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Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications

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Abstract

We develop a new framework to measure market-wide (systemic) tail risk in the cross-section of high-frequency stock returns. We estimate the time-varying jump intensities of asset prices and introduce a testing approach that identifies multi-asset tail risk based on the release times of scheduled news announcements. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we find that most of the FOMC announcements create systemic left tail risk, but there is no evidence that macro announcements do so. The magnitude of the tail risk induced by Fed news varies over the business cycle, peaks during the global financial crisis and remains high over different phases of unconventional monetary policy. We use our approach to construct a Fed-induced systemic tail risk (STR) indicator. STR helps explain the pre-FOMC announcement drift and significantly increases variance risk premia, particularly for the meetings without press conferences.

Suggested Citation

  • Deniz Erdemlioglu & Christopher J. Neely & Xiye Yang, 2023. "Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications," Working Papers 2023-016, Federal Reserve Bank of St. Louis.
  • Handle: RePEc:fip:fedlwp:96490
    DOI: 10.20955/wp.2023.016
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    1. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, July.
    2. Bibinger, Markus & Neely, Christopher & Winkelmann, Lars, 2019. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 158-184.
    3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    4. Marcel Fratzscher & Marco Lo Duca & Roland Straub, 2018. "On the International Spillovers of US Quantitative Easing," Economic Journal, Royal Economic Society, vol. 128(608), pages 330-377, February.
    5. Emi Nakamura & Jón Steinsson, 2018. "High-Frequency Identification of Monetary Non-Neutrality: The Information Effect," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(3), pages 1283-1330.
    6. Bauer, Michael D. & Neely, Christopher J., 2014. "International channels of the Fed's unconventional monetary policy," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 24-46.
    7. Chan, Kam Fong & Bowman, Robert G. & Neely, Christopher J., 2017. "Systematic cojumps, market component portfolios and scheduled macroeconomic announcements," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 43-58.
    8. Evans, Kevin P., 2011. "Intraday jumps and US macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2511-2527, October.
    9. Pierre Bajgrowicz & Olivier Scaillet & Adrien Treccani, 2016. "Jumps in High-Frequency Data: Spurious Detections, Dynamics, and News," Management Science, INFORMS, vol. 62(8), pages 2198-2217, August.
    10. Amengual, Dante & Xiu, Dacheng, 2018. "Resolution of policy uncertainty and sudden declines in volatility," Journal of Econometrics, Elsevier, vol. 203(2), pages 297-315.
    11. Lars Winkelmann & Markus Bibinger & Tobias Linzert, 2016. "ECB Monetary Policy Surprises: Identification Through Cojumps in Interest Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 613-629, June.
    12. Neely, Christopher J., 2015. "Unconventional monetary policy had large international effects," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 101-111.
    13. Valentina Corradi & Walter Distaso & Marcelo Fernandes, 2020. "Testing for Jump Spillovers Without Testing for Jumps," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1214-1226, July.
    14. Bandi, F.M. & Renò, R., 2016. "Price and volatility co-jumps," Journal of Financial Economics, Elsevier, vol. 119(1), pages 107-146.
    15. Cieslak, Anna & Schrimpf, Andreas, 2019. "Non-monetary news in central bank communication," Journal of International Economics, Elsevier, vol. 118(C), pages 293-315.
    16. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    17. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S., 2020. "High-frequency jump tests: Which test should we use?," Journal of Econometrics, Elsevier, vol. 219(2), pages 478-487.
    18. Jens H. E. Christensen & Glenn D. Rudebusch, 2012. "The Response of Interest Rates to US and UK Quantitative Easing," Economic Journal, Royal Economic Society, vol. 122(564), pages 385-414, November.
    19. Jacod, Jean & Klüppelberg, Claudia & Müller, Gernot, 2017. "Testing for non-correlation between price and volatility jumps," Journal of Econometrics, Elsevier, vol. 197(2), pages 284-297.
    20. Michael A. S. Joyce & Ana Lasaosa & Ibrahim Stevens & Matthew Tong, 2011. "The Financial Market Impact of Quantitative Easing in the United Kingdom," International Journal of Central Banking, International Journal of Central Banking, vol. 7(3), pages 113-161, September.
    21. Dungey, Mardi & Hvozdyk, Lyudmyla, 2012. "Cojumping: Evidence from the US Treasury bond and futures markets," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1563-1575.
    22. Bollerslev, Tim & Todorov, Viktor & Li, Sophia Zhengzi, 2013. "Jump tails, extreme dependencies, and the distribution of stock returns," Journal of Econometrics, Elsevier, vol. 172(2), pages 307-324.
    23. Joseph Gagnon & Matthew Raskin & Julie Remache & Brian Sack, 2011. "The Financial Market Effects of the Federal Reserve's Large-Scale Asset Purchases," International Journal of Central Banking, International Journal of Central Banking, vol. 7(1), pages 3-43, March.
    24. Masazumi Hattori & Andreas Schrimpf & Vladyslav Sushko, 2016. "The Response of Tail Risk Perceptions to Unconventional Monetary Policy," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(2), pages 111-136, April.
    25. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    26. Marco Di Maggio & Amir Kermani & Christopher J Palmer, 2020. "How Quantitative Easing Works: Evidence on the Refinancing Channel," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(3), pages 1498-1528.
    27. Refet S Gürkaynak & Brian Sack & Eric Swanson, 2005. "Do Actions Speak Louder Than Words? The Response of Asset Prices to Monetary Policy Actions and Statements," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    28. Lee, Suzanne S. & Hannig, Jan, 2010. "Detecting jumps from Lévy jump diffusion processes," Journal of Financial Economics, Elsevier, vol. 96(2), pages 271-290, May.
    29. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    30. George Kapetanios & Haroon Mumtaz & Ibrahim Stevens & Konstantinos Theodoridis, 2012. "Assessing the Economy‐wide Effects of Quantitative Easing," Economic Journal, Royal Economic Society, vol. 122(564), pages 316-347, November.
    31. Suzanne S. Lee & Per A. Mykland, 2008. "Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics," The Review of Financial Studies, Society for Financial Studies, vol. 21(6), pages 2535-2563, November.
    32. Jean-François Bégin & Christian Dorion & Geneviève Gauthier, 2020. "Idiosyncratic Jump Risk Matters: Evidence from Equity Returns and Options," The Review of Financial Studies, Society for Financial Studies, vol. 33(1), pages 155-211.
    33. Jing, Bing-Yi & Kong, Xin-Bing & Liu, Zhi & Mykland, Per, 2012. "On the jump activity index for semimartingales," Journal of Econometrics, Elsevier, vol. 166(2), pages 213-223.
    34. Joyce, Michael, 2012. "Quantitative easing and other unconventional monetary policies: Bank of England conference summary," Bank of England Quarterly Bulletin, Bank of England, vol. 52(1), pages 48-56.
    35. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
    36. Fumio Hayashi & Junko Koeda, 2019. "Exiting from quantitative easing," Quantitative Economics, Econometric Society, vol. 10(3), pages 1069-1107, July.
    37. Michael Joyce & David Miles & Andrew Scott & Dimitri Vayanos, 2012. "Quantitative Easing and Unconventional Monetary Policy – an Introduction," Economic Journal, Royal Economic Society, vol. 122(564), pages 271-288, November.
    38. David S. Bates, 2019. "How Crashes Develop: Intradaily Volatility and Crash Evolution," Journal of Finance, American Finance Association, vol. 74(1), pages 193-238, February.
    39. Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    40. Brian M Weller, 2019. "Measuring Tail Risks at High Frequency," The Review of Financial Studies, Society for Financial Studies, vol. 32(9), pages 3571-3616.
    41. Alexander Rodnyansky & Olivier M. Darmouni, 2017. "The Effects of Quantitative Easing on Bank Lending Behavior," The Review of Financial Studies, Society for Financial Studies, vol. 30(11), pages 3858-3887.
    42. Jérôme Lahaye & Sébastien Laurent & Christopher J. Neely, 2011. "Jumps, cojumps and macro announcements," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 893-921, September.
    43. David O. Lucca & Emanuel Moench, 2015. "The Pre-FOMC Announcement Drift," Journal of Finance, American Finance Association, vol. 70(1), pages 329-371, February.
    44. Jean Jacod & Viktor Todorov, 2010. "Do price and volatility jump together?," Papers 1010.4990, arXiv.org.
    45. Todorov, Viktor & Bollerslev, Tim, 2010. "Jumps and betas: A new framework for disentangling and estimating systematic risks," Journal of Econometrics, Elsevier, vol. 157(2), pages 220-235, August.
    46. Tim Bollerslev & Jia Li & Yuan Xue, 2018. "Volume, Volatility, and Public News Announcements," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(4), pages 2005-2041.
    47. Aït-Sahalia, Yacine & Xiu, Dacheng, 2016. "Increased correlation among asset classes: Are volatility or jumps to blame, or both?," Journal of Econometrics, Elsevier, vol. 194(2), pages 205-219.
    48. repec:taf:jnlbes:v:30:y:2012:i:2:p:242-255 is not listed on IDEAS
    49. van Oordt, Maarten R. C. & Zhou, Chen, 2016. "Systematic Tail Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(2), pages 685-705, April.
    50. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2020. "The Pricing of Tail Risk and the Equity Premium: Evidence From International Option Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 662-678, July.
    51. Anna Cieslak & Adair Morse & Annette Vissing‐Jorgensen, 2019. "Stock Returns over the FOMC Cycle," Journal of Finance, American Finance Association, vol. 74(5), pages 2201-2248, October.
    52. Aït-Sahalia, Yacine & Cacho-Diaz, Julio & Laeven, Roger J.A., 2015. "Modeling financial contagion using mutually exciting jump processes," Journal of Financial Economics, Elsevier, vol. 117(3), pages 585-606.
    53. Markus Pelger, 2020. "Understanding Systematic Risk: A High‐Frequency Approach," Journal of Finance, American Finance Association, vol. 75(4), pages 2179-2220, August.
    54. Suzanne S. Lee, 2012. "Jumps and Information Flow in Financial Markets," The Review of Financial Studies, Society for Financial Studies, vol. 25(2), pages 439-479.
    55. Bollerslev, Tim & Todorov, Viktor, 2014. "Time-varying jump tails," Journal of Econometrics, Elsevier, vol. 183(2), pages 168-180.
    56. Tarun Chordia, 2005. "An Empirical Analysis of Stock and Bond Market Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 18(1), pages 85-129.
    57. Boswijk, H. Peter & Laeven, Roger J.A. & Yang, Xiye, 2018. "Testing for self-excitation in jumps," Journal of Econometrics, Elsevier, vol. 203(2), pages 256-266.
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    More about this item

    Keywords

    time-varying tail risk; high-frequency data; Federal Open Market Committee (FOMC) news; monetary policy announcements; cojumps; systemic risk; jump intensity;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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