Motivation: This post is about stock price modeling. People often says something like "the price is linked to the grouth and future expectations of a company". I'd like to convert these words into numbers and formulas, to understand things better.
Problem setting: Imagine you are seer (*) and you know the future of a company exactly: assets overtime a(t), liabilities overtime l(t), all cash in/out streams c(t), income overtime i(t) and all distributions amounts with dates d(t), etc. Imagine the company has 1000 shares and this number never changes. Imagine you don't know the future stock price, you know only the current price P_0
Question: How would you calculate the future stock price P(t) as a function of the know parameters above.
- I realize that the stock price may strongly depend on other company factors not listed above (brand value, visibility,...), or may depend on the probability distributions of the parameters, or may depend on parameters that are external to the company (GDP, probability of a viral pandemic where the company operates,...). Feel free to add/remove and use the parameters you think are the most important.
- I realize that there is no unique answer to the question. The stock price can have different models, some may be simple and not very accurate, others more complex and more accurate. I am interested in reasonably accuarte models.
- I realize that nobody can use these formulas because nobody knows the future, it is just to understand things.
(*) This is purely hypothetical and unrealistic, but I think it is an interesting prospective to understand how things work