebalancing a Portfolio -- Troubleshooting Model Risk -- Chapter 12 Gauging Interest-Rate Derivatives -- Looking at the Yield Curve and Forward Rates -- Forward rate agreements -- Interest-rate derivatives -- Black 76 model -- Bond pricing equations -- The market price of risk -- Modelling the Interest-Rate -- The Ho Lee model -- The one-factor Vasicek model -- Arbitrage free models -- 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 -- Seeking certainty -- Modelling attitudes to risk -- Using the Covariance Matrix to Measure Market Risk -- Estimating parameters -- Shrinking the covariance matrix -- Chapter 14 Comprehending Portfolio Theory -- Diversifying Portfolios -- Minimising Portfolio Variance -- Using portfolio budget constraints -- Doing the maths for returns and correlations -- Building an efficient frontier -- Dealing with poor estimates -- Capital Asset Pricing Model -- Assessing Portfolio Performance -- Sharpe ratio -- Drawdowns -- Going for risk parity -- 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 -- Calculating a simple cash portfolio -- Using the covariance matrix -- Estimating Volatilities and Correlations -- Simulating the VaR -- Using historical data -- Spinning a Monte Carlo simulation -- Validating Your Model -- Backtesting -- Stress testing and the Basel Accord |
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Includes the Average VaR -- Estimating Tail Risk with Extreme Value Theory -- Part 6 Market Trading and Strategy -- Chapter 16 Forecasting Markets -- Measuring with Technical Analysis -- Constructing candlesticks -- Relying on relative strength -- Checking momentum indicators -- Blending the stochastic indicator -- Breaking out of channels -- Making Predictions Using Market Variables -- Understanding regression models -- Forecasting with regression models -- Predicting from Past Values -- Defining and calculating autocorrelation -- Getting to know autocorrelation models -- Moving average models -- Mentioning kernel regression -- Chapter 17 Fitting Models to Data -- Maximising the Likelihood -- Minimising least squares -- Using chi-squared -- Comparing models with Akaike -- Fitting and Overfitting -- Applying Occam's Razor -- Detecting Outliers -- The Curse of Dimensionality -- Seeing into the Future -- Backtesting -- Out-of-sample validation -- Chapter 18 Markets in Practice -- Auctioning Assets -- Selling on eBay -- Auctioning debt by the US Treasury -- Balancing supply and demand with double-sided auctions -- Looking at the Price Impact of a Trade -- Being a Market Maker and Coping with Bid-Ask Spreads -- Exploring the meaning of liquidity -- Making use of information -- Calculating the bid-ask spread -- 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 |
| Summary |
An accessible, thorough introduction to quantitative finance Does the complex world of quantitative finance make you quiver' You're not alone! It's a tough subject for even high-level financial gurus to grasp, but Quantitative Finance For Dummies offers plain-English guidance on making sense of applying mathematics to investing decisions. With this complete guide, you'll gain a solid understanding of futures, options and risk, and get up-to-speed on the most popular equations, methods, formulas and models (such as the Black-Scholes model) that are applied in quantitative finance. Also known as mathematical finance, quantitative finance is the field of mathematics applied to financial markets. It's a highly technical discipline-but almost all investment companies and hedge funds use quantitative methods. This fun and friendly guide breaks the subject of quantitative finance down to easily digestible parts, making it approachable for personal investors and finance students alike. With the help of Quantitative Finance For Dummies, you'll learn the mathematical skills necessary for success with quantitative finance, the most up-to-date portfolio and risk management applications and everything you need to know about basic derivatives pricing.-Covers the core models, formulas and methods used in quantitative finance -Includes examples and brief exercises to help augment your understanding of QF -Provides an easy-to-follow introduction to the complex world of quantitative finance -Explains how QF methods are used to define the current market value of a derivative security Whether you're an aspiring quant or a top-tier personal investor, Quantitative Finance For Dummies is your go-to guide for coming to grips with QF/risk management |
| Notes |
"Learning made easy"--Cover |
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Includes index |
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Online resource; title from PDF title page (EBSCO, viewed June 20, 2016) |
| Subject |
Finance -- Mathematical models.
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Options (Finance) -- Mathematical models
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BUSINESS & ECONOMICS -- Finance.
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Finance -- Mathematical models
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Options (Finance) -- Mathematical models
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| Form |
Electronic book
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| ISBN |
9781118769423 |
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1118769422 |
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9781118769430 |
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1118769430 |
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