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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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
49 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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33 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
84 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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31 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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26 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
36 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
215 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
54 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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40 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
141 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
143 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
500 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
62 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
140 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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22 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
143 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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74 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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40 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
99 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
195 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 ...
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0answers
85 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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107 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
80 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
70 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
125 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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147 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
140 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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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 ...
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3answers
407 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
91 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
123 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 ...
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2answers
95 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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74 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 ...
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1answer
68 views

Regression of TAQ half-hourly stock volume data against news volume

I am planning to run regression of half-hourly stock volume against the half-hourly news volume for that particular stock. I am looking at 2 years of data for my analysis. However, I am stuck thinking ...
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2answers
147 views

The implied volatility surface and the option Greeks - to what extent is the information contained in their daily movements the same?

What is the link between option Greeks (i.e. vega, delta, gamma, theta) and implied volatility surface (IVS) movements? Could you say that their 'information content' is the same. i.e. that out of ...
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1answer
130 views

Constant term in linear regresion

Can someone give a mathematical proof as to why including a constant in a linear regression equivalent is to running a regression with demeaned data and zero constant? More specifically, consider the ...
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1answer
164 views

Estimating Beta from unevenly spaced price history

I have a certain non-stock asset that has 1 transaction every 1 to 8 months. I also have a price index of that class of asset compiled by another party on monthly basis. If I regress $price = \alpha' ...
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1answer
138 views

Minimum Variance Hedge Ratio in Binomial Framework

In order to find the minimum variance hedge ratio when holding a portfolio of vanilla call options and hedging with stock, you can do an OLS regression. In a binomial model framework, given ...
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2answers
255 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. ...
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1answer
576 views

Lagged dependent variable, yes or no?

I read conflicting opinions about the inclusion of lagged dependent variables in modeling, and I guess it is partly up to the researcher and depending on the scope and goal of the research. I'm ...
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107 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 ...
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175 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. ...
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82 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 ...
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201 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 ...
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3answers
3k 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 ...
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1answer
198 views

From $AR(p)$ to SDE

Let the Vasicek model to be $$\Delta r_{t}=k(\theta - r_{t-1})\Delta t+\sigma\Delta z_{t}$$ Due to the fact that $$\Delta r_{t}=r_{t}-r_{t-1}$$ if you let $\Delta t=1$, it is easy to see by ...
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3answers
491 views

Time Series or Regression

I'd like to research the impact of certain events and characteristics on the liquidity of the stocks over time. I've got a sample of 200 stocks and I use several measures of liquidity (Amihud, Bid-Ask ...
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597 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 ...
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539 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 ...