Asset Price Dynamics, Volatility, and Prediction
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A01=Stephen J. Taylor
Approximation
Arbitrage
Asymptotic distribution
Author_Stephen J. Taylor
Autocorrelation
Autoregressive conditional heteroskedasticity
Calculation
Category=KFF
Conditional expectation
Conditional probability distribution
Conditional variance
Cumulative distribution function
Currency
Discrete time and continuous time
Dividend
Efficient-market hypothesis
eq_bestseller
eq_business-finance-law
eq_isMigrated=0
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Estimation
Estimation theory
Excess Kurtosis
Exchange rate
Expected value
Forecasting
Forward price
Futures contract
Futures exchange
Geometric Brownian motion
Implied volatility
Independent and identically distributed random variables
Interest rate
Intraday Return
Investor
Kurtosis
Likelihood function
Likelihood-ratio test
Linear function
Logarithm
Market price
Monte Carlo method
Normal distribution
Parameter
Percentage
Prediction
Price Change
Pricing
Probability
Probability distribution
Quantity
Random variable
Random walk hypothesis
Risk premium
S&P 100
S&P 500 Index
Skewness
Special case
Standard deviation
Standard error
Stationary process
Statistic
Stochastic process
Stochastic volatility
Stock market
Stock market index
Summary statistics
Summation
Test statistic
Time series
Transaction cost
Valuation (finance)
Variable (mathematics)
Variance
Volatility clustering
Wiener process
Product details
- ISBN 9780691134796
- Weight: 765g
- Dimensions: 156 x 235mm
- Publication Date: 02 Sep 2007
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Paperback
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This book shows how current and recent market prices convey information about the probability distributions that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and assess predictions about future prices, their volatility, and their probability distributions. Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributions.
Asset Price Dynamics, Volatility, and Prediction is ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative analysts, fund managers, risk managers, and investors who seek realistic expectations about future asset prices and the risks to which they are exposed.
Stephen J. Taylor is Professor of Finance at Lancaster University, England. He is the author of "Modelling Financial Time Series" and many influential articles about applications of financial econometrics.
