Abstract
The Black–Litterman (BL) model for portfolio optimization combines investors’ expectations with the Markowitz framework. The BL model is designed for investors with private information or knowledge of market behaviour. In this paper, I propose a method where investors’ expectations are based on either news sentiment using high-frequency data or on a combination of accounting variables; financial analysts’ recommendations, and corporate social network indicators with quarterly data. The results show promise when compared to a market portfolio. I also provide recommendations for trading strategies using the results of this BL model.
| Original language | English |
|---|---|
| Pages (from-to) | 1405-1416 |
| Number of pages | 12 |
| Journal | Quantitative Finance |
| Volume | 15 |
| Issue number | 8 |
| DOIs | |
| State | Published - 3 Aug 2015 |
Keywords
- Black–Litterman model
- Boosting
- Link mining
- Machine learning
- Portfolio optimization
- Social network
- Text analysis
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