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The relationship between the volatility of returns and the number of jumps in financial markets

Listed author(s):
  • Cartea, Álvaro
  • Karyampas, Dimitrios

The contribution of this paper is two-fold. First we show how to estimate the volatility of high frequency log-returns where the estimates are not a affected by microstructure noise and the presence of Lévy-type jumps in prices. The second contribution focuses on the relationship between the number of jumps and the volatility of log-returns of the SPY, which is the fund that tracks the S&P 500. We employ SPY high frequency data (minute-by-minute) to obtain estimates of the volatility of the SPY log-returns to show that: (i) The number of jumps in the SPY is an important variable in explaining the daily volatility of the SPY log-returns; (ii) The number of jumps in the SPY prices has more explanatory power with respect to daily volatility than other variables based on: volume, number of trades, open and close, and other jump activity measures based on Bipower Variation; (iii) The number of jumps in the SPY prices has a similar explanatory power to that of the VIX, and slightly less explanatory power than measures based on high and low prices, when it comes to explaining volatility; (iv) Forecasts of the average number of jumps are important variables when producing monthly volatility forecasts and, furthermore, they contain information that is not impounded in the VIX.

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File URL: http://e-archivo.uc3m.es/bitstream/handle/10016/5903/wb097508.pdf?sequence=1
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Paper provided by Universidad Carlos III de Madrid. Departamento de Economía de la Empresa in its series DEE - Working Papers. Business Economics. WB with number wb097508.

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Date of creation: Dec 2009
Handle: RePEc:cte:wbrepe:wb097508
Contact details of provider: Web page: http://www.business.uc3m.es/es/index

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