Tori should buy approximately 40 shares of Company A and 58 shares of Company B to stay within her $15,000 budget, minimize risk, and achieve a revenue of at least $3500 annually.
Let's denote the number of shares of Company A as (x) and the number of shares of Company B as y. The total cost (C) and total revenue (R) can be expressed as follows:
![\[ C = 148x + 153y \]\[ R = 30x + 61y \]](https://img.qammunity.org/2024/formulas/mathematics/college/2fu781pxop3sq690u55ahqwtpnkhsgwgt0.png)
Tori's investment constraint is
, and she wants to obtain at least $3500 in annual revenue, so
. Additionally, Tori wants to minimize the risk, which is represented by the beta value. The beta values are 0.39 for Company A and 1.17 for Company B.
The optimization problem can be formulated as follows:
![\[ \text{Minimize } 0.39x + 1.17y \]\[ \text{Subject to } \begin{cases} 148x + 153y \leq 15,000 \\ 30x + 61y \geq 3500 \end{cases} \]](https://img.qammunity.org/2024/formulas/mathematics/college/i9w2og3lbh8id0vkulv5uxl341mumw6cyu.png)
Solving this linear programming problem will provide the optimal values for x and y, representing the number of shares Tori should buy from each company to meet her investment goals.
To find the optimal number of shares x and y\ that Tori should buy from each company to meet her investment goals, we can solve the linear programming problem:
![\[ \text{Minimize } 0.39x + 1.17y \]\[ \text{Subject to } \begin{cases} 148x + 153y \leq 15,000 \\ 30x + 61y \geq 3500 \end{cases} \]](https://img.qammunity.org/2024/formulas/mathematics/college/i9w2og3lbh8id0vkulv5uxl341mumw6cyu.png)
Using linear programming techniques, we find that the optimal values are
and
. However, since the number of shares must be whole numbers, Tori should round down to the nearest whole number (as you cannot buy a fraction of a share).
Therefore, Tori should buy approximately 40 shares of Company A and 58 shares of Company B to minimize risk, stay within her budget, and achieve her desired annual revenue.