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Introduction to Asset Price Dynamics, Volatility, and Prediction

In: Asset Price Dynamics, Volatility, and Prediction

Author

Listed:
  • Stephen J. Taylor

    (Lancaster University, England)

Abstract

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.

Suggested Citation

  • Stephen J. Taylor, 2007. "Introduction to Asset Price Dynamics, Volatility, and Prediction," Introductory Chapters, in: Asset Price Dynamics, Volatility, and Prediction, Princeton University Press.
  • Handle: RePEc:pup:chapts:8055-1
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    Citations

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    Cited by:

    1. Jonathan E. Ogbuabor & God’stime O. Eigbiremolen & Gladys C. Aneke & Manasseh O. Charles, 2018. "Measuring the dynamics of APEC output connectedness," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 32(1), pages 29-44, May.
    2. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    3. Ekeocha, Patterson & Ogbuabor, Jonathan, 2020. "Measuring and Evaluating the Dynamics of Trade Shock Propagation in the Oceania," Conference papers 333234, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    4. Bernardina Algieri, 2016. "Conditional price volatility, speculation, and excessive speculation in commodity markets: sheep or shepherd behaviour?," International Review of Applied Economics, Taylor & Francis Journals, vol. 30(2), pages 210-237, March.
    5. He, Xue-Zhong & Zheng, Huanhuan, 2016. "Trading heterogeneity under information uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 64-80.
    6. Esmeralda Gonçalves & Joana Leite & NazarÉ Mendes-Lopes, 2016. "On the Distribution Estimation of Power Threshold Garch Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(5), pages 579-602, September.
    7. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    8. Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
    9. Apostolos Ampountolas, 2019. "Forecasting hotel demand uncertainty using time series Bayesian VAR models," Tourism Economics, , vol. 25(5), pages 734-756, August.
    10. Christian Francq & Jean-Michel Zakoïan, 2013. "Estimating the Marginal Law of a Time Series With Applications to Heavy-Tailed Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 412-425, October.
    11. Christian Francq & Jean-Michel Zakoïan, 2013. "Optimal predictions of powers of conditionally heteroscedastic processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(2), pages 345-367, March.
    12. Mao, Xiuping & Ruiz, Esther & Veiga, Helena, 2017. "Threshold stochastic volatility: Properties and forecasting," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1105-1123.
    13. repec:cte:wsrepe:ws131110 is not listed on IDEAS
    14. Celeste, Valerio & Corbet, Shaen & Gurdgiev, Constantin, 2020. "Fractal dynamics and wavelet analysis: Deep volatility and return properties of Bitcoin, Ethereum and Ripple," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 310-324.
    15. Omar Rojas & Carlos Trejo-Pech, 2014. "Financial Time Series: Stylized Facts for the Mexican Stock Exchange Index Compared to Developed Markets," Papers 1412.3126, arXiv.org.
    16. Charles Cuthbertson & Grigorios Pavliotis & Avraam Rafailidis & Petter Wiberg, 2010. "Asymptotic Analysis For Foreign Exchange Derivatives With Stochastic Volatility," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 13(07), pages 1131-1147.
    17. Caio Mário Mesquita & Cristiano Arbex Valle & Adriano César Machado Pereira, 2024. "Scenario Generation for Financial Data with a Machine Learning Approach Based on Realized Volatility and Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 1879-1919, May.
    18. Algieri, Bernardina, 2012. "Price Volatility, Speculation and Excessive Speculation in Commodity Markets: sheep or shepherd behaviour?," Discussion Papers 124390, University of Bonn, Center for Development Research (ZEF).
    19. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 315-332.
    20. Ogbuabor, Jonathan E. & Anthony-Orji, Onyinye I. & Manasseh, Charles O. & Orji, Anthony, 2020. "Measuring the dynamics of COMESA output connectedness with the global economy," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).

    More about this item

    Keywords

    market prices; probability distribution; equity; foreign exchange; asset prices; option contracts; predictions; volatility; finance theory; statistical evidence; stochastic processes; mathematical models; price dynamics; random walk; trading rules; quantitative analysis;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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