Questions tagged [regression]

Techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables.

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Aggregation of (cross-sectional) Factor model

Suppose I have a large factor model for security returns, i.e. I have a vector $\mathbf{Y}(t) \in \mathbb{R}^{P}$, with factor loadings $\mathbf{\beta} \in \mathbb{R}^{P \times K}$ over a set of $K$ ...
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Cross Sectional vs. Time-Series Risk Premia Estimate

Consider the single factor model in time series form, e.g: $$ r_t^i = \alpha_i + \beta^i f_t +\epsilon^i_t \quad (1) $$ Here $i$ is not an exponent but a superscript, e.g. it represents the return ...
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Using regression for binomial prediction of tomorrow's return

I completed a challenge which asks the user to predict tomorrow's market return. The data available is prices data and the model must be logistic regression. They call it "machine learning" ...
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Regression taking in account size of earnings surprises

I'm trying to regress earnings surprises on variable x. However, absolute earnings surprises are mostly influenced by company total earnings and the number of shares outstanding. So I can't just use ...
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Constructing a Replicating Portfolio : Regression on Individual Constituents or their Average?

I would like to replicate a portfolio of stocks $S_1, \cdots, S_n$ using other instruments, $X_1, \cdots, X_m$. Using the letters above with a subscript $t$ to denote the forward returns over some ...
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Should I include factor loadings as explanatory variables for regression of abnormal and raw returns?

My research is to explain stock returns in a regression model. My dependent variable is raw returns and abnormal returns calculated from 3-factor model (Fama and French). Besides regressing against my ...
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Coefficients of univariate regressions equal to those in the multivariate regression

I am currently running fixed effect regressions with multiple dummy variables. These dummy variables are created by a grid of '1' '0': ...
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Cross sectional regression for monthly retuns wih time lag

I am trying to understand the cross-sectional regression methology of Fama MacBeth in the setting of monthly returns with time lags. I was reading "Seasonality in the cross-section, Steven L. ...
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Understanding Fama MacBeth regression

I tried to understand the FamaMacBeth procedure but I don't think that I got it. A time series regression is just a linear regression for each of the $n$ returns? Consider the most easy linear ...
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How to add Yearly /Quarterly control variables on daily panel data?

I am working on a dataset where I have to regress daily stock return on daily ESG momentum scores, including some control variables. For market based measure of risk factors, I have added Fama-French ...
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1 answer
65 views

Case Shiller repeat sales index methodology

I am trying to find a definitive specification of the index construction methodology for the S&P CoreLogic Case-Shiller Home Price Indices produced by S&P Global – also known simply as Case-...
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Event study individual day Abnormal returns in STATA

I am conducting an event study, testing the abnormal returns for a sample of 39 companies and a single event (April 29 2009). Currently, I am calculating the ARs using the FF 3-Factor Model and the ...
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How do I perform the regression analysis? Do I need to create a Panel Dataset?

I am currently trying to replicate a regression from the 2015 paper "Science and the stock market: Investors' recognition of unburnable carbo" by Griffin et al. It analyzes oil and gas firms'...
2 votes
1 answer
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Is it compulsory to use seemingly unrelated regression method while running the Fama French style 25 portfolios on the independent risk factors?

I have scanned rigorously on the internet but the information regarding the SURE methodology seems surprisingly very little (at least with regard to its application in finance). I would have imagined ...
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Fama-MacBeth regression [pmg() from plm-package] yields NA coefficients

I am trying to estimate Fama-Mac Beth coefficients with this code: ...
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Is it safe to assume inflation rate and treasury yields are stationary?

I have YoY percent change in CPI and the nominal 10 year Treasury yield. I want to run some correlation analysis between them but worry they are not stationary. I ran a DF test and found that, ...
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Help interpret an event study methodology used in a famous research paper

I wonder if someone out there familiar with reading research articles, especially finance research can help me interpret which event study methodology the author uses in her famous research article. ...
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1 answer
106 views

R-squared to be computed on training sample or test sample?

I am currently going through the book Machine Learning For Factor Investing whose online version can be read here: http://www.mlfactor.com In the section on model validation, one can read the ...
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Should I train (and apply) a commodity forecasting model using nominal or real historical (futures) prices?

I am forecasting hourly power prices by applying Gradient Boosting to, among other variables, average monthly gas prices. The algorithm is currently trained on historical nominal monthly average gas ...
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1 answer
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Intuition behind the definition of “long run propensity” equaling sum of coefficients?

In a multiple linear regression model with independent variables x(t), x(t-1), x(t-2), etc. and dependent variable y, the “long run propensity” is defined to be the sum of beta coefficients in the ...
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How exactly is time series regression useful to market participant?

Assume we run an OLS regression with dependent variable of 3-month holding period returns of a stock, and independent variable of 10 year treasury yields. Assume regression coefficient is 2, so for ...
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OLS regression using varying holding period returns against 10 year yield?

Can I run an OLS regression using varying holding periods for a stock? I want to find the relationship between returns of stock x and the 10 year treasury yield, but I want to find what happens if for ...
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Interpreting regression coefficients using financial return data?

My independent variable is the monthly returns of Stock A. My dependent variable is the monthly returns of Stock B. Returns are calculated using [(price at end of month) / (price at beginning of month)...
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1 answer
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Regressing indexed data with non-indexed data, and varying base years?

Is it acceptable to run a regression with several independent variable datasets whose base years are different? I.e., predicting some variable y using Q4 2007 = 100 vs. Q1 1980 = 100, not in a ...
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1 answer
107 views

Statistical significance in the context of financial data?

I understand statistical significance in the general sense: we take a sample from a population and compute some parameter from the sample to infer what is the propulsion parameter to some degree of ...
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Compare portfolio returns across time dimension

I've designed a trading strategy and would like to understand whether the return profile for it differs for the trades implemented before and after the Covid pandemic. Specifically I would like to ...
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Real estate returns with incomplete dataset?

I have a dataset of real estate returns in markets A, B, and C. I also have national returns, denoted market N. I have 10 columns representing the time period for each data point. Market A only has ...
3 votes
3 answers
3k views

Why and when we should use the log variable?

Normally, I see finance papers use the real ratios but log regarding non-ratio variables. For example, some papers used log(asset) or log(1+firm age) or log GDP, but regarding the ratio, they use the ...
2 votes
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Should we include the industry variables when we control for year*industry fixed effects?

In panel data, we control for firms and years fixed effects even we also have some time-variant firm-level regressors. I am wondering whether it also happens at the industry level. If it is the case, ...
4 votes
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Bet sizing with regression predicitions?

Applying the kelly criterion for bet sizing is quite easy if we use a (binary) classification model (say to predict the sign of a price return) or other model where probabilities of classes are a ...
1 vote
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Checking Regression Inputs & Outputs (Factor Regression)

I am looking to check the assumptions and interpretation of the output of a regression that I have run for factor exposures in a long/short equity portfolio: Portfolio is long/short equity with a net ...
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2 votes
1 answer
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What about autocorrelation and heteroskedasticity in Fama French?

I am analysing ESG and conventional mutual funds. I decided to measure the extra performance of each category using the Fama French 4 factor model, but it seems to me that in previous literature they ...
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FamaFrench, FamaMacBeth or Panel regression?

I hope my question is not extremely trivial. I want to analyse the performance of mutual funds using the Fama-French model. My dependent variable is the return of mutual funds (varying over time and ...
0 votes
1 answer
112 views

Regression analysis in finance - book recommendation

Hey I am looking for a good book about regression analysis in finance (e.g. credit risk). Could you recommend something? It would be great if this book will be connected with some programmic language ...
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1 answer
138 views

CAPM alphas have unexpected p-value distribution

I am trying to "test" whether the EMH holds by testing for every stock in the S&P 500 whether it has a "significant" CAPM alpha. If the EMH is true, then the null-hypothesis (...
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Statistical Inference of Variance Risk Premia

Good afternoon, I am currently following Carr and Wu (2009) to compute variance risk premia from options written as (RV-EV)*100 for the payoff of a long var swap position. Now I want to see whether my ...
0 votes
1 answer
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ETF NAV Premium vs. market ETF premium interpretation regression output

this is my first post in this forum, so if I'm doing any kind of mistake please let me know. My situation is as follows: I'm currently writing my Thesis and I'm looking into the discrepancies of ETF ...
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1 answer
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Regression of stochastic integral on Wiener process

This question is a follow-up from the following: conditional expectation of stochastic integral so I won't repeat myself regarding assumptions and notation. Using Brownian bridge approach, we know ...
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1 answer
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Not getting coefficient estimates when running a Fama Macbeth Analysis

I am trying to run a Fama Macbeth analysis in R, where I am using the 'pmg' function with the following code: ...
1 vote
0 answers
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Size factor - Root Market Cap Weighted

I saw in a paper for specifically the Northfield equity risk model that when constructing their factors they use the standard, time series regression to get each stock’s beta to a specific factor and ...
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1 answer
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Fama-French model interpretation of coefficients help

So i've run a regression for a stock and these are the results. I was wondering if I'm right in inferring that because the SMB coefficient is negative, this particular stock I've chosen has a large ...
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2 answers
126 views

Regressing changes in yield/yield curve

If I'm regressing changes in individual points along a yield curve and measures of changes in level/slope/curvature of that yield curve against the returns of some random variable then do I want to ...
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2 answers
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Best method to determine future success or to determine best linearity?

Long time viewer, but first time poster, so excuse me if i'm in the wrong place please. Anyway, I am working on a project that is pretty interesting. Through data mining, I am able to gather a ton of ...
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3 votes
1 answer
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Fair Value Regression Methods

Recently we had an invited talk at our university (I'm Ph.D. student in ML department, so I'm sorry if my question is stupid, since I do not have quantitative finance background), where one researcher ...
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EGARCH and GARCH effects with White Noise squared residuals

I'm asked to model a series which it's returns are white noise and after adjusting a regression like $r_t=c$ and looking it's squared residuals (white noise too) I'm asked to adjust a GARCH and EGARCH ...
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Fama McBeth - Significance

The very last step of the Fama McBeth procedure is to aggregate the estimated regression coefficients by taking their mean. The mean is then the estimate for the "overall" regression ...
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Difference between returns

I have a monthly time series of monthly returns for a specific factor that I'm investigating, the Quality factor QMJ as proposed by Asness et al. (https://www.aqr.com/Insights/Datasets/Quality-Minus-...
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Can you apply GARCH to ARIMAX models?

Is it possible to apply the idea of GARCH to time series models that include exogenous variables? For example, say I estimate a cash flow forecast model. Does it make sense to model the residuals by ...
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How often to tune the regularisation parameter in LASSO?

I'm trying to implement the following paper: Avellaneda & Lee (2010), Statistical Arbitrage in the US equities market. To build the strategy, the idea is to trade a stock and hedge using a basket ...
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Sigma squared times identity matrix in normality of errors

In OLS regression, we have the normality of the error terms $$\varepsilon \sim N(0,\sigma^2I_n)$$ I understand that we want to have a constant variance for homoscedastic errors, but why is $\sigma^2$ ...
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