Advertisement

Sentiment Proxies: Computing Market Volatility

  • Stephen Kelly
  • Khurshid Ahmad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7435)

Abstract

Macroeconomic announcements can have an influential effect on the price, and related volatility, of an object traded in financial markets. Modeling the impact of a relevant announcement on a specific commodity is of interest in building financial models of such objects. The announcements may generate false hopes or correctly indicate the ways in which the prices of objects may change. We describe a bootstrap model which is an attempt to analyse the impact of a publicly released oil inventory announcement on the price of oil futures contracts. A comparison with traditional econometric regression model is presented and we perturb the traditional models with: (a) a dummy time series that contains the dates on which the announcement is made, and (b) a sentiment time series that reflects the sentiment of the market. The sentiment time series is generated using natural language processing techniques.

Keywords

Price Change Sentiment Analysis Future Contract Foreign Exchange Market Price Return 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ahmad, K.: Affective Computing and Sentiment Analysis: Metaphor, Ontology and Terminology. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  2. 2.
    Almeida, A., Goodhart, C., Payne, R.: The effects of macroeconomic news on high frequency exchange rate behavior. J. Fin. and Quant. Analysis 22, 383–408 (1998)CrossRefGoogle Scholar
  3. 3.
    Andersen, T.G., Bollerslev, T., et al.: Real-time price discovery in global stock, bond and foreign exchange markets. NBER Working Paper Series, No. 11312(2), pp. 251–277 (2007)Google Scholar
  4. 4.
    Boyer, M.M., Filion, D.: Common and Fundamental Factors in Stock Returns of Canadian Oil and Gas Companies. Energy Economics 29(3), 428–453 (2007)CrossRefGoogle Scholar
  5. 5.
    Bauwens, L., Ben Omrane, W., Giot, P.: News announcements, market activity and volatility in the $ foreign exchange market. J. Int. Money and Finance 24(7), 1108–1125 (2003)CrossRefGoogle Scholar
  6. 6.
    Ederington, L.H., Lee, J.H.: How Markets Process Information: News Releases and Volatility. J. Finance 48(4), 1161 (1993)CrossRefGoogle Scholar
  7. 7.
    Efron, B., Tibshirani, R.: An introduction to the bootstrap. Chapman Hall (1993)Google Scholar
  8. 8.
    Groß-Klußmann, A., Hautsch, N.: When machines read the news: Using automated text analytics to quantify high frequency news-[..]. J. Emp. Finance 18(2), 321–340 (2011)CrossRefGoogle Scholar
  9. 9.
    Payne, R.: Announcement effects and seasonality in the intra-day foreign exchange market. Discussion paper series, vol. 238. LSE Financial Markets Group (1996)Google Scholar
  10. 10.
    WPSR (Weekly Petroleum Status Report), http://www.eia.gov
  11. 11.
    Xu, B., Ouenniche, J.: A data envelopment analysis-based framework for the relative performance evaluation of competing crude oil prices volatility forecasting models. Energy Economics 34(2), 576–583 (2012)CrossRefGoogle Scholar
  12. 12.
    Ye, M., Zyren, J., Shore, J.: Forecasting crude oil spot price using OECD petroleum inventory levels. Int. Adv. in Economic Research 8(4), 324–333 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stephen Kelly
    • 1
  • Khurshid Ahmad
    • 1
  1. 1.Trinity College DublinIreland

Personalised recommendations