1. 1 Event Based Financial Information Extract and analysis Student : Lee, Dah-Sheng Professor: Lee, Hahn-Ming Date: 23 July 2004

2. 2 Outline  Motivation  Property analysis  Related work  Approach  References

3. 3 Motivation  At important events or announcements, there can be large changes in the value of securities.  Events and their corresponding jumps can occur at random or scheduled times. However, the amplitude of the response in either case can be unpredictable or random.

4. 4 Property analysis of event  Classified event: –ex:international OR local, report or news and so on.  Accuracy of event: –It depends on author, source of event, publish date and so on.  Effective time of limitations: –The effects of events are Long term, Short term or no effective.

5. Related work 1/2 AuthorFocusMethodDiscussion [1] 2003 Kei-keung Hung et al. 1.EASLD combines the ASLD(adaptive supervised learning decision )trading system ) with a portfolio optimization scheme to take a balance between the expected returns and risks. 2.Time-varying portfolio is better than static one. 1.Using two kinds of portfolio optimization scheme, SMPO and IPSRM-D, to get a balance between the expected returns and risks for ASLD System. 2.Learning relations of weighting of N assets in portfolio by ENRBF NN. to modify weighting dynamically. 1.Experimental is base on flat price movement of assets (stock market index and Foreign Exchange Market). The EASLD may not analysis the violent price fluctuation. 2.The final result of portfolio of assets are selected by refer to a fixed threshold value, is it rational ?? [2]2002 Peijun Guo et al. Portfolio construction problem transformed into a conflict one of inherent diversity of knowledge. Dual exponential possibility distributions are identified from the given data to characterize a decision-maker’s knowledge. A decision group’s knowledge can be represented by a set of such dual possibility distributions. 1.The method has the property of fuzzy and rough sets. 2.The outlier decided by a fixed threshold value may not a efficiently method.

6. Related work 2/2 AuthorFocusMethodDiscussion [3]2001 Nicolas Chapados et al. 1.To implementing asset- allocation framework of statistics by using approach of A.I.. 2.The authors focus on feasibility study of implementation in Neural Network. 1.Three models implemented by Neural Network, the first one is make to forecast of asset behavior and the second paradigm is directly make the portfolio allocation decisions with (or without) recurrence. 2. All of the models above are used the same net structural. 3. The risk-free asset is assigned. 1.In this paper, very high performance is not the target which the authors want. 2.They want to prove the VaR-Based framework can constructed on Neural Network. 3.The return of portfolio is better the stock index and the experimental result is satisfied in testing of hypothesis.

7. 7 Approach

8. 8 References [1] "An Extended ASLD Trading System to Enhance Portfolio Management“,An Extended ASLD Trading System to Enhance Portfolio Management Kei-keung Hung et al., IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 14, NO. 2, MARCH 2003, page(s): 413-425 [2] "Group Decision With Inconsistent Knowledge",Group Decision With Inconsistent Knowledge Peijun Guo et al., IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 32, NO. 6, NOVEMBER 2002, page(s): 670-679 [3] "Cost Functions and Model Combination for VaR-Based Allocation Using Neural Network",Cost Functions and Model Combination for VaR-Based Allocation Using Neural Network Nicolas Chapados et al., IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 12, NO. 4, JULY 2001, page(s): 890-906