Financial Economics Books
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Market Models
- A Guide to Financial Data Analysis
by Carol Alexander Chapters: 1. Understanding volatility and correlation. 2. Implied volatility and correlation. 3. Moving average models. 4. GARCH models. 5. Forecasting Volatility and Correlation. 6. Principle component analysis. 7. Covariance matrices. 8. Risk measurement in factor models. 9. Value-at-risk. 10. Modelling non-normal returns. 11. Time series models. 12. Cointegration. 13. Forecasting high-frequency data. Technical appendices: A1. Linear Regression. A2. Statistical inference. A3. Residual analysis. A4. Data problems. A5. Prediction. A6. Maximum likelihood methods. |
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Numerical Methods in Finance
- A MATLAB-Based Introduction
by Paolo Brandimarte |
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The Econometrics of Financial Markets
by John Campbell, Andrew W. Lo, and A. Craig MacKinlay |
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Introduction to the Economics and Mathematics of Financial Markets
by Jaksa Cvitanic and Fernando Zaperto MIT Press |
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Solutions Manual
- Introduction to the Economics and Mathematics of Financial Markets
by Jaksa Cvitanic and Fernando Zaperto MIT Press |
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An Introduction to High-Frequency Finance
by Michel M. Dacorogna, et al. |
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Financial Crises
- And What to Do About Them
by Barry Eichengreen |
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Modern Portfolio Theory and Investment Analysis
by Edwin J. Elton, Martin J. Gruber, Stephen J. Brown and William N. Goetzmann |
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Non-Linear Time Series Models in Empirical Finance
by Philip Hans Franses and Dick van Dijk |
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The New Finance
- The Case Against Efficient Markets
by Robert A. Haugen |
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Value-at-Risk
- Theory and Practice
by Glen Holton |
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Foundations for Financial Economics
by Chi-fu Huang, Robert H. Litzenberger Prentice Hall |
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Puzzles of Finance
- Six Practical Problems and Their Remarkable Solutions
by Mark Kritzman This small book is loaded with insights to make better financial decisions. Much of what passes as common sense investment rules of thumb contain logical falacies or violate certain principles of financial mathematics and risk management. This book sets it straight, being clear to show the assumptions under that make the arguments hold together. Chapters: 1. Siegel's paradox; 2. Likelihood of loss; 3. Time diversification; 4. Why the expected return is not to be expected; 5. Half the stocks all the time or all the stocks half the time; 6. The irrelevance of expected return for option valuation; Primer: 7. Financial concepts and quantitative methods. |
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Computational Finance
- Numerical Methods for Pricing Financial Instruments
by George Levy |
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Modern Investment Management
- An Equilibrium Approach
by Bob Litterman Wiley |
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Fractals and Scaling in Finance
by Benoit B. Mandelbrot |
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The Misbehavior of Markets
by Benoit B. Mandelbrot, Richard L. Hudson |
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Mean-Variance Analysis in Portfolio Choice and Capital Markets
by Harry M. Markowitz, G. Peter Todd, William F. Sharpe Wiley |
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Applied Computational Economics and Finance
by Mario J. Miranda and Paul L. Fackler |
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Applied Computational Economics and Finance
by Mario Mirande and Paul L. Fackler MIT Press |
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Market Volatility
by Robert Shiller |
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Inefficient Markets
- An Introduction to Behavioral Finance
by Andre Shleifer |
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Analysis of Financial Time Series
by Ruey S. Tsay |
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Paul Wilmott on Quantitative Finance
- 2 Volume Set
by Paul Wilmott |