Quantitative Methods and Statistics Flashcards

What is the primary purpose of a Monte Carlo simulation in alternative investment portfolio analysis?

Answer: To model the distribution of possible future outcomes through repeated random sampling

Monte Carlo simulation generates thousands of random scenarios based on specified return and risk parameters, producing a distribution of possible outcomes useful for stress-testing and portfolio planning.

Conditional Value at Risk (CVaR), also known as Expected Shortfall, is best described as:

Answer: The average loss in scenarios where losses exceed the VaR threshold

CVaR (Expected Shortfall) answers the question 'given that we are in the tail beyond VaR, what is our expected loss?' — making it a more complete tail-risk measure than VaR alone.

In a linear regression of portfolio returns on a benchmark, the R-squared (R²) statistic measures:

Answer: The proportion of portfolio return variance explained by the benchmark

R² indicates how much of the variation in the dependent variable (portfolio returns) is captured by the independent variable (benchmark returns); a high R² means benchmark moves largely explain portfolio moves.

Which statistical test is commonly used to assess whether investment return data follows a normal distribution?

Answer: Jarque-Bera test

The Jarque-Bera test uses the skewness and excess kurtosis of a dataset to test the null hypothesis of normality, making it well-suited for evaluating return distributions.

Tracking error is most precisely defined as:

Answer: The standard deviation of the difference between portfolio returns and benchmark returns

Tracking error is the annualized standard deviation of active returns (portfolio return minus benchmark return), measuring how consistently a manager deviates from the benchmark.

The Sortino ratio improves upon the Sharpe ratio for alternative investments by:

Answer: Using downside deviation (volatility of negative returns only) in the denominator

The Sortino ratio replaces total standard deviation with downside deviation (semi-deviation), penalizing only downside volatility and therefore better capturing the asymmetric return profiles common in alternatives.

In a multi-factor regression model, Jensen's alpha represents:

Answer: Portfolio return in excess of what the factor model predicts given the portfolio's risk exposures

Alpha is the intercept term in a factor regression, capturing average return attributable to manager skill or unmodeled sources after stripping out all systematic factor exposures.