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Superviser: Professor Moisă Altăr MSc Student: George PopescuPowerPoint Presentation

Superviser: Professor Moisă Altăr MSc Student: George Popescu

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### Scheme

### Davidson and Duclos (2000) demonstrate that the SSD condition can be written as:

### Interpretation of SSD condition in terms of poverty gap function:

### The put payoff - like utility function: function:

### The OMD function:

### The equivalent margin can be written as a weighted average of OMD’s

### Interpretation: of OMD’s

### Testing for SSD of OMD’s

### OMD for of OMD’sr with R as benchmark:

### The estimated equation: of OMD’s

### Initial (gross) regression equation (34 regressors): of OMD’s

### COMPUTATION OF OMD of OMD’s

### Did the fund SSD the benchmark? over the market, though there were points where the fund return was less than the benchmark returnInverting the benchmark:

### VUAN and IFM series: non-stationary over the market, though there were points where the fund return was less than the benchmark return

ACADEMY OF ECONOMIC STUDIESDOCTORAL SCHOOL OF FINANCE-BANKINGORDERED MEAN DIFFERENCE AND STOCHASTIC DOMINANCE AS PORTFOLIO PERFORMANCE MEASURESwith an approach to cointegration

Superviser: Professor Moisă Altăr

MSc Student: George Popescu

• THE EQUIVALENT MARGIN

• THE OMD. UTILITY FUNCTION AND POVERTY GAP FUNCTION.

• STOCHASTIC DOMINANCE

• THE ECONOMETRIC MODEL

• EMPIRICAL APPLICATION

THE EQUIVALENT MARGIN

- r: fund return
R: benchmark return

t: penalty levied on the fund return

x: investment in fund

- investor’s decision problem:

The OMD(Bowden, 2000)

= the special case when, in the equivalent margin formula, the utility function has the form of a put pay-off

Motivation for this kind of utility function

- Investor is interested in obtaining a target return P, being indifferent to values of R in excess of P and negatively exposed if the return falls below the target
- P- established according to his appetite for risk
- exactly the converse of the poverty gap function (Davidson and Duclos, 2000)
- idea from Merton (1981) and Henriksson and Merton (1981)

A and B: two random variablesA second order stochastically dominates (SSD) B up to a poverty line z if:

The Poverty gap function:

The average poverty gap in B (the dominated distribution) is greater than in A (the dominant distribution) for all poverty lines less than or equal to z. There is a longer way from the actual level of income B to the poverty threshold than from the actual level of A to the same poverty threshold.

The poverty gap function:

So: this kind of utility function shows how far we are from the poverty threshold, after we surpassed the threshold

Introducing the utility function in the equivalent margin formula gives:

OMD = the average area between the regression curve of the fund return on the benchmark return and the benchmark return itself, taken on the Ox axis

If t(P)>0 for all P, then the fund was superior to the benchmark

(for all P)

- each investor can be seen as a spectrum of elementary investors (“gnomes” as named by Bowden), each having a put option profile utility function, but differing by the “strike price” (P), which represents the degree of aversion to risk (P moves to the right as the aversion to risk decreases)

tU: independent of the degree of aversion to risk

or, in terms of the poverty gap function:

OMD for R with r as benchmark:

THE ECONOMETRIC MODEL of OMD’s

- Using the Forsyhte polynomials, transform the initial regression of the fund return on the benchmark return into a regression of the fund return on a set of regressors whose matrix is orthogonal
- the benchmark: divided into several indexes
- insures of non-multicollinearity between independent variables

The Forsythe polynomials: of OMD’s

The estimated values for OMD [t(P)]

EMPIRICAL APPLICATION of OMD’s

- Data:
- r: Capital Plus return (VUAN series)
- R:mutual fund index return (IFM series)

- Period:
- 3 January 2000 - 1 April 2002

- Frequency:
- weekly

- Number of observations:
- 118

Only the significant regressors maintained in terms of t-Statistic (p-values <0.05):

Verifying the OLS presumptions: of OMD’s

Stationarity of residuals of OMD’s

- series sorted in ascending order after the IFM values

Interpretation: of OMD’s

- OMD positive for every realisation of the benchamark the fund was superior (OMD dominant) to the benchmark and preferred by every risk averse investor, no matter his degree of aversion to risk (because if OMD is positive, then the equivalent margin, which is a weighted average of OMD’s, is also positive)

- Preferred by both less and more risk averse investors of OMD’s
- a downward trend the more risk averse investors prefer more than the less risk averse investors the fund
- the fund added utility to both less and more risk averse investors, but the more risk averse ones appreciate more the utility given by the fund than the less risk averse investors.

OMD: the average area between the regression of the fund return on the benchmark return

- The area is always positive the fund was OMD dominant over the market, though there were points where the fund return was less than the benchmark return
- Inconvenient: the first values for OMD are computed using few values
- Remedy: Baysian approach; I tried implement the exponentially weighted OMD (EWOMD), which gives less weighting to the first values

The regression to be estimated:

Verifying the OLS presumptions: over the market, though there were points where the fund return was less than the benchmark return

The OMD for IFM over the market, though there were points where the fund return was less than the benchmark return

Interpretation: over the market, though there were points where the fund return was less than the benchmark return

- OMD is not negative for all the fund return values the fund did not SSD the market (represented by the benchmark)
- not always the poverty gap was less for the fund than for the benchmark
- the fund SSD the benchmark only for the greater values of the fund returns the fund was preferred especially by the more risk averse investors (who fix lower levels they wish the fund to attain)

AN APPROACH TO COINTEGRATION over the market, though there were points where the fund return was less than the benchmark return

- both the OMD measure and the cointegration theory describe long run behaviour
- the fund is allowed to have temporary fall below the benchmark, but these falls do not affect the overall conclusion if the long run behaviour indicates the superiority of the fund
- Does exist a cointegration relation between VUAN and IFM that verifies the superiority of the fund?

VAR(3) system

VAR(3) and not VAR(2) because of: over the market, though there were points where the fund return was less than the benchmark return

- LR test
- Akaike and Schwartz
- lack of autocorrelation of residuals

Apply the Johansen test to find a cointegrating relation: over the market, though there were points where the fund return was less than the benchmark return

- The dominance of the fund in terms of OMD verified by the cointegrating relation

Remained to be developed: over the market, though there were points where the fund return was less than the benchmark return

- Computation of OMD (the first values: computed using few values) - Baysian approach, EWOMD
- equivalent margin - martingale measures

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