CAIA Chapter 3: Statistical Foundations
Statistical Foundations
Statistical Foundations
Fichier Détails
Cartes-fiches | 43 |
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Langue | English |
Catégorie | Finances |
Niveau | Université |
Crée / Actualisé | 17.12.2014 / 16.06.2019 |
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Shortfall risk
is simply the probability that the return will be less than the investor's target rate return.
Target semivariance
is similar to semivariance except that target semivariance substitutes the investor's target rate of return in place of the mean return.
Target semistandard deviation
is simply the square root of the target semivariance
Tracking error
indicates the dispersion of the returns of an investment relative to a benchmark return, when a benchmark return is the contemporaneous realized return on an index or peer group of comparable risk.
Drawdown
is defined as the maximum loss in the value of n asset, usually in percentage return form rather than currency
Value at Risk (VaR or VAR)
is the loss figure associated with a particular percentile of a cumulative loss function. VaR is the maximum loss over a specified time period within a specified probability.
Conditional vale-at-risk (CVaR)
aka, expected tail loss. Is the expected loss of the investor, given that VaR has been equaled or exceeded. Provides the investor with information about the potential magnitudes of losses beyond VaR
Monte Carlo analysis
is a type of simulation in which very many potential paths of the future are projected using an assumed model and the results are analyzed as an approximation to the future probability distribution. It is used in difficult problems (no expected values etc
heteroskedasticity
is when the variance of a variable changes
Homoskedasticity
is when the variance is constant
autoregressive
is when subsequent values to a variable are explained by past values of the same variable
Conditionally heteroskedastic
financial asset that have different levels of return variation even when the conditions are similar, for example, when viewed at similar price levels
GARCH generalized autroregressive conditional heteroskedasticity:
in the context of financial returns GARCH is a robust methodology that can model return variation through time in a way that allows that variation to change based on the variable's past history &even when some conditions such as price levels havn't chang
return computation interval
for a particular analysis is the smallest time interval for which returns are calculated, such as daily, monthly or even annually.
Volatility
in investment terminology, the standard deviation of returns is often termed the volatility.
histogram
a graphical representation of a frequency distribution
Ex Ante
Future possible returns and their probabilities are referred to as ex ante or expectational return probability distributions
Ex Post
meaning from forwards. based on realized outcomes rathern than anticipated outcomes
normal distriution
is the familiar bell-shaped distribution that is also known as Gaussian distribution. The normal distribution tends to approcimate many distributions observed in nature and/or generated as the result of human actions and interactions, incl. financial retu
Compounding
is the recognition of interest on interest or, more generally, earning on earnings
Simple interest
A computation that does not incorporate compounding
Continuous compounding
assumes that earning can instantaneously be reinvested to generate additional earnings
Discrete compounding
any compounding interval other than continuous compounding is known as discrete compounding
Log returns
the mathematics of returns can be simplified by expression returns as continuously compounded rates
arithmetic mean log return
when the arithmetic mean log return is converted into an equivalent simple rate that rate is referred to as the geometric mean return
lognormal
a variable has a lognormal distribution if the distribution of the logarithm of the variable is normally distributed
autocorrelation
referres to the possible correlation of the returns with each other. first-order autocorrelation refers to the correlation between returns in time period t and the return in the previous time period t-1. Positive when moving in the same direction
When are some returns markedly nonnormal?
Autocorrelation, Illiquidity, Nonnormality
Illiquidity
many alternative investments are thinly traded. Observed market prices might therefore be heavily influenced by the liquidity needs of the market participants rather than driven toward an efficient price by the actions of numerous well-informed buyers/Sel
Nonlinearity
e.g. short-term call option: the dispersion in the call option's return distribution changes through time as the underlying assets's price changes, even if the volatility of the underlying asset remains constant
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