What is the rear probability?

The rear probability measures the probability that the event will occur, given that the event has already occurred. This is a change in the original probability or probability without further information called previous probability. The probability of the back is calculated using Bayes' sentence. Financial modeling of stock portfolios is a common application of rear probability in finance. Sometimes it is difficult to accurately assign the probability of events, which limits the usefulness of the rear probability.

In order to calculate the probability of the rear part, a conditional probability of two dependent events can be examined. Let and be a target event, then P (a) is probability and priori. Let B be the second event that is dependent or related to the event A, the probability of P (b). Next, let the probability of an event B, since it occurs, P (b | a).

With Bayes' sentence, the rear probability of P (A | B) can be calculated. The theory of y:P (A | B) = p (b | a)*p (a) ⁄ _{p (b) . Note that if events A and B are independent, then their joint probability is P (A | B) = P (A). This means that their rear and previous probabilities are identical because the event B has no effect on the event A.}

The example of financing is the calculation of whether the stock price will increase, given that the interest rates have increased. Let and there will be that shares prices are rising and the probability that stocks will rise is 50% or P (A) = 0.50. Let B be that interest rates rise and the likelihood that stocks are growing is 75% or P (b) = 0.75. Finally, let the probability that interest rates will increase as stock prices will be 20% or P (b | a) = 0.20.

The probability that stock prices will increase as interest rate increases can be determined by involving these values ​​in Bayese. ProvideE P (A | B) =

0.20*0.50

⁄ 0.75 = 0.13 or 13%. This means that if interest rates are increasing, stock prices also have a 13% chance of growth, not a safe bet.

Financial analysts use many different types of events to analyze the relationships of many different types of events. Tin courses, changes in economic policy and consumer habits are examples of events that could affect stock prices. The probability that these events will occur is very difficult. Also, defining the impact that the event at the stock price can also be very demanding.