Suppose we hold a stock at our portfolio and going to decide whether we should sell it or buy more in the following 5 days. We know that at the after 5 day of trading there will be $5 dividend for each unit of stock we are holding at our portfolio. However, holding one unit of stock at our portfolio costs $1 to us, and there is no transaction cost of selling and buying. Due to restrictions, we can hold at most 5 stocks. Suppose we believe that price of the stock is equally likely to be 2, 3, 4, or 5. Create a Python program that maximizes your profits from trading the commodity over the next 5 days.

Total marketing effort is a term used to describe the critical decision factors that affect demand: price, advertising, distribution, and product quality. define the variable x to represent total marketing effort. a typical model that is used to predict demand as a function of total marketing effort is based on the power function: d = axb suppose that a is a positive number. different model forms result from varying the constant b. sketch the graphs of this model for b = 0, b = 1, 0< b< 1, b< 0, and b> 1. (we encourage you to use excel to do this.) what does each model tell you about the relationship between demand and marketing effort? what assumptions are implied? are they reasonable? how would you go about selecting the appropriate model?