So far we have looked at a lot of Mathematical concepts, let try to apply it to something other than a coin. We will try go through a Binomial Tree model, and try to apply it for a Stock.
So, the Stock will start at a price at , we assume that with probability it goes up by a factor of and that it goes down with probability by a factor of .
Thus the Stock at ( which we will denote by ) can be represented by with probability and with probability
Now if we keep repeating the same experiment at each node we end up with something like
In this manner we can keep continuing the experiment, but for now, lets stick to a total of time steps i.e at the end
So, what can we do with a binomial model ? Well we can compute the probability of each stock price node at each step.
At step for example - and at say step we have a few more states, , and so on.
We can also compute things like, what is the Expected value of a stock at each time step. At we have
Not only this, but the binomial model also adjusts to given information. What it means is that if you know where you are at step 1, the probabilities are now different! How does that happen? Well there is one more thing that changes as the time steps grow, that is the Filtration.
When we write we actually mean where is the given filtration at the step.
So say at step we now the probability of is but that is not correct, the correct way to say it is given no information i.e the probability is , but if we knew where the stock ends up at step one i.e the probabilities change accordingly. So if say the Stock went up to at step 1.
Thus, once we create a binomial model for a Stock, we can
- Tell the probability of each point of Stock - Time on tree
- Compute the expected value of the Stock at each Time Step
- Amend the Tree probabilities as we get more information
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