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Intelligent Asset ManagementSentiment Analysis for View Modeling

Intelligent Asset Management: Sentiment Analysis for View Modeling [This chapter investigates a method to incorporate market sentiment to asset allocation models. In the previous chapter, we experimented with robust mean-variance optimization, which is a static process that finds the status quo optimal portfolio weights and surfs market fluctuations. However, an important piece of the jigsaw is missing, i.e., the irrational components in rise and fall of asset prices. In fact, if all the market participants hold the same robust Markowitz portfolio, the market would not clear, nor would transactions happen. The Black-Litterman modelBlack-Litterman model provides us an entry to include subjective views to asset allocation models. As an extension to it, concept-level sentiment analysis methods described in this chapter will be used to compute the subjective views, emulating a financial analyst’s activities.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Intelligent Asset ManagementSentiment Analysis for View Modeling

Part of the Socio-Affective Computing Book Series (volume 9)
Xing, Frank; Cambria, Erik; Welsch, Roy
Intelligent Asset Management — Nov 14, 2019
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Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2019
ISBN
978-3-030-30262-7
Pages
63 –96
DOI
10.1007/978-3-030-30263-4_5
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter investigates a method to incorporate market sentiment to asset allocation models. In the previous chapter, we experimented with robust mean-variance optimization, which is a static process that finds the status quo optimal portfolio weights and surfs market fluctuations. However, an important piece of the jigsaw is missing, i.e., the irrational components in rise and fall of asset prices. In fact, if all the market participants hold the same robust Markowitz portfolio, the market would not clear, nor would transactions happen. The Black-Litterman modelBlack-Litterman model provides us an entry to include subjective views to asset allocation models. As an extension to it, concept-level sentiment analysis methods described in this chapter will be used to compute the subjective views, emulating a financial analyst’s activities.]

Published: Nov 14, 2019

Keywords: Concept-level sentiment analysis; Subjective view modeling; Market sentiment; The Black-Litterman model; Sentic computing; ECM-LSTM LSTMECM-LSTM

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