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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2
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3answers
121 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 ...
9
votes
1answer
2k views

How do I reproduce the cross-sectional regression in “Intraday Patterns in the Cross-section of Stock Returns”?

Recently I was trying to reproduce the results of "Intraday Patterns in the Cross-section of Stock Returns" (published in the Journal of Finance 2010). The authors used cross-sectional regression to ...
10
votes
1answer
189 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 ...
1
vote
0answers
15 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, ...
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
39 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
votes
1answer
37 views

For a Fama-Macbeth regression , How does one predict the returns based on the model?

Fama-Macbeth does a two-step regression i.e a time-series and cross-sectional regression and we estimate betas and lambdas, so how does one predict based on these parameters, which one to choose?
2
votes
1answer
38 views

How to retrieve and format futures data for use in regression/time series models?

I need to form a predictive time series model for monthly Brent crude oil spot price. I am looking to form 1-12 month ahead forecast horizons. There is a bounty of previous literature which uses ...
2
votes
1answer
108 views

Orthogonal Regression/PCA

I am doing orthogonal regression. My X matrix consists of returns on a broad market index, value index, growth index, a few sectors,.....(my Y is the returns on an equity fund) I am regressing the Y ...
1
vote
1answer
44 views

What is wrong in my non-linear estimation sample code?

I am trying to reproduce the code and plot you see here on pages 8,9 and 10 which was coded in MATLAB, but I'd like to convert it to R code. I believe I converted the MATLAB code below to R syntax ...
3
votes
3answers
47 views

Interpretation of t-test in event study with dummy regression

I am not sure about my interpretation of the t-ratios in dummy regression models for event studies. I have the results for two different groups of models examining the impact of news on stock returns ...
1
vote
0answers
47 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 ...
5
votes
1answer
149 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 ...
1
vote
1answer
35 views

Differences between dummy regression event study and regression on residuals from market model

I have two different event study approaches and I wonder if the results are exactly the same. Model 1 applies a dummy regression market model: (1) $R_{t}=\beta_{0} + ...
24
votes
5answers
4k views

Machine Learning vs Regression and/or Why still use the latter?

I come from a different field (Machine learning/AI/data science), but aim to ask a philosophical question with the utmost respect: Why do quantitative financial analysts (analysts/traders/etc.) prefer ...
2
votes
4answers
122 views

How to interpret regression coefficients with dummy explanatory variables?

I am a bit confused about the interpretation of the regression coefficients in a regression model: $R_{t}=\beta_0+\beta_1R_{mt}+\beta_2D_{t}+\epsilon_t$ where $R_{t}$ is the log return of some ...
1
vote
1answer
38 views

Testing day of the week effect

I am currently reading a bit about testing day of the weeks effects. I saw two different model specifications and wonder how to interpret the results. The first model type includes only 4 dummies for ...
-2
votes
1answer
39 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 ...
1
vote
1answer
27 views

Adjust regression for thin trading

What procedures can I apply to control in a regression on company returns for thinly traded stocks? Is the inclusion of the SMB-factor a potential approach? Or just a dummy variable indicating if a ...
8
votes
3answers
326 views

Does Kalman filter always improve over linear regression?

If I have a simple linear regression that has statistical signification but I would like to improve the overall prediction results. Will a Kalman filter be always an improvement or as least achieve ...
4
votes
1answer
431 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
55 views

Rebucketing Risk using PCA/other methods

was working on a project and could use some help. New to the community and looking fwd to being an active part of it. My question is, let's say we have a vector of securities V, and it trades with ...
0
votes
0answers
30 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 ...
7
votes
3answers
1k views

Using rolling returns in a multivariate linear regression?

I am trying to use fundamental factors such as PE, BV, & CFO in a multivariate linear regression with the response variable being the rolling 1 month returns. But this approach seems flawed as the ...
2
votes
1answer
55 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). ...
1
vote
0answers
15 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 ...
6
votes
2answers
365 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 ...
1
vote
1answer
60 views

Regression model syntax

I'm following the methodology outlined in Developing High-Frequency Equities Trading Models. On page 27, the author outlines an OLS regression model to obtain beta coefficients. The model is defined ...
1
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0answers
176 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 ...
12
votes
4answers
5k views

R: Fast and efficient way of running a multivariate regression across a (really) large panel (First pass of Fama MacBeth)

I am attempting to run a rolling multivariate regression (14 explanatory variables) across a panel of 5000 stocks: For each of the 5000 stocks, I run 284 regressions (by rolling over my sample ...
2
votes
2answers
167 views

Transforming Variables in Regression

I have a very simple problem that hopefully someone could help me with or at least point me in the right direction. I am testing to see which factors affect index returns the most and would like to ...
0
votes
0answers
41 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
votes
0answers
62 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, ...
9
votes
1answer
245 views

Regression in liquidity risk model of Jarrow/Protter

In the paper "Liquidity Risk and Risk Measure Computation" authors describe a linear supply curve model for liquidity risks in presence of market impact, i.e. impact-affected asset price $S(t,x)$ is ...
3
votes
2answers
469 views

What's the meaning of the intercept in asset pricing model?

I would like to understand the role of alpha (intercept) in the regression-based asset pricing model or $n$-factor models; one of the most famous of those one is the Fama-French 3-factor model. ...
1
vote
1answer
108 views

how can I calculate the factor loading (beta)?

I am writing my Thesis about hedge funds performance measurement and I want to use the seven factor model proposed by Fung & Hsieh (2004). Now, I am struggling to find out how to calculate the ...
1
vote
0answers
69 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 ...
0
votes
3answers
417 views

How to create a model or formula for evaluating trade opportunities

I want to build a formula to produce a score for a potential trade based on 4 variables, time, return, liquidity of security, and probability of failure. For a set of potential trades I first ...
14
votes
3answers
1k views

Please give a step-by-step explanation on how to build a factor model

Factor models such as Fama-French or the other ones that are partially summarized here work on the cross-section of asset returns. How are the factors built, how are sensitivities/coefficients ...
0
votes
2answers
151 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?
0
votes
1answer
240 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 ...
1
vote
3answers
161 views

Technical Indicators reference

I have been looking for a good reference where I can find how technical indicators of stock market analysis are calculated. I have a dataset (time series) which I want to extract these indicators to ...
1
vote
1answer
391 views

Actually benefiting from logistic regression to estimate probability of default

Does anyone know any events where using logistic regression to estimate probability of default has led to a bank, financial institution, government or anything really to benefit in practice? I see a ...
0
votes
0answers
33 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 ...
0
votes
1answer
116 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 ...
5
votes
0answers
88 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 ...
1
vote
0answers
46 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 ...
2
votes
2answers
228 views

Using Financial Ratios to get credit rating or PD

Hello I'm looking for papers, aside from ones that use CDS spreads, about credit rating development or estimating default probability based on financial ratios that also include methodology and maybe ...
2
votes
3answers
252 views

Ran multivariate linear regression, checked normal probability plot, residuals are not normal. What can I do?

One of the required assumptions for multiple linear regression is that residuals are normally distributed, correct? After running my regression, my normal probability plot is showing the typical ...
6
votes
3answers
621 views

Testing the validity of a factor model for stock returns

Consider the following m regression equation system: $$r^i = X^i \beta^i + \epsilon^i \;\;\; \text{for} \;i=1,2,3,..,n$$ where $r^i$ is a $(T\times 1)$ vector of the T observations of the dependent ...