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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178 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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1answer
450 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
170 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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1answer
503 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
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1answer
120 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 ...
6
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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 ...
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0answers
49 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
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2answers
256 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
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3answers
262 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
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3answers
630 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 ...
2
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0answers
174 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
191 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
108 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
316 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 ...
3
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0answers
186 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. ...
0
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1answer
274 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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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 ...
12
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5answers
6k views

Using linear regression on (lagged) returns of one stock to predict returns of another

Suppose I want to build a linear regression to see if returns of one stock can predict returns of another. For example, let's say I want to see if the VIX return on day X is predictive of the S&P ...
3
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1answer
186 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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1answer
247 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 ...
7
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2answers
467 views

Efficiency vs. Robustness - To use a constant or not in single factor time-series regression?

Arbitrage pricing theory states that expected returns for a security are linear combination of exposures to risk factors and the returns on these risk factors. Betas, or the exposures of the security ...
2
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2answers
202 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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0answers
109 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 ...
2
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1answer
78 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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1answer
161 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 ...
3
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1answer
182 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' ...
14
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1answer
5k views

Which approach to estimating fundamental factor models is better, cross-sectional (unobservable) factors or time-series (observable) factors?

There are many approaches to estimating fundamental factor equity models. I would like to focus on two traditional methods: The time-series regression approach of Fama and French. Factors are ...
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1answer
796 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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0answers
153 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 ...
2
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0answers
221 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
188 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. ...
4
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0answers
98 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 ...
2
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1answer
1k views

Multiple (linear) regression

I am looking for some inputs on a pair trading strategy that I am trying to improve with some semi-fundamental input. The basic idea is to use multiple linear regression to estimate the price of a ...
5
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1answer
214 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 ...
2
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3answers
573 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 ...
2
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3answers
468 views

Why do long-term equity return forecast models use dependent observations?

I've been reading up on different models used to forecast the equity risk premium, and I've seen a couple of papers that had questionable methods. For example, this paper by Javier Estrada goes into ...
8
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0answers
675 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
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2answers
566 views

Why are regressors squared and not ^1.5 or ^2.2 or ^2.5?

When a researcher in economics or finance wants to apply a linear regression model but suspects a non-linear relationship between one of the regressors and the dependent variable, it is typical to ...
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0answers
105 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 ...
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1answer
165 views

Regression of Unequally Weighted Portfolio against a Single Index

When I regress a single stock against a market index, I get a high value of R2 and beta closer to 1. APPL.fit <- lm(APPL ~ JKSE) When I regress an unequally ...
4
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0answers
540 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: ...
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0answers
35 views

How to set up Heston and Rouwenhorst regression? [duplicate]

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. ...
2
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0answers
320 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. ...
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1answer
427 views

Proxy for Expected Economic Growth

Can anyone help me understand how expected economic growth is usually measured? I've read several papers that talk about using breakeven inflation as a proxy for expected inflation, and then the ...
0
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2answers
533 views

Regression with Lagged variables

I am new to regression analysis. Let's say initially I have a linear regression x = alag(x1) + blag(x2) + clag(x3) -- eq 1 I want to predict the price x based on the the price of x from previous ...
5
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2answers
195 views

How does the number of free dimensions of a model affect its required size of sample?

Adding more variables to a model usually increases its accuracy. However, without adequate analysis it could also lead to curve fitting. Another question (How much data is needed to validate a ...
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1answer
113 views

Regression extensions

I'm trying to find extensions for my regression and obviously would like to use PE, BV and CFO. But I've got monthly data, while all company's fundamentals are semi-annually... Can I deal with it ...
5
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1answer
3k views

How to use Newey West covariance corrector?

I have implemented the following model: daily_vol(t+1) = A*daily_vol(t) + B*weekly_vol(t) + C*monthly_vol(t) + error where vol means volatility, and A, B, C are ...
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1answer
258 views

Regression giving the return on a stock

I have this regression equation: $$ R_{stock} = 3,28\% + 1,65*R_{market} $$ Where $R_{stock}$ is the expected return on a stock and $R_{market}$ being the market risk premium. I have a one-year ...
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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 ...