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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2answers
182 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 ...
2
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1answer
107 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 ...
2
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0answers
145 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
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0answers
184 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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0answers
218 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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0answers
288 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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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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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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1answer
706 views

How to compute portfolio weights from multivariate regression results?

Assuming that I performed a multivariate regression and I found a set of $k$ coefficients $\alpha_1, ..., \alpha_k$ for each of the factors $F_1, ... F_k$. I have then computed the following ...
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1answer
387 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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1answer
159 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 ...
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1answer
254 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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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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1answer
34 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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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
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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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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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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1answer
153 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
254 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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1answer
153 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
730 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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1answer
405 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 ...
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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, ...
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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 ...
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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 ...
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0answers
172 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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0answers
67 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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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 ...
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0answers
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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0answers
100 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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0answers
141 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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0answers
103 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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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. ...
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0answers
116 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 ...
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1answer
225 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 ...
0
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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
35 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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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?
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2answers
514 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 ...
0
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1answer
239 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 ...
0
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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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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 ...
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3answers
102 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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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 ...
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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 ...
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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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0answers
61 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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0answers
32 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 ...