14-09-2017, 02:21 PM
A probability distribution is a statistical function that describes all possible values and probabilities that a random variable can take within a given range. This interval will be between the statistically possible minimum and maximum values, but where the likely value is likely to be plotted in the probability distribution depends on a number of factors. These factors include the mean of the distribution, the standard deviation, the asymmetry and the kurtosis.
Academics and fund managers alike can determine the probability distribution of a particular action to determine the potential returns that the action may generate in the future. The return history of the stock, which can be measured at any time interval, will probably consist only of a fraction of the stock yields, which will lead to analysis of the sampling error. By increasing the size of the sample, this error can be drastically reduced.
There are many different classifications of probability distributions. Some of them include the normal distribution, the chi-square distribution, the binomial distribution, and the Poisson distribution. The different probability distributions serve different purposes. The binomial distribution, for example, evaluates the probability that an event occurs several times in a given number of trials and given the probability of the event in each trial. The usual example would use a fair coin and calculate the probability that that coin would raise heads in ten straight strokes.
The most common distribution is the normal distribution and is frequently used in finance, investment, science and engineering. The normal distribution is characterized by its mean and standard deviation, which means that the distribution is not biased and does present kurtosis. This makes the distribution symmetrical and is represented as a bell-shaped curve when plotted.
Academics and fund managers alike can determine the probability distribution of a particular action to determine the potential returns that the action may generate in the future. The return history of the stock, which can be measured at any time interval, will probably consist only of a fraction of the stock yields, which will lead to analysis of the sampling error. By increasing the size of the sample, this error can be drastically reduced.
There are many different classifications of probability distributions. Some of them include the normal distribution, the chi-square distribution, the binomial distribution, and the Poisson distribution. The different probability distributions serve different purposes. The binomial distribution, for example, evaluates the probability that an event occurs several times in a given number of trials and given the probability of the event in each trial. The usual example would use a fair coin and calculate the probability that that coin would raise heads in ten straight strokes.
The most common distribution is the normal distribution and is frequently used in finance, investment, science and engineering. The normal distribution is characterized by its mean and standard deviation, which means that the distribution is not biased and does present kurtosis. This makes the distribution symmetrical and is represented as a bell-shaped curve when plotted.