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Application of Constraints and Fuzzy Measures in Finance Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

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Page 1: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Application of Constraints and Fuzzy Measures in FinanceTanja Magoč, François Modave, Xiaojing Wang, and Martine CeberioComputer Science DepartmentThe University of Texas at El Paso

Page 2: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Outline

Problems in the area of finance Portfolio selection

Current techniques for portfolio selection

Utility based decision making Use of fuzzy measures Use of constraints Use of intervals

Page 3: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Problems in the area of finance

Numerous problems in the area of finance use computation techniques Data mining Option pricing Selection of optimal portfolio

Page 4: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Portfolio selection

Portfolio: a distribution of wealth among several investment assets

Problem: select optimal portfolio Goal:▪ Maximize return for a given acceptable level of risk▪ Minimize risk to obtain required level of return

Constraints:▪ Minimal required return▪ Maximal acceptable risk▪ Time horizon▪ Transaction cost▪ Preferred portfolio structure▪ etc.

Page 5: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Simple formalization of the problem

maximize (minimize) subject to

Goal: find the vector

m

iiixw

1

),...,( 1 mwww

m

iii

m

iii

m

ii

i

returnRw

riskrw

w

w

1

1

1

1

0

Page 6: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Existing techniques

Return-based strategies Methods involving stochastic

processes Intelligent systems techniques

Genetic algorithms Rule-based expert systems Neural networks Support vector machines

Page 7: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Drawbacks of the existing techniques

Learn from examples: Overfitting data

Ignore relationships among characteristics of an asset: Higher risk usually implies higher return Longer time to maturity usually leads to

higher risk Assume precise data:

Return expected by an investor Return and risk associated with an asset

Page 8: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Tools for a novel approach

Multi-criteria decision making Fuzzy measure and fuzzy integration:

Take care of dependence among characteristics

Intervals: Take care of imprecise data

Page 9: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Multi-criteria decision making Comparison of multidimensional alternatives

to select the optimal one Pick the best stock for investment

Elements of a MCDM setting: a set of alternatives

stocks (finitely many) a set of criteria

return, time to maturity, reputation of company a set of values of the criterion

return=[0,50], time={1,2,3}, reputation={bad, average, good}

a preference relation for each criterion Challenge: Combine partial preferences into

a global preference

Page 10: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Utility function

Utility function is a transformation from an ordered set to a set of real numbers

Construct a utility function for each criterion that maps values of all criteria to a common scale

Combine monodimensional utilities into a global utility function using an aggregation operator. How?

Page 11: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Combining monodimensional utilities

Maximax approach Optimistic situation

Maximin approach Pessimistic situation

Weighted sum approach Advantage: simple to calculate, O(n) Disadvantage: ignores the dependence

among criteria▪ Longer time to maturity higher return

Page 12: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Non-additive (fuzzy) measure in a finite case

is called a non-additive measure if

(i) (ii) (iii) if

: ( ) [0,1]P I

( ) 0 ( ) 1I ( ) ( )B C )(IPCB

Page 13: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Fuzzy integration: the Choquet integral

Decision maker inputs value of importance of each subset of the set of criteria

The Choquet integral is an aggregation operator evaluated w.r.t. a non-additive measure, which is defined by the values of importance of (subsets of) criteria

Drawback: exponential complexity

Page 14: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

2-additive measure

A non-additive measure where all interaction indices of order 3 and higher are null, and at least one interaction index of order 2 is not null.

Advantages of using 2-additive measure: Lower complexity than non-additive

measure Takes into consideration dependence

among criteria

Page 15: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

The Choquet integral w.r.t. a 2-additive measure

The Choquet integral w.r.t. a 2-additive measure:

Decision-maker inputs the importance of each attribute and the importance of each pair of attributes

I

n

i jiiji

Iij

Iij IIifIjfifIjfiffdC

ijij 100

||2

1||)(

Page 16: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Advantages and drawbacks of 2-additive approach

Advantages: Considers the interactions among

attributes Quadratic complexity

Drawback: Imprecise values of importance and

interaction indices

Page 17: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Intervals

A real interval is a closed and connected set of real numbers

Calculate the Choquet integral w.r.t. a 2-additive measure over intervals

xx,

Page 18: Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso

Conclusion

Present a feasible computation approach in portfolio selection, combining interval values with 2-additive fuzzy measures and integrals.