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Forecasting S&P500 volatility by characterizing shocks using Latent Semantic Analysis on new articles

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Moreno Miranda, Nicolas ULiège
Promotor(s) : Lambert, Marie ULiège
Date of defense : 23-Jun-2016/28-Jun-2016 • Permalink : http://hdl.handle.net/2268.2/1305
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Title : Forecasting S&P500 volatility by characterizing shocks using Latent Semantic Analysis on new articles
Author : Moreno Miranda, Nicolas ULiège
Date of defense  : 23-Jun-2016/28-Jun-2016
Advisor(s) : Lambert, Marie ULiège
Committee's member(s) : Ittoo, Ashwin ULiège
Platania, Federico ULiège
Language : English
Number of pages : 63
Keywords : [en] LSA
[en] GARCH
[en] EGARCH
[en] GARCH-X
[en] Latent Semantic Analysis
[en] Volatility Forecasting
[en] S&P500
[en] Lagged corredlations
[en] Reuters
[en] News
[en] News Articles
[en] Conditional Volatility
Discipline(s) : Business & economic sciences > Finance
Institution(s) : Université de Liège, Liège, Belgique
Degree: Master en ingénieur de gestion, à finalité spécialisée en Financial Engineering
Faculty: Master thesis of the HEC-Ecole de gestion de l'Université de Liège

Abstract

[en] The information contained in news articles plays a key role on
financial markets. It may describe changes in the fundamentals of a company
or influence the way investors perceive the risk associated with it. This paper
aims at measuring with mathematical means the main underlying semantic
content of news articles, such that it captures information useful to forecast
volatility.

A modified EGARCH model with external factors, obtained from a latent semantic alaysis on news articles, is proposed to measure the impact on volatility induced by the latent semantic content of the textual news data. I find that several semantic dimensions play an important
role in explaining observed volatility, while others are useful to forecast it. It
is likely, that with further research, a model based on semantic content could
greatly improve our understanding of the market’s response to news releases.


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Author

  • Moreno Miranda, Nicolas ULiège Université de Liège > Master ingé. gest., fin. spéc. fin. engin. (ex 2e ma.)

Promotor(s)

Committee's member(s)

  • Ittoo, Ashwin ULiège Université de Liège - ULg > HEC-Ecole de gestion de l'ULg : UER > Systèmes d'information de gestion
    ORBi View his publications on ORBi
  • Platania, Federico ULiège Université de Liège - ULg > HEC-Ecole de gestion de l'ULg : UER > Analyse financière et finance d'entreprise
    ORBi View his publications on ORBi
  • Total number of views 51
  • Total number of downloads 22










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