Essentials of Financial Economics (eBook, PDF)
A Hands-On Approach
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This textbook offers a comprehensive guide to key topics in financial economics, seamlessly blending theoretical insights with practical applications. It covers essential areas such as portfolio allocation, asset pricing, empirical finance, and behavioral finance, providing students with a solid conceptual foundation through a combination of theory and real-world examples.Core topics include mean-variance portfolio theory, linear factor models for asset pricing, consumption-based asset pricing, the Black-Litterman asset allocation model, empirical cross-sectional asset pricing, and event studi...
This textbook offers a comprehensive guide to key topics in financial economics, seamlessly blending theoretical insights with practical applications. It covers essential areas such as portfolio allocation, asset pricing, empirical finance, and behavioral finance, providing students with a solid conceptual foundation through a combination of theory and real-world examples.
Core topics include mean-variance portfolio theory, linear factor models for asset pricing, consumption-based asset pricing, the Black-Litterman asset allocation model, empirical cross-sectional asset pricing, and event studies. With a strong emphasis on hands-on implementation, the book integrates programming languages such as MATLAB, Python, Julia, and R, enabling students to apply financial models effectively.
The book begins with a concise and standard review of decision-making under uncertainty, gradually advancing to topics such as intertemporal consumption choices and their impact on asset prices, before concluding with empirical tools for capturing market sentiment. By bridging fundamental and advanced finance concepts, it equips students with the necessary tools to navigate the financial landscape. Theoretical models are presented with transparency, avoiding the "black box" issue by clearly explaining mathematical derivations. This structured approach enhances learning and empowers students to utilize the provided code for key financial tasks, including portfolio management, risk analysis, and market sentiment analysis.
Core topics include mean-variance portfolio theory, linear factor models for asset pricing, consumption-based asset pricing, the Black-Litterman asset allocation model, empirical cross-sectional asset pricing, and event studies. With a strong emphasis on hands-on implementation, the book integrates programming languages such as MATLAB, Python, Julia, and R, enabling students to apply financial models effectively.
The book begins with a concise and standard review of decision-making under uncertainty, gradually advancing to topics such as intertemporal consumption choices and their impact on asset prices, before concluding with empirical tools for capturing market sentiment. By bridging fundamental and advanced finance concepts, it equips students with the necessary tools to navigate the financial landscape. Theoretical models are presented with transparency, avoiding the "black box" issue by clearly explaining mathematical derivations. This structured approach enhances learning and empowers students to utilize the provided code for key financial tasks, including portfolio management, risk analysis, and market sentiment analysis.
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