Econometrics of Financial Markets

Regular price €77.99
A01=A. Craig MacKinlay
A01=Andrew W. Lo
A01=John Y. Campbell
Approximation
Arbitrage
Asset
Asymptotic distribution
Author_A. Craig MacKinlay
Author_Andrew W. Lo
Author_John Y. Campbell
Autocorrelation
Autocovariance
Autoregressive conditional heteroskedasticity
Bid-Ask Spread
Calculation
Capital asset pricing model
Category=KCH
Category=KFFM
Coefficient
Compound Return
Conditional expectation
Conditional probability distribution
Covariance matrix
Degrees of freedom (statistics)
Discounts and allowances
Discrete time and continuous time
Dividend
Economic equilibrium
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_non-fiction
Error term
Estimation
Estimator
Event study
Expected value
Financial economics
Forecasting
Forward rate
Generalized method of moments
Heteroscedasticity
Inference
Instrumental variable
Interest rate
Investment
Investor
Likelihood function
Likelihood-ratio test
Linear regression
Market portfolio
Market price
Maximum likelihood estimation
Nonparametric statistics
Normal distribution
Null hypothesis
Parameter
Predictability
Price Change
Pricing
Probability
Random variable
Rate of return
Real versus nominal value (economics)
Regression analysis
Risk aversion
Share price
Sharpe ratio
Standard deviation
Standard error
Statistic
Statistical significance
Stochastic discount factor
Stochastic process
Summation
Test statistic
Time series
Uncertainty
Unit root
Variance
Yield curve
Yield spread

Product details

  • ISBN 9780691043012
  • Weight: 992g
  • Dimensions: 152 x 235mm
  • Publication Date: 29 Dec 1996
  • Publisher: Princeton University Press
  • Publication City/Country: US
  • Product Form: Hardback
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The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications
John Y. Campbell is the Morton L. and Carole S. Olshan Professor of Economics at Harvard University. He is the author of Financial Decisions and Markets (Princeton) and the coauthor of Strategic Asset Allocation. Andrew W. Lo is the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management, director of the MIT Laboratory for Financial Engineering, and an external faculty member at the Santa Fe Institute. His books include Adaptive Markets and Hedge Funds (both Princeton). A. Craig MacKinlay is the Joseph P. Wargrove Professor of Finance at the Wharton School, University of Pennsylvania, where he is also an academic director at the Jacobs Levy Equity Management Center for Quantitative Financial Research. MacKinlay and Lo are the authors of A Non-Random Walk Down Wall Street (Princeton).