Version:

Sharpe : Sharpe model.

**Description**

Sharpe.gms: Sharpe model. Consiglio, Nielsen and Zenios. PRACTICAL FINANCIAL OPTIMIZATION: A Library of GAMS Models, Section 3.3 Last modified: Apr 2008.

**Category :** GAMS FIN library

**Mainfile :** Sharpe.gms **includes :** Estimate.gdx

```
$TITLE Sharpe model
* Sharpe.gms: Sharpe model.
* Consiglio, Nielsen and Zenios.
* PRACTICAL FINANCIAL OPTIMIZATION: A Library of GAMS Models, Section 3.3
* Last modified: Apr 2008.
SET Assets;
ALIAS(Assets,i,j);
PARAMETERS
RiskFreeRate
ExExpectedReturns(i) Excess Expected returns
ExVarCov(i,j) Variance-Covariance matrix of the excess returns;
$GDXIN Estimate
$LOAD Assets=subset RiskFreeRate=MeanRiskFreeReturn ExVarCov=ExcessCov
$LOAD ExExpectedReturns=MeanExcessRet
$GDXIN
POSITIVE VARIABLES
x(i) Holdings of assets;
VARIABLES
PortVariance Portfolio variance
d_bar Portfolio expected excess return
z Objective function value;
EQUATIONS
ReturnDef Equation defining the portfolio excess return
VarDef Equation defining the portfolio excess variance
NormalCon Equation defining the normalization contraint
ObjDef Objective function definition;
ReturnDef .. d_bar =E= SUM(i, ExExpectedReturns(i) * x(i));
VarDef .. PortVariance =E= SUM((i,j), x(i) * ExVarCov(i,j) * x(j));
NormalCon .. SUM(i, x(i)) =E= 1;
ObjDef .. z =E= d_bar / SQRT( PortVariance );
* Put strictly positive bound on Variance to keep the model out of trouble:
PortVariance.LO = 0.001;
MODEL Sharpe /ReturnDef, VarDef, NormalCon, ObjDef/;
SOLVE Sharpe MAXIMIZING z USING nlp;
* Use the optimal sharpe ratio to build an efficient frontier.
* In this case the frontier is described by a line
* whose slope is the sharpe ratio, and the intercept equal to the benchmark return.
* The scalar "theta" determines the
* amount invested in the tangency portfolio. When theta is less than
* 1, part of the capital is invested at the benchmark rate. When theta is greater
* than 1, the investor is borrowing at the benchmark rate and invest the
* proceeds in the tangency portfolio. (We are assuming that the benchmark
* is the risk free, therefore its variance is zero.
SCALARS
theta Fraction of the wealth invested in the market portfolio
CurrentPortVariance Variance of the current portfolio
CurrentPortReturn Return of the current portfolio;
FILE SharpeHandle /"SharpeFrontier.csv"/;
SharpeHandle.pc = 5;
PUT SharpeHandle;
PUT "Standard Deviations","Expected Return","Theta"/;
FOR ( CurrentPortVariance = 0 TO 1 BY 0.1,
theta = SQRT ( CurrentPortVariance / PortVariance.L );
CurrentPortReturn = RiskFreeRate + theta * d_bar.L;
PUT SQRT(CurrentPortVariance):6:5, CurrentPortReturn:6:5, theta:6:5/;
);
* Also plot the tangent portfolio
theta = 1;
PUT SQRT(PortVariance.L):6:5,(RiskFreeRate + theta * d_bar.L):6:5,theta:6:5/;
PUTCLOSE;
```