22 votes
Accepted

Why and when we should use the log variable?

Based on your paper and variables, I assume you ask about the use in econometric models. There are some rules of thumb for taking logs (do not take them for granted). See for example Wooldrigde: ...
AKdemy's user avatar
  • 9,059
21 votes
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Fama-Macbeth second step confusion

Then for each month $t$, you run a cross-section regression: $r_{i,t} = \lambda_0 + \hat{\beta}_i {\lambda}_t + \alpha_{i,t}$ Where: $\hat{\beta}_i \equiv [\beta_{i, MktRf}, \beta_{i, SMB}, \beta_{i,...
phdstudent's user avatar
  • 8,061
14 votes
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Calculating alpha and its meaning

Alphas from a time-series regression are error terms in the cross-sectional, linear relationship between expected returns and factor betas. If a factor model were correct those error terms (the alphas)...
Matthew Gunn's user avatar
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13 votes

Choosing the right statistical test for Mutual Fund Performance Evaluation

Define excess return $r^x_{it} = r_{it} - r^f_{t}$ as the return $i$ minus the risk free rate, and $f_{jt}$ similarly denotes the excess return of factor $j$ at time $t$. Let's say we have some factor ...
Matthew Gunn's user avatar
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12 votes

Fama-Macbeth second step confusion

The two step Fama-Macbeth regression works as follows: First, run a cross sectional regression in each period. I believe that you want to estimate risk premia for each of the Fama and French factors. ...
Freddorick's user avatar
12 votes

Fama Mac-Beth (1973) vs Fixed effect

A more apples to apples comparison would be between (i) Fama-Macbeth procedure and (2) clustering standard-errors by date. Adding fixed-effects is somewhat different. Problem: cross-sectional ...
Matthew Gunn's user avatar
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9 votes

Definitions of Beta

I slightly disagree with Alex’s comment. The CAPM does not read as \begin{align*} r_{i,t} = r_{f,t}+ \beta_{i} (r_{m,t}-r_{f,t}) + \varepsilon_{i,t}. \end{align*} There is an important difference ...
Kevin's user avatar
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8 votes
Accepted

What drives the idiosyncratic volatility puzzle?

Preliminary The empirical finding of a strong negative cross-sectional relation between idiosyncratic volatility and future stock returns is highly inconsistent with the predictions of all theoretical ...
skoestlmeier's user avatar
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8 votes
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CAPM model as a regression

If you really believed the CAPM's prediction that $\alpha=0$, then imposing $\alpha=0$ in your estimation would indeed lead to your 2nd formula. The problems? The CAPM doesn't work so imposing a ...
Matthew Gunn's user avatar
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8 votes
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What is the textbook answer to dealing with multicollinearity?

As one of the interviewers suggested, the expected answer starts with PCA and SVD. Before detailing it, let's take a paragraph about the way you seem to "misunderstand" the problem: ...
lehalle's user avatar
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8 votes
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Fama / French 3 Factor Data Not Giving Expected Results

That's perfectly normal. You are running a regression for a single stock. Single stocks have a lot of idiosyncratic risk (which is what the $R^2$ is capturing). I just run the fama-french regression ...
phdstudent's user avatar
  • 8,061
7 votes
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Interpreting the coefficients of Fama-MacBeth regression

No, you cannot interpret the average return for the factor as the risk premium. The second stage regression is equivalent to building a set of portfolios that have no net investment, a unit exposure ...
Tim Wilding's user avatar
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6 votes
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Modelling and forecasting mixed frequency financial data

MIDAS is useful when you have a low frequency series and you want to include high frequency data in the regression. So for instance, if you want to forecast quarterly GDP data and want to include ...
John's user avatar
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6 votes
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Using cross-sectional factor model (BARRA type) returns in a time series factor model (Fama-French type)?

What you're describing sounds like the reverse of a Fama-Macbeth regression. The original Fama-Macbeth approach estimated rolling time series regressions to get CAPM betas and then doing a cross-...
John's user avatar
  • 5,391
6 votes

How exactly do I calculate and interpret factors in Fama-French model?

The clearest hands-on explanation I have seen so far is the following: Bernstein, W.: Rolling Your Own: Three-Factor Analysis Everything is explained very clearly and step-by-step with Excel. ...
vonjd's user avatar
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6 votes
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Linear Regression vs Mean Variance Optimization

In a linear regression approach you do the following: $$ (X \beta - y)^2 \rightarrow Min $$ thus you try to predict something. Your objective is quadratic. You usually add constraints on $\sum \...
Richi Wa's user avatar
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5 votes

How to use factor models for prediction?

You kinda mentioned in your questions, but the predictive model is essentially a lagged version of the "factor model". Part of the problem comes from the subscripts, the model itself doesn't really ...
Will Gu's user avatar
  • 702
5 votes
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Hansen and Jagannathan distance

It would be easier to answer if you tell us where that equation came from (there are many ways of deriving the HJ distance) - in any case the numerator of your equation should be the expected return ...
phdstudent's user avatar
  • 8,061
5 votes
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How to do Fama French (1993) cross sectional regressions? A few questions

You say: At this point I don't really get any further, as I am unsure about which "cross section" is being talked about here. Since I have created 25 portfolios, I can only have all in all ...
phdstudent's user avatar
  • 8,061
5 votes

Why and when we should use the log variable?

I cite from the fantastic book by Bali, Engle, and Murray (2016): Empirical Asset Pricing: The Cross Section of Stock Returns. In what follows, they talk about the pricing of size in the stock market (...
Kevin's user avatar
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4 votes

Testing Valuation, Size and Momentum (proprietary factors) from 1988-2013: No evidence of driving cross-sectional returns

I think your best shot is to share with us your 3,000 stocks. How far can that be from FF sample? As a quick check I took the 25 book-to-market portfolios and the Fama-French 3 factor model and run ...
phdstudent's user avatar
  • 8,061
4 votes

CAPM Calculations

The question above looks somewhat confused. Where's the error term? A recipe for a standard calculation It's customary to work with monthly returns. For each portfolio $i$, calculate monthly ...
Matthew Gunn's user avatar
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4 votes
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How can you determine the correct significance of the Shiller P/E regression?

Overlapping observations leads to correlation of error terms Let $r_{t \rightarrow t+k}$ be the log return from time $t$ to $t+k$. Imagine you're running a regression forecasting $k$ year returns ...
Matthew Gunn's user avatar
  • 6,934
4 votes

Is my data fittet to be significant?

The question you ask is in fact about what people in machine learning call overfitting: the more you choose your "metaparameters" to provide high returns on your sample of days the less you can trust ...
lehalle's user avatar
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4 votes

Calculating fund alpha using Fama-French 3 factor model?

In the long run, you'd probably be better off learning a real programming language like Python, R, or MATLAB. While you can do this in Excel using mmult, ...
Matthew Gunn's user avatar
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4 votes

Question about Fama Macbeth Regression (Confusion about paper)

Fama-MacBeth procedure (Step 1): So if my understanding is clear, first we would use the cross sectional regression to estimate 4*5,000=20,000 betas? That is not right, because betas (and other risk-...
skoestlmeier's user avatar
  • 2,916
4 votes

Fama-Macbeth practitioner's step by step guide?

For each stock run a time series regression: $r_{i,t} = \alpha + \beta F_t + \epsilon_t$ Then for each month $t$, you run a cross-section regression: $r_{i,t} = \lambda_0 + \hat{\beta}_i {\lambda}_t + ...
phdstudent's user avatar
  • 8,061
4 votes

Is it safe to assume inflation rate and treasury yields are stationary?

Answering your main question: Is it a huge problem if I start running correlations on the original values? Short answer: Yes. Both the raw/untransformed CPI and treasury yields are widely known non-...
Pleb's user avatar
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4 votes
Accepted

Cross Sectional vs. Time-Series Risk Premia Estimate

No one is better at explaining asset pricing than John Cochrane. He explains it in detail in his brilliant textbook. The following videos from his video course are pure gold 2.2 Time-Series and GRS 2....
Kevin's user avatar
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4 votes
Accepted

How does one show that the Sharpe Ratio is closely related to the t-statistic of the mean differential return?

It makes sense. Intuitively, I consider the Sharpe ratio as a proxy for win-rate. Let's assume normal returns. The Z score is defined as: $$ \frac{x - \mu}{\sigma} $$ The T-stat for zero-mean is ...
Newquant's user avatar
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