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Multi-Asset Risk Modeling

Author

Listed:
  • Glantz, Morton

    (Lecturer in Finance & Business Economics, Fordham Graduate School of Business, New York, NY, USA)

  • Kissell, Robert

    (Robert Kissell, PhD, is President of Kissell Research Group, a global financial and economic consulting firm specializing in quantitative modeling, statistical analysis, and algorithmic trading. He is also currently an adjunct faculty member of the Gabelli School of Business at Fordham University, and has held several senior leadership positions with prominent bulge bracket Investment Banks.)

Abstract

Multi-Asset Risk Modeling describes, in a single volume, the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management. Covers all asset classes Provides mathematical theoretical explanations of risk as well as practical examples with empirical data Includes sections on equity risk modeling, futures and derivatives, credit markets, foreign exchange, and commodities

Suggested Citation

  • Glantz, Morton & Kissell, Robert, 2013. "Multi-Asset Risk Modeling," Elsevier Monographs, Elsevier, edition 1, number 9780124016903.
    • Handle: RePEc:eee:monogr:9780124016903
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    Citations

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    Cited by:

    1. Marvin Aron Kennis, 2018. "Multi-channel discourse as an indicator for Bitcoin price and volume movements," Papers 1811.03146, arXiv.org.
    2. Bazzana, Flavio & Collini, Andrea, 2020. "How does HFT activity impact market volatility and the bid-ask spread after an exogenous shock? An empirical analysis on S&P 500 ETF," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    3. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Karikari, Nana Kwasi & Gil-Alana, Luis Alberiko, 2022. "The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    4. Angerer, Martin & Neugebauer, Tibor & Shachat, Jason, 2023. "Arbitrage bots in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 206(C), pages 262-278.
    5. Emmanuel Joel Aikins Abakah & Guglielmo Maria Caporale & Luis A. Gil-Alana, 2021. "The Impact of Containment Measures and Monetary and Fiscal Responses on US Financial Markets during the Covid-19 Pandemic," CESifo Working Paper Series 9163, CESifo.
    6. Sonya Zhu, 2023. "Volume dynamics around FOMC announcements," BIS Working Papers 1079, Bank for International Settlements.
    7. Zineb Lanbouri & Saaid Achchab, 2019. "A new approach for Trading based on Long-Short Term memory technique [Une nouvelle approche pour le Trading basée sur la technique Long-Short Term Memory]," Post-Print hal-02396905, HAL.
    8. Erdinc Akyildirim & Ahmet Goncu & Ahmet Sensoy, 2021. "Prediction of cryptocurrency returns using machine learning," Annals of Operations Research, Springer, vol. 297(1), pages 3-36, February.
    9. Sensoy, Ahmet, 2019. "The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies," Finance Research Letters, Elsevier, vol. 28(C), pages 68-73.
    10. Akyildirim, Erdinc & Sensoy, Ahmet & Gulay, Guzhan & Corbet, Shaen & Salari, Hajar Novin, 2021. "Big data analytics, order imbalance and the predictability of stock returns," Journal of Multinational Financial Management, Elsevier, vol. 62(C).

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