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Market and Liquidity Risks Using Transaction-by-Transaction Information

Author

Listed:
  • Mariano González-Sánchez

    (Department of Business and Accounting, UNED (Universidad Nacional de Educación a Distancia), Paseo Senda del Rey, 11 Madrid, Spain)

  • Eva M. Ibáñez Jiménez

    (Department of Business and Accounting, UNED (Universidad Nacional de Educación a Distancia), Paseo Senda del Rey, 11 Madrid, Spain)

  • Ana I. Segovia San Juan

    (Department of Business and Accounting, UNED (Universidad Nacional de Educación a Distancia), Paseo Senda del Rey, 11 Madrid, Spain)

Abstract

The usual measures of market risk are based on the axiom of positive homogeneity while neglecting an important element of market information—liquidity. To analyze the effects of this omission, in the present study, we define the behavior of prices and volume via stochastic processes subordinated to the time elapsing between two consecutive transactions in the market. Using simulated data and market data from companies of different sizes and capitalization levels, we compare the results of measuring risk using prices compared to using both prices and volumes. The results indicate that traditional measures of market risk behave inversely to the degree of liquidity of the asset, thereby underestimating the risk of liquid assets and overestimating the risk of less liquid assets.

Suggested Citation

  • Mariano González-Sánchez & Eva M. Ibáñez Jiménez & Ana I. Segovia San Juan, 2021. "Market and Liquidity Risks Using Transaction-by-Transaction Information," Mathematics, MDPI, vol. 9(14), pages 1-14, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:14:p:1678-:d:595865
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    References listed on IDEAS

    as
    1. Ron Dembo & Dan Rosen, 1999. "The practice of portfolio replication. A practical overview of forward and inverse problems," Annals of Operations Research, Springer, vol. 85(0), pages 267-284, January.
    2. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
    3. Bae, Kyounghun & Kim, Daejin, 2020. "Liquidity risk and exchange-traded fund returns, variances, and tracking errors," Journal of Financial Economics, Elsevier, vol. 138(1), pages 222-253.
    4. Theo Berger & Christina Uffmann, 2021. "Assessing liquidity‐adjusted risk forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1179-1189, November.
    5. Leland, Hayne E, 1985. "Option Pricing and Replication with Transactions Costs," Journal of Finance, American Finance Association, vol. 40(5), pages 1283-1301, December.
    6. Dionne, Georges & Duchesne, Pierre & Pacurar, Maria, 2009. "Intraday Value at Risk (IVaR) using tick-by-tick data with application to the Toronto Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 777-792, December.
    7. Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
    8. U. Çetin & R. Jarrow & P. Protter & M. Warachka, 2008. "Pricing Options in an Extended Black Scholes Economy with Illiquidity: Theory and Empirical Evidence," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 9, pages 185-221, World Scientific Publishing Co. Pte. Ltd..
    9. Bialkowski, Jedrzej & Darolles, Serge & Le Fol, Gaëlle, 2008. "Improving VWAP strategies: A dynamic volume approach," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1709-1722, September.
    10. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    11. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    12. Luc Bauwens & Pierre Giot, 2000. "The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks," Annals of Economics and Statistics, GENES, issue 60, pages 117-149.
    13. Raberto, Marco & Scalas, Enrico & Mainardi, Francesco, 2002. "Waiting-times and returns in high-frequency financial data: an empirical study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 749-755.
    14. repec:adr:anecst:y:2000:i:60:p:05 is not listed on IDEAS
    15. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    16. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    17. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2008. "Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration," Annals of Finance, Springer, vol. 4(2), pages 217-241, March.
    18. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    19. Timotheos Angelidis & Alexandros Benos, 2006. "Liquidity adjusted value-at-risk based on the components of the bid-ask spread," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 835-851.
    20. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    21. Indeewara Perera & Javier Hidalgo & Mervyn J. Silvapulle, 2016. "A Goodness-of-Fit Test for a Class of Autoregressive Conditional Duration Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1111-1141, June.
    22. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    23. Persaud, Avinash, 2003. "Liquidity black holes: why modern financial regulation in developed countries is making short-term capital flows to developing countries even more volatile," Copublicaciones, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), number 1786.
    24. Cohen & Shin, 2013. "Positive Feedback Trading Under Stress: Evidence from the US Treasury Securities Market," Global Economic Review, Taylor & Francis Journals, vol. 42(4), pages 314-345, December.
    25. Easley, David & O'Hara, Maureen, 1992. "Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
    26. Hans Föllmer & Alexander Schied, 2002. "Convex measures of risk and trading constraints," Finance and Stochastics, Springer, vol. 6(4), pages 429-447.
    27. Frittelli, Marco & Rosazza Gianin, Emanuela, 2002. "Putting order in risk measures," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1473-1486, July.
    28. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    29. Angel Pardo & Roberto Pascual, 2012. "On the hidden side of liquidity," The European Journal of Finance, Taylor & Francis Journals, vol. 18(10), pages 949-967, November.
    30. Carlo Acerbi & Giacomo Scandolo, 2008. "Liquidity risk theory and coherent measures of risk," Quantitative Finance, Taylor & Francis Journals, vol. 8(7), pages 681-692.
    31. A.E. Whalley & P. Wilmott, 1999. "Optimal Hedging of Options with Small but Arbitrary Transaction Cost Structure," OFRC Working Papers Series 1999mf09, Oxford Financial Research Centre.
    32. Dang, Tung Lam & Nguyen, Thi Minh Hue, 2020. "Liquidity risk and stock performance during the financial crisis," Research in International Business and Finance, Elsevier, vol. 52(C).
    33. Hans Rau-Bredow, 2019. "Bigger Is Not Always Safer: A Critical Analysis of the Subadditivity Assumption for Coherent Risk Measures," Risks, MDPI, vol. 7(3), pages 1-18, August.
    34. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    35. Kunitomo, Naoto, 1992. "Improving the Parkinson Method of Estimating Security Price Volatilities," The Journal of Business, University of Chicago Press, vol. 65(2), pages 295-302, April.
    36. Yiu-kuen Tse & Thomas Tao Yang, 2012. "Estimation of High-Frequency Volatility: An Autoregressive Conditional Duration Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 533-545, April.
    37. Kozubowski, Tomasz J. & Podgórski, Krzysztof & Rychlik, Igor, 2013. "Multivariate generalized Laplace distribution and related random fields," Journal of Multivariate Analysis, Elsevier, vol. 113(C), pages 59-72.
    38. David Heath & Hyejin Ku, 2004. "Pareto Equilibria with coherent measures of risk," Mathematical Finance, Wiley Blackwell, vol. 14(2), pages 163-172, April.
    39. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    40. Dong‐Hyun Ahn & Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 1999. "Optimal Risk Management Using Options," Journal of Finance, American Finance Association, vol. 54(1), pages 359-375, February.
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