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  • Mastering R for Quantitative Finance
  • Edina Berlinger Ferenc Illés Milán Badics ?dám Banai Gergely Daróczi Barbara D?m?t?r Gergely Gabler Dániel Havran Péter Juhász
  • 170字
  • 2021-07-23 20:10:46

References

  • Bai, J. (2003): Inferential theory for factor models of large dimensions. Econometrica, 71:135-171.
  • Bialkowski, J., Darolles, S., and Le Fol, G. (2008): Improving VWAP strategies: A dynamic volume approach. Journal of Banking & Finance, 32:1709-1722.
  • Brownlees, C. T., Cipollini, F., and Gallo, G. M. (2011): Intra-daily volume modeling and prediction for algorithmic trading. Journal of Financial Econometrics, 9:489-518.
  • Hmaied, D. M., Sioud, O. B., and Grar, A. (2006): Intra-daily and weekly patterns of bid-ask spreads, trading volume and volatility on the Tunisian Stock Exchange. Banque & Marchés, 84:35-44.
  • Hussain, S. M. (2011): The intraday behavior of bid-ask spreads, trading volume, and return volatility: Evidence from DAX30. International Journal of Economics and Finance, 3:23-34.
  • Kaastra, I. and Boyd, M. S. (1995): Forecasting futures trading volume using neural networks. The Journal of Futures Markets, Vol. 15, No. 8,:953-970.
  • Lux, T. and Kaizoji, T. (2004): Forecasting volatility and volume in the Tokyo stock market: The advantage of long memory models. Economics working paper, Christian-Albrechts-Universit?t Kiel, Department of Economics.
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