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The science that describes the management, creation and study of money, banking, credit, investments, assets and liabilities.

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Intuition behind unit roots in practice

One area where the application of unit roots to time series modelling seems very intuitive is in climate change: carbon dioxide stays in the air, so past shocks (size of flow) have a cumulative effect ...
ABCBAA's user avatar
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Information coefficient as loss function of XGBoost

I am trying to train an XGBoost regressor for stock price prediction. I want to customize the objective function to be Information Coefficient (IC). The definition of IC is the Pearson correlation ...
atlantic0cean's user avatar
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ML on Vienna Stock Exchange: Predicting hypes for the ATX index and conducting sentiment analysis on the top listed companies [duplicate]

Hello everyone and nice to meet you! :) I am new to this forum... I would like to practice on ML and create a model which predicts stock hypes for ATX index (Austrian Traded Index) and detects the top ...
user415686's user avatar
1 vote
1 answer
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Derivation of a dynamical Generalized Pareto distribution

I'm currently reading a paper for my master thesis on the tail index estimation for asset returns using the peak over threshold method. In this paper the authors introduce the cumulative distribution ...
data_science_101's user avatar
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Regressing time series of continuous proportions Y(invested in different buckets) against X (prices) variables

I am not sure of what model need to be applied in my case. So my goal is to model the below data. I have the monthly deposits data from 2001 till 2024 for this analysis. Each customer can invest in ...
choppalli vaishnavi's user avatar
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9 views

Interpretation and Analysis of a Multivariate Threshold Autoregressive Model

I'm looking to study the asymmetric affect a market rate, like the Fed Funds rate has on an interest rate. In other words, I would like to study the response of interest rate adjustments in different ...
dsupin's user avatar
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Autocorrelation and ARMA model

Consider the market model for security $i$ $$ R_{i,t}=α_i+β_i R_{m,t}+e_i $$ I'm estimating the parameters of this model (alpha and beta) using OLS. However, the Breusch-Godfrey test indicates the ...
Mattia's user avatar
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2 votes
1 answer
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Backtransforming a probabilistic forecast?

Let's say that we have a probabilistic forecast for the future percentage return of an asset in the form of a probability density, $\hat{R}_{t+1}$. If our initial goal was to create a probabilistic ...
QMath's user avatar
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Infimum of a set - Value at Risk

I don't understand these semantics. Can somebody tell me with easy words and some other examples how to understand this last equation and why it equals 0? How to understand this colon after variable '...
wojtek5739g's user avatar
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23 views

Deriving the multivariate asset returns model and interpreting cholesky factorization

I am trying to understand the multivariate asset returns model for a portfolio of assets from chapter 4 DCC-GARCH of Orskaug "Multivariate DCC-GARCH Model With Various Error Distributions" (...
Jose_Peeterson's user avatar
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How to test Markovian property in a financial time series?

I want to build a Markov Chain model for a financial time series to determine transition probabilities from one state to another. The underlying assumption is that series obeys the Markovian property. ...
Sane's user avatar
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Stock clustering based on fundamental reporting

I want to made a stock clusterization, based on their fundamental features from companies quarter reports. I collected quarter reports from 2018 to 2022. Some companies have reports for all quarters ...
TImur Nazarov's user avatar
3 votes
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40 views

Event studies: does test power depend on the window length?

I am reading Cambell, Lo & MacKinlay "The Econometrics of Financial Markets" (1996). Chapter 4 covers event studies. Section 4.6 provides power analysis of tests discussed in section 4.4....
Richard Hardy's user avatar
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Stationary Bootstrap Block Size Impact on Portfolio Simulation Results

I'm analyzing simulated portfolios generated using the stationary bootstrap method proposed by Politis et al. (1994). This method is expected to be robust to the choice of average block size, as it ...
pinpss's user avatar
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Heteroskedasticity Adjusted Correlation Coefficients

I've been reading Forbes & Rigobon (2002) "No contagion, only interdependence" article, in which they suggest to adjust the correlation coefficients for heteroskedasticity. I can't ...
krauuuus's user avatar
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30 views

Panel vs Pooled OLS

My sample comprises of data on accounting performance of companies that had their IPOs between 2009-22. I want to examine if companies which had more foreign investor participation in their IPOs ...
roshnigarg's user avatar
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Determining values for Default Correlation between two companies

I'm a second year undergrad university statistics student working on a real life project for IDB, a bank in Latin America. However the project is really above my level, and I could do with some help. ...
Henry Lavender's user avatar
2 votes
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185 views

Are Purging and Embargo better than TimeSeriesSplit?

It is well known that the classical k-fold CV does not work well when it comes to time series data. I recently found two methods called Purging and Embargo, which aim to modify the k-fold CV, so that ...
Mr. Ivan's user avatar
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Interpolation on bond issuance data

I am currently working on an analysis on bond issuance during the COVID pandemic. I will run a linear regression of spread on multiple bond issuance characteristics but also on multiple firm key-...
Felipe Ramos's user avatar
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What is this method name for comparing two financial time series by their difference (subtraction)?

I am trying to find a reference/name for what I am doing for explaining it in an academic work. My scenario is that: I have financial time-series A and B. I want to answer if A outperforms B or vice-...
Reuel Ribeiro's user avatar
1 vote
2 answers
48 views

Gridsearch on ARIMA favours random walk

I am working on a time-series forecasting problem with ARIMA. Since long-term predictions were not good, I've started using a "rolling ARIMA" like explained here ...
nico_so's user avatar
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1 answer
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What studied statistical model (if any) fits this application?

I'm having trouble identifying what statistical model or methodology is suited for my application. My situation is as follows: I want to create a stock trading agent that trades a single stock-cash ...
QMath's user avatar
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1 answer
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Success probability when we have expected return and volatility

I am reading Taleb "Fooled By Randomness", and the author says that a 15% return with 10% volatility translates to 93% success in a year and 50.02% success in any given second. Could someone ...
manish's user avatar
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9 votes
1 answer
84 views

Testing a multifactor asset pricing model against another one

I have a sample of $(Y_{i,t},X_{1,i,t},X_{2,i,t})$ for $i=1,\dots,N$ and $t=1,\dots,T$. I want to figure out which data generating process (DGP) it comes from, DGP1 or DGP2. DGP1: $$ Y_{i,t}=\lambda_0+...
Richard Hardy's user avatar
4 votes
1 answer
13 views

Incorporating idiosyncratic risk as a pricing factor with GMM

Originally I posted this on Quantitative Finance SE here but got no response. Months later, I am posting it here hoping for better luck. Suppose we are given a dataset with $T$ time periods and $N$ ...
Richard Hardy's user avatar
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21 views

Understanding clustering using oblique decision tree

I would like to understand the following post with regards to the code below. https://www.kaggle.com/competitions/optiver-realized-volatility-prediction/discussion/276137#1559582 Initially, Principal ...
Jose_Peeterson's user avatar
5 votes
2 answers
336 views

Should the Wilcoxon Rank sum test be used for testing the mean difference significance?

I was looking replicate the results of the paper DOI:10.3905/jpm.2014.40.3.087 (Exploring Macroeconomic Sensitivities: How Investments Respond to Different Economic Environments, Ilmanen Maloney Ross ...
Luca Dibo's user avatar
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27 views

A small part of my data is non-stationary, how to solve the issue?

For a project, I have to produce an ARIMA forecast of Boeing's stock returns over the last 10 years. I've tried to check stationarity of data with ACF first and found out that lag 1 is statistically ...
Gytz's user avatar
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0 answers
7 views

Time based cross-validation for EOM patterns

I want to evaluate different models (ARIMA, MLP, LSTM, regression, etc.) on their performance to predict/forecast stock prices in a period (horizon) of 7 days around month-end. The data for these ...
koder124's user avatar
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22 views

Is there any bias introduced by evaluating a model and decisions based on this model on the same data set?

As an example, let's say we have some financial time series such as closing prices of some stock and we would like to evaluate the ability of different models to forecast future closing prices as well ...
QMath's user avatar
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1 answer
41 views

Does variance depend linearly on beta?

Under the CAPM, consider an investment with stochastic cash flows. Does the variance of the return on the investment depend linearly on beta? if not, why so?
Piercarlo's user avatar
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82 views

Constrained regression with multiple sum=0 constraints

this is my first post on this website so please advice me if I can add any relevant information. I'm running into a problem of how properly set up a model by using the Sum to zero constraint in Python....
Antonio Amoretti's user avatar
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0 answers
12 views

Hierarchial clustering given a list of banking syndicates

I have a list of banking syndicates (groups of banks), and I'm trying to do some hierarchical clustering on it to gather if there is some connection between them (e.g. if lots of syndicates share the ...
apg's user avatar
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0 answers
73 views

Identifying stress in financial stress index constructed using PCA using Hodrick-Prescott filter

I am reading: https://www.econstor.eu/bitstream/10419/128519/1/ewp-356.pdf The footnote on page 19 says: The trend was derived using the Hodrick-Prescott method where the smoothing parameter λ is set ...
user2338823's user avatar
1 vote
0 answers
78 views

How to create representative training, validation, and test sets when working with time series data?

In my application, I am working with a relatively long time series of daily market index percentage returns (many years) and am trying to model the dependence structure of the returns from a pure time ...
QMath's user avatar
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1 vote
0 answers
10 views

Expected Regression Coefficent in return space

Say you are running a regression on predicting the future 1 second return(new price / curr_price - 1)/ using the return of past 1 Milli second, what is the expected range of coefficient in this case? ...
DarkKnight's user avatar
1 vote
2 answers
70 views

Measuring Portfolio Volatility when Risk-Off

I'm trying to calculate the annualized volatility of a single-asset trading strategy that is either 100% long or 100% cash. Imagine a risk-free asset with a guaranteed and fixed daily return of 0.1%. ...
Sir Fart-A-Lot's user avatar
1 vote
0 answers
17 views

Evaluate Value at Risk (VaR) models with different VaR backtesting approaches - averaging p-values?

I estimated the Value at Risk of a time series of log returns with different approaches and models. Now I want to compare the models and choose the model that most accurately estimated the Value at ...
Isabel's user avatar
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0 votes
0 answers
18 views

Choosing one method for modeling Value at Risk (VaR) over another - determining the "best" model

I estimated the Value at Risk of a time series of log returns with different approaches and models. Now I want to compare the models and chose the model that most accurately estimated the Value at ...
Isabel's user avatar
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0 votes
0 answers
60 views

How to normalize slope of historical financial data?

Im trying to find a method to normalize the slope value for the historical net profits of many companies. But the problem arises when certain companies are clocking profits in thousands, and some in ...
maksumit's user avatar
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0 answers
22 views

Insignificant confounder

I have a simple regression of price on growth: $price_i = \beta_0 + \beta_1growth_i+u_i$ In this simple regression, the p value for $\beta_1$ is highly significant, but I am worried that there is a ...
rudinable's user avatar
0 votes
0 answers
39 views

How to properly add dummy variables as controls when the independent variable is a dummy variable?

I am writing a thesis where I investigate whether ESG/sustainable funds' decision to invest in fossil fuels/weapons affects fund flows. I am regressing a fund flow variable on a dummy variable x which ...
Christian's user avatar
1 vote
1 answer
36 views

Comparing different methods for modeling Value at Risk (VaR) - understanding VaR backtesting results

I estimated the Value at Risk of a time series of log returns with different approaches and models. Now I want to compare the models and find the model that most accurately estimated the Value at Risk....
Isabel's user avatar
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3 votes
1 answer
44 views

Reconciling Nondeterministic and Probabilistic Decision Rules

I've been getting a bit stuck recently on how to reconcile the two seemingly-competing ideas of nondeterministic and probabilistic decision rules. As an example: Let $t=0$ denote the current time and ...
QMath's user avatar
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1 vote
0 answers
126 views

Should standardizing a vector of data lead to a unit length vector? [closed]

I am reading "Introduction to Econophysics" by Stanley and Mantegna and I found the following in Chapter 13. I can't understand why the 2-Norm of a vector standardized by subtracting the ...
lotak's user avatar
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1 vote
0 answers
29 views

What color financial time series are there? [closed]

There is a folklore white noise hypothesis related to (and equivalent to some forms of) the efficient market hypothesis in finance -see references below. But are there some asset pairs whose return ...
plm's user avatar
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2 votes
1 answer
434 views

How can I interpret the below GJR-GARCH model in terms of "leverage effects"?

I'm very new here and am struggling to interpret the model. Please help me in layman's terms. ...
Rijia's user avatar
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1 vote
1 answer
65 views

How can I combine multiple regression models? [closed]

I'm trying to predict some financial feature (continuous) and there are two or more good regression models. Is it possible to combine multiple regression models? If so, what kind of method is it ...
070701's user avatar
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1 vote
1 answer
37 views

If returns are random variables, then how can CAPM be posed as a simple linear regression?

The Capital Asset Pricing model proposes that, $$ R_i=R_f+\beta(R_m-R_f) $$ where $R_i$ is the return of the i-th asset, $R_f$ is the risk-free rate and $R_m$ is the Market returns. $\beta$ is ...
Who cares's user avatar
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0 answers
171 views

Loss function weighting in regression when the target varies orders of magnitude between groups

I have a dataset with 200 groups, and 50-300 observations per group. The target I'm trying to predict is a strictly positive financial metric, which varies 5+ orders of magnitude between groups but is ...
Marcin Kozłowski's user avatar

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