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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184 views

For Probability of Default in retail credit what is more popular logistic regression or GLM with Poisson distribution and why?

Trying to understand which regression model is more popular in retail credit card industry Logistic regression or GLM with Poisson distribution and why?
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2answers
540 views

Regression with Lagged variables

I am new to regression analysis. Let's say initially I have a linear regression x = alag(x1) + blag(x2) + clag(x3) -- eq 1 I want to predict the price x based on the the price of x from previous ...
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1answer
508 views

Linear Model setup for Second-pass Regression

I'm confused on modeling the second pass regression given the beta's from the first pass. First-pass regression : $r_{it} - r_{ft} = a_{i}+b_{i}(r_{Mt}-r_{ft})+e_{it}$ For estimating this model (9 ...
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1answer
121 views

How to construct a deterministic trading model based on a loess (local regression) model?

Given data that has been fit to a loess model, can you make reliable decisions on future trades given a good past fit? Has anyone here done so and can give an example of their use case? I am yet to ...
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0answers
7 views

subsamples versus dummy variable approach, Fama MacBeth (1973) procedure

I am running an asset pricing test (Fama MacBeth); regressing six month ahead excess stock returns on past six month return (momentum) and a number of control variables (B/M, Size etc). I have run my ...
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13 views

Deming Regression

I am trying to test the linearity = interdependence or the non-linear (contagion) between Asian countries during the Asian crises using the fluctuation of the exchange rate. Is it relevant to use the ...
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1answer
20 views

Heteroskedasticity and significance of parameters

I am doing a regression analysis and my variable of interest turns out to be significant at the 5% level, but the model contains heteroskedasticity which can not be mitigated (using Box-Cox, Feasible ...
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20 views

Practical Implications of Fama French Loadings

Suppose you have historical returns for a portfolio. You regress these against the Fama French factors to get the loadings/coefficients. How can you use this information? For example, can you use the ...
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17 views

Using the univariate regression coefficient to calculate cumulative return - does it make sense?

When testing a stand-alone signal usually one of the simple tests I do is a long-short equal-weight strategy to see how the wealth chart looks like. Going through my predecessor's code I see ...
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1answer
70 views

Fama-French three-factor model vs four-factor (Carhart) and five-factor model

I'm performing a study where I compare the Fama-French three factor model to the CAPM on the Swedish industrials industry. I do this to compare which of the models is the best performer, but also if ...
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22 views

Why do people use weighted regression with returns?

For example, by ADV. Intuitively it makes sense that a very liquid high ADV stock should carry more weight, but when I try it with some real life data I get higher standard error than unweighted...is ...
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1answer
47 views

Deriving the single factor model

Consider the following regressions, with the common factor $x$: $y_1 = \beta_1 \cdot x + \gamma_1 \cdot \epsilon_1 $ $y_2 = \beta_2 \cdot x + \gamma_2 \cdot \epsilon_2 $ With $\epsilon_1$, ...
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13 views

Magnitude of Predictors on Logistic Regression

We are using logistic regression for calculating delinquency. We know what the major predictors are, but we don't know how to quantify the impact of each of the major predictors. We know how to rank ...
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0answers
46 views

Seasonality of Securities & Dummy Variable Regression Analysis

I have some pricing data for some securities that I am looking at for seasonality. 1 My Data is organized as: Date Ret DVar1 DVar2 ...... date % 1 0 date % 0 1 ...
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0answers
33 views

Is there a considered floor for variation the 1st principal component must explain?

I am wondering if there is a considered floor to the percentage variation the 1st principal component must explain in general for PCA - ie. any lower and it is not worth doing PCA at all? Is the floor ...
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1answer
114 views

Regression extensions

I'm trying to find extensions for my regression and obviously would like to use PE, BV and CFO. But I've got monthly data, while all company's fundamentals are semi-annually... Can I deal with it ...
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0answers
10 views

Regression model extension [on hold]

I've been asked to do out of sample procedure for my simple regression model. my dependent data is belong to 2500 index nad independent one is belong to 2500 stock log returned data. how should i ...
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1answer
41 views

regression analysis [closed]

"A model estimated with a large no. of observations may allow one to reject null hypothesis of zero coefficients for many explanatory variables.Thus we might choose to select a somewhat lower ...
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1answer
525 views

Trading Strategies and Portfolio Constructions based on Cross Sectional Regression? [closed]

I often see trading strategies and portfolio construction that are based on cross-sectional regression. For example, I often see regressing some numbers against some factors. I was wondering how ...
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1answer
746 views

How to calculate the weight of the stocks using the linear regression?

I do a simple example with the follow three series(stocks prices): ...