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The Elements of Financial Econometrics

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  • Fan,Jianqing
  • Yao,Qiwei

Abstract

Financial econometrics is an interdisciplinary subject that uses statistical methods and economic theory to address a variety of quantitative problems in finance. This compact, master's-level textbook focuses on methodology and includes real financial data illustrations throughout. The mathematical level is purposely kept moderate, allowing the power of the quantitative methods to be understood without too much technical detail. Wherever possible, the authors indicate where to find the relevant R codes to implement the various methods. This book grew out of a course at Princeton University which is one of the world's flagship programs in computational finance and financial engineering. It will therefore be useful for those with an economics and finance background who are looking to sharpen their quantitative skills, and also for those with strong quantitative skills who want to learn how to apply them to finance.

Suggested Citation

  • Fan,Jianqing & Yao,Qiwei, 2017. "The Elements of Financial Econometrics," Cambridge Books, Cambridge University Press, number 9781107191174, January.
    • Handle: RePEc:cup:cbooks:9781107191174
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    Citations

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    Cited by:

    1. Podhorsky, Andrea, 2023. "Taxing bitcoin: Incentivizing the difficulty adjustment mechanism to reduce electricity usage," International Review of Financial Analysis, Elsevier, vol. 86(C).
    2. Czudaj, Robert L., 2019. "Crude oil futures trading and uncertainty," Energy Economics, Elsevier, vol. 80(C), pages 793-811.
    3. Czudaj Robert L., 2020. "The role of uncertainty on agricultural futures markets momentum trading and volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-39, June.
    4. Simmet Anastasia & Pohlmeier Winfried, 2020. "The CAPM with Measurement Error: ‘There’s life in the old dog yet!’," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 240(4), pages 417-453, August.
    5. Basnarkov, Lasko & Stojkoski, Viktor & Utkovski, Zoran & Kocarev, Ljupco, 2020. "Lead–lag relationships in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    6. Ke Wan & Alain Kornhauser, 2023. "Market Making and Pricing of Financial Derivatives based on Road Travel Times," Papers 2305.02523, arXiv.org, revised May 2023.
    7. Zhu, Changbo & Müller, Hans-Georg, 2024. "Spherical autoregressive models, with application to distributional and compositional time series," Journal of Econometrics, Elsevier, vol. 239(2).
    8. Wan, Runzhe & Li, Yingying & Lu, Wenbin & Song, Rui, 2024. "Mining the factor zoo: Estimation of latent factor models with sufficient proxies," Journal of Econometrics, Elsevier, vol. 239(2).

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