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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14
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3answers
266 views

Regression model when samples are small and not correlated

I received this question during an onsite interview for a quant job and I'm still scratching my head on how to solve this problem. Any help would be appreciated. Mr Quant thinks that there is a ...
2
votes
3answers
204 views

Hedge Fund risk management on a daily basis

Since Hedge Funds/Fund of Funds report on a monthly basis usually within 10 days after the month end, monitoring and managing (hedging) potential risks is quite a difficult task. Having done some ...
4
votes
1answer
487 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
49 views

Regressing using Fama-French portfolios with small amount of stocks

I'm doing some research for my thesis and I was wondering if it is possible to only use monthly stock price data for 22 stocks and construct Fama-French portfolios out of them and then regress? What ...
0
votes
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 ...
0
votes
1answer
68 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 ...
8
votes
0answers
681 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 ...
6
votes
0answers
93 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
votes
0answers
99 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 ...
4
votes
0answers
543 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
189 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
votes
0answers
349 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
184 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 ...
2
votes
0answers
190 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
votes
0answers
222 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
votes
0answers
327 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
vote
0answers
33 views

Can a momentum strategy be cast as a multilinear regression model?

Disclaimer: the question is similar to Can momentum strategies be quantitative in nature? and (to an extent) What is the expected return I should use for the momentum strategy in MV optimization ...
1
vote
0answers
29 views

Cross-sectional Regression: Using calculated coefficient of first regression for a second regression as dependent variable

Hello stackexchange community! I am new to R and econometrics and and stuck in a step of the fama-macbeth (1973) regression, in which risk premia of stocks are estimated with a two-step regression ...
1
vote
0answers
31 views

How to combine regression models?

Say I have three data sets of size $n$ each: $y_1$ = heights of people from the US only $y_2$ = heights of men from the whole world $y_3$ = heights of women from the whole world And I build a ...
1
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0answers
21 views

Regression on default rates and backward extrapolation

Suppose that we have bankruptcy data representative for Small and Medium-sized enterprises in a country. We can therefore calculate default rates. Furthermore suppose that we found that GDP, ...
1
vote
0answers
51 views

Transforming Variables in time series regression

I have multiple quarterly time series data and trying to build a linear regression model using this dataset. Should the transformations on the LHS and RHS be the same i.e QoQ percent changes? Could ...
1
vote
0answers
17 views

Calculating rate of renewal for Certificate of Deposit

I am trying to calculate the rate of renewal for a large stock of Certificates of Deposit. These contracts are given on a fixed amount of time and some of them get renewed every time they reach ...
1
vote
0answers
249 views

Using cross-sectional factor model (BARRA type) returns in a time series factor model (Fama-French type)?

This may be seen as a follow up question for the previous discussion on time-series vs cross-sectional factor models: Which approach to estimating fundamental factor models is better, cross-sectional ...
1
vote
0answers
75 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
vote
0answers
50 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
vote
0answers
19 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
110 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
vote
0answers
156 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
106 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
vote
0answers
119 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
votes
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 ...
0
votes
0answers
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 ...
0
votes
0answers
19 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 ...
0
votes
0answers
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 ...
0
votes
0answers
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 ...
0
votes
0answers
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 ...
0
votes
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 ...
0
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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 ...