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Prince Modi
Prince Modi

Reputation: 495

Implementing Excel Solver in R

I am trying to implement an Excel Solver in R.

I have two vectors of weights. Old_Weights and New_Weights. I need to find New_Weights.

Objective Function: Max ( (Returns - Cost) / Risk)

Example:

Old_Weights<-c(0.5,0.5,0)
New_Weights<-c(X,Y,Z)

Returns <- New_Weights * Market_Returns
Cost<- (New_Weights - Old_Weights) * 15
Risk <- t(New_Weights) * Var(Market_Returns) * New_Weights

So basically I need a function that would change the values of X,Y,Z that maximizes the Objective Function.

Upvotes: 1

Views: 955

Answers (1)

yixi zhou
yixi zhou

Reputation: 297

You can use The optim() function in R to compute this.

The general format for the optim() function is optim(objective, constraints, bounds = NULL, types= NULL, maximum = FALSE)

You can first write a function including your parameters, for example, 

> f <- function(x) 15 * (x[1]-0.5) + 7 * (x[2]-3)^2 + 30

Setting up the constraints next

> c <- c(1, 1)

Then use optim(c, f) to get the optimized solution

> r <- optim(c, f)

> r

Upvotes: 2

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