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CFA II > Quantitative Methods > Flashcards

Quantitative Methods Flashcards

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CFA flashcards
1
Q

What are the two formulas for R Squared?

A

R sq = Correlation Squared

R sq = RSS / SST

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2
Q

What is the formula to calculate the t-stat for the correlation coefficient?

A

t = (r√n-2) / (1-r2)

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3
Q

What does R Squared represent?

A

R squared represents the amount of variation in the dependent variables accounted for by an independent variable.

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4
Q

Does regression analysis assume that:

a) The independent variable is uncorrelated with the residuals.
b) The dependent variable is uncorrelated with the residuals.

A

It only assumes that the Independent Variable is uncorrelated with the residuals.

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5
Q

For a single-factor regression model, how many degrees of freedom does the critical T for calculation of a confidence interval for:

a) A parameter estimate.
b) A “Y-Value” estimate.

A

2 degrees of freedom for both.

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6
Q

What are the formulas for Mean Squared Regression and Mean Squared Error?

A

MSR = RSS/ df

MSE = SSE/ df

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7
Q

What is the formula for Standard Error of the Estimate?

A

SEE = √MSE

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8
Q

What is the formula for F-Stat?

A

F-Stat = MSR/MSE

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9
Q

What is the formula for calculating a confidence interval?

A

Confidence Interval = Coefficient Estimate +/- (Critical T)(Standard Error)

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10
Q

What is the formula for calculating t-stat for a parameter?

A

T-Stat = (Coefficient Estimate - Value to Compare) / Standard Error

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11
Q

What is spurious correlation?

A

Spurious correlation is when there there appears to be a statistical correlation between variables, but no actual relationship exists.

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12
Q

How many degrees of freedom does the regression have?

A

k degrees of freedom.

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13
Q

How many degrees of freedom does the error have?

A

n - k - 1 degrees of freedom.

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14
Q

How should the upper and lower Durbin-Watson values be used to determine whether to accept or reject the null hypothesis.

A

0 - Lower = Reject H0; Positive serial correlation exists

Lower - Higher = Inconclusive

> Higher = Do not reject H0

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15
Q

Would failing to include a variable that affects the dependent variable lead to misspecification?

A

Yes.

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16
Q

Would using actual inflation as a proxy for expected inflation lead to misspecification?

A

Yes.

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17
Q

Would using a lagged variable lead to misspecification?

A

Yes.

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18
Q

How will be the coefficients be when a model is misspecified?

A

Biased and inconsistent.

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19
Q

What is the solution to serial correlation?

A

Use Hansen method to adjust the standard errors.

20
Q

What should all qualitative variables be tested for?

A

Heteroskedasticity, Serial Correlation and Multi-Collinearity.

21
Q

What is a potential solution when a time series has a unit root?

A

Model the first differences, as these usually do not exhibit a unit root.

22
Q

What is a trend model?

A

A model in which the independent variable is time (t).

23
Q

When is a loglinear model used?

A

When a time series grows at a constant rate.

24
Q

What does covariance stationary mean?

A

That the time series will be mean-reverting.

25
Q

How is annual seasonal lag of quarterly returns?

a) By adding a t-4 parameter
b) By adding a t-12 paramater
c) By adding both

A

By adding a t-4 parameter.

26
Q

How do you know if a time series is a random walk?

A

It has a unit root.

27
Q

What is the null hypothesis of the Dickey-Fuller/ Engle-Granger test?

A

That the time series has a unit root/ is nonstationary.

28
Q

Does the Dickey-Fuller test use conventional or adjusted:

a) t-statistics
b) Criticial t-values

A

The Dickey-Fuller test uses a conventional t-statistic but compares it to adjusted critical t-values.

29
Q

What does a 4th autocorrelation need to differ significantly from for a model to exhibit seasonality?

A

Zero.

30
Q

What is Autoregressive Conditional Heteroskedasticity (ARCH).

A

When an error is correlated with a lagged error.

31
Q

What will the R2 and coefficient t-stats be if multicollinearity is present?

A

High R2 and insignificant t-stats.

32
Q

How does historical simulation estimate VaR?

A

It uses actual returns and takes the 5th percentile.

33
Q

What is the formula for VaR?

A

VaR = Mean Return - (Critical T * Standard Deviation)

34
Q

How do you adjust annual standard deviation (volatility) in VaR to calculate daily standard deviation?

A

Daily SD = Annual SD / √No. Of Days

Note the square root of days, not the no. of days.

35
Q

What is maximum drawdown?

A

The worst drop in performance from peak to trough, or the worst historical performance in a period.

36
Q

How many degrees of freedom are there when determing the critical t-stat?

A

N - K - 1 degrees of freedom.

37
Q

What is the general limit for a t-stat to be significant?

A

Greater than 2.

38
Q

What is serial correlation?

A

When there is correlation between regression errors.

39
Q

What is heteroskedasticity?

A

When the variance of errors is not constant, and is related to the independent variables.

40
Q

What is reverse stress testing?

A

Creating a hypothetical event that would affect a company’s top exposure at the same time.

41
Q

What is the test for heteroskedasticity and what part of the regression does it test?

A

The Breusch-Pagan Chi Squared test is carried out on the R-Squared

42
Q

What part of the regression does the Hansen method adjust?

A

The standard errors.

43
Q

What are the two steps to test for ARCH?

A
  1. Square the residuals.

2. Regress the squared residuals against squared residuals from previous periods.

44
Q

What is the formula for the standard error of the autocorrelation?

A

1 / √n

45
Q

If a regression covers periods that should have their own regressions, what type of misspecification is this?

A

Functional form misspecification.

46
Q

What do unbiased and consistent mean?

A

Unbiased means the sample is representative of the population.

Consistent means that as the sample size increases, the estimate gets closer to the population.

CFA II (11 decks)

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