Statistical & Quantitative Methods Flashcards
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Read the first 7 Statistical & Quantitative Methods flashcards as text
What does a Pearson correlation coefficient of -1.0 between two assets indicate?
Answer: A perfect negative linear relationship between the assets
A correlation coefficient of -1.0 indicates a perfect negative linear relationship, meaning the two assets move in exactly opposite directions.
Which statistical measure is used to construct Bollinger Bands around a moving average?
Answer: Standard deviation
Bollinger Bands are constructed by adding and subtracting a specified multiple of the standard deviation from a simple moving average.
In a normal distribution, approximately what percentage of data falls within two standard deviations of the mean?
Answer: 95%
By the empirical rule, approximately 95% of data in a normal distribution falls within two standard deviations of the mean.
What does R-squared (R²) measure when linear regression is applied to price data?
Answer: The proportion of price variance explained by the regression model
R-squared, the coefficient of determination, measures the proportion of variance in the dependent variable (price) that is explained by the independent variable(s) in the model.
What does a Z-score tell a technical analyst about a data point?
Answer: How many standard deviations the data point lies above or below the mean
A Z-score measures how many standard deviations a data point is from the mean, allowing analysts to identify statistically unusual price levels.
What is the primary purpose of applying a moving average to price data?
Answer: To smooth price fluctuations and identify the underlying trend direction
Moving averages smooth short-term price fluctuations to reveal the underlying trend direction of a security over the chosen period.
In time series analysis of price data, what does autocorrelation measure?
Answer: The correlation between a time series and a lagged version of itself
Autocorrelation measures the correlation between a time series and its own past values at specified lag intervals, helping analysts assess price persistence.