Questions tagged [regression]

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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65 views

Difference between returns

I have a monthly time series of monthly returns for a specific factor that I'm investigating, the Quality factor QMJ as proposed by Asness et al. (https://www.aqr.com/Insights/Datasets/Quality-Minus-...
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Can you apply GARCH to ARIMAX models?

Is it possible to apply the idea of GARCH to time series models that include exogenous variables? For example, say I estimate a cash flow forecast model. Does it make sense to model the residuals by ...
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Identifying factor model shifts in different periods

Given a set of K independent variables X = (x1, x2, ..., xk) and a dependent variables y, I try to run the step-wise regression ...
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How often to tune the regularisation parameter in LASSO?

I'm trying to implement the following paper: Avellaneda & Lee (2010), Statistical Arbitrage in the US equities market. To build the strategy, the idea is to trade a stock and hedge using a basket ...
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52 views

Sigma squared times identity matrix in normality of errors

In OLS regression, we have the normality of the error terms $$\varepsilon \sim N(0,\sigma^2I_n)$$ I understand that we want to have a constant variance for homoscedastic errors, but why is $\sigma^2$ ...
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Minimizing the sum of squared errors in linear regression (proof/matrix notation)

I'd appreciate you helping me understanding the proof of minimizing the sum of squared errors in linear regression models using matrix notation. I'm trying to derive by minimizing the sum of squared ...
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transforming variables

I am would like to create a regression model with different variables however before using these variables in my regression model I would like to transform the variable in order to make it more ...
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The question is related to the regression analysis - stationarity testing

How to interpret different scenarios in ADF test. Scenarios: ADF Test: Type: None, Drift, Trend What exactly each of the types specify and when to use which 'type' during performing stationarity and ...
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Fama MacBeth regression over long time horizons

I have a question related to Fama MacBeth type regressions: I use total stock returns as the dependent variable and various variables (including market beta, size, valuation) as explanatory variables. ...
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basic cross sectional regression question for dummy variable

how does a cross sectional regression works if you have only 1 independent variables being a dummy variable-ratings. lets suppose building a proxy benchmark for similar rated company.
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How to measure the sensitivity of a fund to a set of indices?

I'm trying to understand how recently created funds work and ultimately derive a sort of a probability distribution for their future returns, by approximating them with indices and then using the ...
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Which features based on orderbook information could be relevant for price prediction?

I have some orderbook data, including 5 ask prices, 5 bid prices, amount of asks and bids for every price, and midprice which is equal to (best bid + best ask)/ 2. I would like to predict absolute ...
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Performance measurement

When I regress the excess performance of a portfolio on the MKT Factor using daily data. I get a Beta of 0.95 and an alpha of 0.00011 that I annualize *252 = 2.77% I know that the annualized return of ...
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1answer
71 views

Factor model for Gold has low adjusted R2

I am trying to build up a factor model for gold. To be able to identify the correct factors, I did a correlation analysis between a few factors vs gold and I integrated this analysis with what I saw ...
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Alpha and returns annualized

Basic question , but if I do a daily regression and get an alpha of 0.00004. Should the yearly alpha be : 0.00004 *100 *252 = 1.008% OR 0.00004 * 100 *365 = 1.46%. What is considered the yearly alpha ...
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How can the different r2 score of an AR(1) model on prices vs. returns be explained

This is maybe a silly question, but I want to understand. As far as I understand an AR(1) model, it is basically a linear regression model with the same but lagged variable, right? However I am ...
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1answer
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Factor Model Regression Market Factor Statistically Insignificant After Adding Extra Factors

I am running a simple 4 factor model which includes the factors: Benchmark (Market - FortyConsumerSixtyHealthcare), SMB, HML and MOM. When I simply apply the regression to the portfolio returns and ...
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How can you use factor modelling to improve your current portfolio [closed]

Firstly let me apologise if this has been asked on on here before - I went through some of the factor modelling post on here but I've struggled to find the answers. I am new to the quant world and I ...
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Reintegrating Fractionally Differentiated Time Series Prediction

I am working on a supervised learning approach to Time Series Regression, and am currently investigating fractionall differentiation (optimizing the stationarity/information tradeoff) discussed ...
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Is there a noticeable difference in making scatter plots and regression models with tick-data or with candle data?

I am asking this question because I want to research some variables. An example is the RSI where the current RSI is updated every tick. This means that the value of the RSI is fluctuating a lot inside ...
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1answer
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Low volatility in factor regression

Let's say we are working with the standard Fama-French 3 factor model and we want to add a low volatility factor. Is it alright to add a low volatility risk premium in a model such as the CAPM or FF3. ...
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58 views

What date to pick for regression on global stocks

Let's say I have a return of a stock in Japan that I wish to regress on the S&P 500 index using daily data for 1 year. Since the Japanese stock market has different holidays than the US, the dates ...
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1answer
50 views

does oversampling affect the correlation?

I have a dataset of monthly data. One column is my target variable and all the other are my feature. I have computed correlation between my target and all the other feature and then I made linear ...
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Choice of factor model based on correlation

I have a portfolio of assets. Each assets have been discretionally (based on investment manager experience) related to economic factors like (like exchange rate inflation spread etc). Now for each ...
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In your experience, when trying to predict something that occurs, do you model with a fixed time period?

Let's say you are building a simple model (like the classroom examples) of trying to predict, given past information, if the stock goes up or down in the future. One could, like in classroom examples, ...
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73 views

Adding more factors to Fama French Carhart 4 factor model

Does it make sense to add more factors such as Quality Minus Junk (QMJ) and Betting Against Beta (BAB) in the Fama-French-Carhart model? Also, if anyone can point me to an article it would be ...
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Should Fama-French coefficients be calculated with daily or monthly returns?

I noticed when I regress the return of a portfolio on the Fama French 3 factor model that the value and the statistical significance of the coefficients vary when I use daily versus monthly portfolio ...
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Global portfolio alpha

How does one compute the alpha of a global portfolio. Let's say we are using the Fama French 3 factor model and we have a portfolio of 50% US stocks and 50% German stocks. Should the regression be ...
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How to do Fama French (1993) cross sectional regressions? A few questions

I am still relatively new to asset pricing factor models and have a few questions about my current empirical study. I would be very pleased if you could help me. I have created a new factor which I ...
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What's the industry standard/typical way to model contango or futures spreads?

If you want to include futures spread either as a response or predictor, I would imagine you also need to include time to expiration somewhere in your model. What is the industry standard way to ...
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How do Hedge Funds account for returns from short selling?

I was going over my notes from an Asset Pricing module yesterday and came across something interesting I hadn't thought about in a while. It was how Hedge Funds can over inflate their performance by ...
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Constructing a replicating portfolio of a long-only strategy using long-short factors

Lets say I want to estimate a replicating portfolio by doing a linear regression between the returns of a long-only portfolio and several long-short factors like Fama-French 5-factor or Betting ...
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24 views

PanelOLS or simple OLS?

It is probably a silly question but please assume the following. I gather hedge funds returns and I want to do a regression against few dependent variables (FF factors, etc.). In essence, I get a ...
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Tradeoffs of using Loess regression to fit random walks

I am curious if anyone has had much experience attempting to predict random walks using Loess regression or a variant of local statistical methods.
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How to set up the dummy variable for OLS event study regression

I've been going back and forth with how I should work to find an event effect. would be so grateful for some clarification. I have daily time series of exchange rates for different countries ( 1 for ...
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1answer
36 views

How do you build a model with uncertain time range?

Let's say you want to test the hypothesis that given a signal reaches some threshold, some asset will have some return over the next period. Here we have two unknowns. One, the value of your ...
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understanding the linear constraint on a regression performance report

I am trying to understand a regression performance attribution. The problem the code solves is shown below. min 0.5 * x'Hx + f'x st. Ax <= b So I have n ...
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1answer
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Existing research on fund performance contribution analysis?

Consider the following problem: You would like to understand how a particular Multi Asset Class fund is invested (ascertain the weights attributed to each asset class) You have at your disposal a ...
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Results of Fama french three factors model and Fama MacBeth cross sectional regression

I am doing research work on “Idiosyncratic volatility and stock return”. I have calculated Idiosyncratic volatility with the help of Fama french three factor model. IV is defined as the standard ...
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1answer
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in-sample vs. out of sample conundrum

Lets say I for work with data from 2000-now in one sample (in-sample), and lets say that my out-of -sample will be from 2000 to 1950. I will then get some type of out-of-sample result. If i then run a ...
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Why use square root of companies market cap in the WLS matrix

When doing a regression based performance attribution I see that people normally use WLS. So that both our independent and dependent variables are multiplied by our WLS matrix, which is a diagonal ...
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Results of Fama MacBeth regression

I have run Fama MacBeth cross section regression of of Excess Return of stocks on Idiosyncratic volatility, the log of market capitalization, book to equity ratio and Beta. I'm getting all significant ...
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“using daily returns over rolling annual periods from the regression”

I stumbled upon the following sentences many times in different papers, all describing an approach for the same experiment: They try to calculate sensitivities (Beta) for different stocks via ...
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1answer
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Regression based performance attribution with dummy variables

I am following some work to do with a regression based performance attribution. The regression is a cross sectional one. The $y$ vector is the risk free return for say 1,000 companies. The $X$ matrix ...
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1answer
68 views

Align volume bars for multivariate analysis

Looking at the book "Advances in financial machine learning" the author proposes a way to sample high frequency financial data in several fashions which are not only the standard time bars. I was ...
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Appropriate regression when multiple dependent values for same independent value

I have a data set which looks as following: Y 1 2 1 1.5 1 2.5 2 5 2 3 3 5.2 3 6 3 6.8 4 6 4 7 And the corresponding plot is: What kind ...
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Beta estimates of Regressions on AR(1) Process

I am currently working through the paper The Myth of Long-Horizon Predictability [1] and I got stuck in reproducing the empirical results in Section 1.4. It is my understanding that time series of ...
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Python Panel Data Regression for OUP Calibration

I have a model for predicting stock returns that classifies stocks as overbought or oversold, kind of like an RSI. It follows an OUP and I am curious about my $\mu$, $\sigma$, and $\kappa$ parameters, ...
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CS-Regression Three Factor Model

1# When would the three risk factors market, size and value be priced in the FF Three factor model when performing cs-regression? How do you know that they are priced? 2# How would it be possible to ...
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What value to put in lm() function when testing for cointegration (R)

I'm a CS student working on a financial computing project + have a question regarding cointegration testing using linear regression with the lm() function. https://www.rdocumentation.org/packages/...

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