May 2011
Beginner to intermediate
384 pages
12h 28m
English
Content preview from The Handbook of News Analytics in FinanceBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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6.8 DISCUSSION OF RNSE AND PORTFOLIO CONSTRUCTION
We have shown that it is possible to capitalize on news by looking at days on which a large amount of novel, very polar news occurs. The simulation is relatively unconstrained by the standards of institutional portfolios, to allow the signals to drive the process. Further increases in performance (and reductions in risk) can be implemented by
- Incorporation of quantitative price, volatility, and volume analtyics The human reaction to complicated, important news is conditioned by the market environment in which the human is processing the information, often called “market color”. Incorporating this information from “traditional” quant sources can only improve “quantextual” portfolios.
Figure 6.22. Rolling one-quarter correlation of extreme sentiment simulated portfolio with the S&P 500.
- Further news differentiation RNSE provides a very rich picture of the news as it is created and flows across the wire. Topic and product codes, headlines, and item types are probably all useful for differentiating news that presents an arbitrage opportunity from news that is merely stating prior price movements. There is also a great deal of information to be inferred from content, using either supervised (human in loop) or machine learning.
- Higher frequency trading The results here were on daily intervals. With “information leakage” a significant ...
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