Business, Legal & Accounting Glossary
Uncertainty is an inability to ascertain the true current state or to determine or predict future outcomes.
Uncertainty refers to a state where knowledge is minimal and nothing can be predicted about the future happenings or possible events. Unpredictable global economy along with imperfect markets has to lead to uncertainty in market behaviour. Economists have failed to predict the future due to lack of transparency in global market, which has to lead to a state where nothing can be forecasted regarding the future economy and this state in economics is termed as uncertainty.
Uncertainty is a state that always prevailed in an economy. There is always limited knowledge of market behaviour. If there had been a prior knowledge about the performance of the economy, then investors couldn’t make money in the secondary market.
Whenever any measurement is done with a certain number of data, a question always arises as to how authentic is the result of the measurement. Here lies an uncertainty as how far the result is true. Uncertainty is regarded as a consequence of random effects. Depending on the reasons that lead to uncertainty, various measures have been put forward. Standard deviation, probability measurement, game theory, and variance are the major measurements of uncertainty.
Standard deviation- a statistical measure of uncertainty of values can be expressed as
σ(SD) = √ {∑(x – ¯x )2/ (n-1) }
Where x = list of numbers for which standard deviation is to be calculated, ¯x = average of all the numbers, n = total numbers in the list
Probability measurement deals with the analysis of random effects. Probability measurement is based on discrete probability distribution or continuous probability distribution. The discrete probability distribution is represented by a set of values known as the sample set, which are possible outcomes of any future event.
Let X = { x1, x2……..} be the set of sample space such that x € X, this sample space is accompanied by a probability distribution, ƒ (x) that follows two properties as,
The continuous probability distribution is represented by a set of values that are continuous in nature. The sample-set here used is continuous ranging from negative infinity to positive infinity value. Thus, if F is the continuous probability distribution, then it is represented as
P (X ≤ x) = F (x), where X is a random variable that can be represented with a number of values. The continuous probability distribution satisfies certain properties like
Uncertainty should be avoided for any measurement. An appropriate assessment of uncertainty is considered as a superior professional practice. This can yield proper information about the eminence and dependability of the result.
Risk
Uncertainty is an inability to ascertain the true current state or to determine or predict future outcomes.
Uncertainty may involve risk, but uncertainty is more than risk. Risk is seen as measurable whereas that is not always true for uncertainty. Some people, such as Frank Knight, author of Risk, Uncertainty, and Profit, draw a distinction between risk and uncertainty whereby uncertainty is restricted to only those cases where probability of outcomes are immeasurable. While the distinction between measurable and immeasurable probabilities for outcomes is useful, this is not strictly speaking correct. Uncertainty can sometimes be measurable. If it involves loss, than uncertainty will include risk. However, if there is no possiblity of loss, there is no risk.
One further distinction should be made between risk and uncertainty in that, unlike risk, uncertainty can include profitable outcomes. Risk is concerned only with situations for which there may be unprofitable outcomes or loss.
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This glossary post was last updated: 28th November, 2021 | 0 Views.