18 hasil pencarian dengan kata kunci: 'cfa 2018 ss 03 reading 10 common probability distributions'
• On an unlimited (infinite) number of outcomes i.e. For example, time, weight, distance, rate of return etc. The range of possible outcomes of a continuous random variable is
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Random variable: A variable that has uncertain outcomes is referred to as random variable e.g. the return on a risky asset. Event: An event is an outcome or a set of outcomes of a
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LO.m: Define the standard normal distribution, explain how to standardize a random variable, and calculate and interpret probabilities using the standard
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• The security is being sold by market participants at the same price level over a period of time resulting in an end to uptrend. • However, the buyers are becoming more and more
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Parametric test: A parametric test is a hypothesis test regarding a parameter or a hypothesis test that is based on specific distributional assumptions. • Parametric tests
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• Sampling should not be done from more than one distribution because when random variables are generated by more than one distribution (e.g. combining data collected from a period
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The CLT: states that for a population with mean µ and variance σ , the sampling distribution of the sample means for any sample of size n will be approximately normally
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The central limit theorem tells us that for a population with a mean µ and a finite variance σ , the sampling distribution of the sample means of all possible samples of size n
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Value at risk (VAR) ⇒ minimum value of losses (in money terms) expected over a specified time period at a specified level of probability. Stress testing/scenario analysis ⇒ use
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only projects with expected return > cost of the capital (required return) will increase the value of the firm. • Financing costs are not included in the cash flows; because
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