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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6
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1answer
99 views

How to interpret the French-Fama SMB factor?

I regressed ten portfolios on the Fama French factors and get significant loadings on the SMB factor. However, if I look at the actual average market cap of these portfolios, the portfolios with the ...
4
votes
1answer
155 views

Moving window forecasting in Python

I am looking to create some code that will out-of-sample forecast the HAR-RV model. The model itself is formulated as the following, and the betas are estimated through HAC-OLS or Newey-West. ...
1
vote
1answer
27 views

How to deal with missing returns when creating value (equal) weighted returns

recently I am doing cross sectional regressions, and getting confused about missing returns. Suppose we have 100 stocks, then we want to construct a value weighted return (or equal weighted return). ...
0
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1answer
97 views

Using multiple regression to determine coefficient that feed into another multiple regression problem

Ok so it is a bit of a complicated problem so I hope I explain this well. I currently have a multiple regression formula where I input 3 items and the output is expected growth. Each of these input ...
4
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0answers
72 views

Is Least Median Squares (LMS) regression commonly used in Finance?

Least Median Squares is often argued to give more stable results than does OLS. Whereas in OLS one minimises the mean of squared residuals, in LMS, one instead minimises the median of squared ...
4
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0answers
517 views

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

I am currently testing whether three proprietary factors - Valuation, Size and Momentum - explain cross-sectional returns. A sample of 3000 securities was tested using Fama-MacBeth two-pass ...
4
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0answers
482 views

How to determine ratios for mean-reverting basket

Suppose I have a basket of 3 securities A, B, and C. I believe that the basket is cointegrated and I want to create a mean-reverting trade. I fit the model: ...
3
votes
0answers
81 views

Filtering out AR(1) effects before using stochastic volatility model

I wonder if I first filter out AR(1) (autoregressive model with lag 1) effects from univariate time series and then fit stochastic volatility model does above procedure introduce any bias at first or ...
3
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0answers
140 views

GMM time-series regression factor model with factors that are not returns

Factor models with factors that are not returns are usually estimated and tested by cross-sectional regressions. However, there is a way to use time-series regression to estimate and test the model. ...
3
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0answers
79 views

Dividend Index Futures

My question is dealing with the proportionality between Dividend Index Futures prices and Index prices. Indeed, we in the past we used to do a simple regression between these variables and use the ...
3
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0answers
334 views

How to balance two Forex crosses correctly to do a linear regression?

I have two cross and an account in EUR: EUR/USD GBP/USD I would like to do a balanced linear regression using R. With "balanced" I mean that I would like to normalize it by calculating the ...
2
votes
0answers
172 views

Potential pitfalls in the use of correlation

Background: The red line is an index, which goes from 0 to 100, measuring uncertainty in the markets. The dark blue line is a price index, which has a lower bound at 0, and virtually no upper bound. ...
2
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0answers
198 views

How to properly take averages to reduce data in regression/panel data analysis

I'm trying to do a regression on my panel data. Say I have T=3500 days of data and N=125 firms. Since Matlab get's major memory issues (which I try to prevent by the usual solutions as seen on the ...
2
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0answers
217 views

Any one know how to implement the Heston and Rouwenhorst country-sector effects regression in R?

Heston and Rouwenhorst (1994) devised an empirical estimation strategy to decompose stock returns into three components: a pure industry effect, a pure country effect, and a world-factor return. ...
1
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0answers
39 views

Confused on interpretation of betas/alphas in regression in finance

I ran a regression on two stocks. I don't have the data in front of me, but it is a more conceptual question. Let's say SP500 returned a total 23% return over this time period and MSFT returned ...
1
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0answers
39 views

Should I use a correlation coefficient formula or a multiple regression formula?

I have an assignment dealing with the stock market and I'm a little lost. My instructions are to come up a method to create a score for a stock then compare the score against what the stock actually ...
1
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0answers
100 views

Stationarity tests in the frequency domain for regression

Strict stationarity is the strongest form of stationarity. It means that the joint statistical distribution of any collection of the time series variates never depends on time. So, the mean, variance ...
1
vote
0answers
17 views

Standard errors clustered along the time dimension in pooled panel logit model

I'm trying to estimate a logit model on pooled panel data set (unit of observation is firm-year). My dependant variable is default indicator and I have several macro variables as independant ...
1
vote
0answers
69 views

Variable Selection with Kalman Filter

I'm trying to estimate factor loadings on portfolios over time for portfolios that are traded pretty frequently. I have a sense that several portfolios are loading on the Fama-French HML factor ...
1
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0answers
102 views

How To Regress Returns Vs Price as Pct of 52 week high?

I would like to do a linear regression of daily stock price returns, vs the price as a percentage of the 52 week high. i.e. [next week return] = A * [Price / 52 Week High ] + B where A and B are ...
1
vote
0answers
99 views

Insignificant or significant explanatory power over risk adjusted returns?

Currently iam working on my master thesis which is about risk adjusted returns in the Asia Pacific REIT market. The goal of the paper is to determine/find variables that conceive explanatory power ...
1
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0answers
112 views

What to do with linear regression or regression splines outside of the training range?

This is a cross-post from here In my question on a load forecast model using temperature data as covariates I was advised to use regression splines. This really seems to be a/the solution. Now I ...
0
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0answers
26 views

Test for NonLinearity

I am doing a regression, returns of stocks(cross section of stock returns at a given time) against some fundamental factors. And look at the residuals to get a normalized view when trying to rank the ...
0
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0answers
19 views

Choosing an optimal dependent variable, regression/model fitting

When I select a certain target variable and model that with either linear regression or some other technique, say naive bayes, I hope to finally arrive at a model which has statistical significance, ...
0
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0answers
21 views

Finding optimal ewma and number of periods usedas features in a time series regression

I am using an exponential moving average (ema) to smooth the return of a price time series. I then want to use the last n periods (features) as the independent variables of the time series to predict ...