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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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, ...
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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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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 ...
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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 ...
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1answer
38 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?
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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 ...
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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 ...
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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 ...
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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 ...
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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} + ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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1answer
109 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 ...
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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 ...
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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 ...
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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 ...
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1answer
190 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 ...
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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 ...
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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, ...
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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). ...
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1answer
433 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. ...
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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 ...
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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 ...
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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 ...
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2answers
367 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 ...
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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 ...
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1answer
244 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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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 ...
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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 ...
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1answer
393 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 ...
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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 ...
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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 ...
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2answers
229 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 ...
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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 ...
5
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1answer
150 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 ...
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0answers
147 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 ...
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1answer
156 views

Interpret alpha's on Dual-Beta Model regression Results

I am trying to calculate the Dual-Beta for Apple (AAPL) by running a regression against the Spyder's ETF (SPY) & using the 10-yr Risk Free rate. The formula for the dual beta is: ($r_{AAPL}-r_f) ...
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1answer
98 views

How to model the effect of earnings surprises on long-term returns?

I'm looking into modeling the relationship between EPS announcement surprises with long-term returns (1 quarter to 3 years with intervals). I've based my current methodology off papers looking at the ...
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1answer
256 views

Understanding how to calculate tracking error

I have come across two ways of calculating Tracking Error (TE) but i'm not sure if they are essentially the same. The first way is to calculate the standard deviation of the difference between a ...
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0answers
174 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. ...
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1answer
227 views

What data should be used for regression-based model backtesting?

I ran regressions using historical valuation data and now want to backtest the models I came up with. Are there any issues with using the same historical data set for the backtest that I need to be ...
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18 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 ...
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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 ...
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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 ...
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1answer
218 views

How to see the impact of one variable on a set of other variables?

Editing my question: I have decided to use multiple factor model to model my stress test. I am using factor shock method to implement the propagation of shocks. I am doing this according to a book ...