GARP Financial Risk Manager (FRM) Part 1 Practice Exam 2025 – The Complete All-in-One Guide to Exam Success!

Question: 1 / 400

In probability theory, what does the Poisson Distribution formula represent?

p(x) = n!/[(n-x)! * x!]*p^x*(1-p)^(n-x)

p(x) = E(Rp- Rb)/Tracking Error

p(x) = [lambda^x*e^(-lambda)]/X!

The Poisson Distribution formula represents the probability of a given number of events happening in a fixed interval of time or space under the assumption that these events occur with a known constant mean rate and independently of the time since the last event. The correct formula, represented as \( p(x) = \frac{\lambda^x e^{-\lambda}}{x!} \), where \( \lambda \) is the average rate of occurrence over the specified interval, \( x \) is the actual number of events, and \( e \) is the base of the natural logarithm, encapsulates these core elements of the distribution.

This distribution is typically used in scenarios where events happen randomly but at a predictable average rate, such as the number of phone calls received at a call center in an hour or the number of emails received in a day, therefore making it particularly useful in fields involving risk management and statistical modeling.

The other choices do not represent the Poisson Distribution: the first choice corresponds to the binomial distribution, which models the number of successful outcomes in a fixed number of trials with two possible outcomes; the second choice refers to a formula used for measuring tracking error in finance, which is not related to the Poisson distribution at all; and the

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Pi(u) = [e^(r*t)-d]/(u-d)

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