Quantitative methods Flashcards
Sharpe ratio
Effective Annual Rate (EAR)
Coefficient of Variation
It’s commonly used in finance to evaluate the risk per unit of return of an investment.
Roys safety first formula
Portfolio variance
Bayes’ Formula
Bayes’ Theorem (or Bayes’ Formula) is a fundamental result in probability theory that describes how to update the probabilities of hypotheses when given evidence.
Type 1 error
Rejecting a true null
Coefficient of Determination
Confidence interval for b1
Prediction interval (how to calculate sf as well)
sf= The estimated variance of the prediction error.
To develop the prediction interval, we use the following steps:
Predict the value of Y given the forecasted value of X.
Choose a significance level for the prediction interval.
Determine the critical value for the prediction interval based on the level of significance and degrees of freedom.
Compute the standard error of the forecast.
Compute the percent prediction interval for the prediction.
TSS (total sum of squares)
The sum of squares total (SST) or the total sum of squares (TSS) is the sum of squared differences between the observed dependent variables and the overall mean. Think of it as the dispersion of the observed variables around the mean—similar to the variance in descriptive statistics. But SST measures the total variability of a dataset, commonly used in regression analysis and ANOVA.
SSE (sum of the squares errors)
The sum of squares error (SSE) or residual sum of squares (RSS, where residual means remaining or unexplained) is the difference between the observed and predicted values.
RSS regression sum of squares
The sum of squares due to regression (SSR) or explained sum of squares (ESS) is the sum of the differences between the predicted value and the mean of the dependent variable. In other words, it describes how well our line fits the data.
Standard Error of the Sample Mean (σ unknown)
The Standard Error of the Mean (SEM) is a statistical measure that describes the accuracy with which a sample mean estimates the population mean. It’s fundamentally about understanding the variability or precision of the sample mean as an estimator of the true mean of the overall population.
Continuously Compounded Return (Find R)
Correlation
Joint Probability of Two Events
Probability of A or B- P(A or B)
Probability Stated as Odds (probability omformulerat till odds)
Future Value (FV) with continuous
compounding
Total Probability Rule
The Total Probability Rule is used in probability theory and finance when you need to calculate the probability of an event based on several distinct scenarios or conditions. This rule is particularly useful when you have a complex probability problem that can be broken down into simpler, mutually exclusive parts.
