Questions tagged [time-series]

A temporal sequence of events measured at discrete points in time.

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9 views

Electricity Futures Risk Premiums With ARIMA

I am attempting to model long-term electricity prices using today's futures prices. Unlike most futures, electricity is delivered over a period of time (usually a month), rather than at a point in ...
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34 views

High Frequency financial data [duplicate]

I really need high frequency data for my thesis. The data should contain the following columns: Time with format: yyyy-mm-dd h:mm:ss; Price; Bid price; Ask price; Bid volume; Aks volume; volume I ...
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How to merge two sets of timeseries together while maintaining the same returns?

I have a question about merging two sets of timeseries without causing much havoc. I have to merge dataset 1 into dataset 2. Problem is: The levels are different. (Ex: dataset 1 is moving between 2 - ...
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32 views

How do I deal with nonexistant data in a time series with an irregular frequency?

I am trying to do some time series analysis on the margin resulting from three specific commodity futures contracts and ultimately forecast the margin. The margin is calculated as M = F1 + F2 - F3. I ...
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46 views

Modelling Skew when using ARMA Time Series

I am currently modelling financial time series via ARMA processes, but I have reason to believe that in addition to significant autocorrelation, the time series also exhibit skewness. Is there a way ...
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Examining individual portfolio allocation changes over time

I am currently working with a pretty large panel dataset containing the investment holdings of many individuals over time (i.e., for each individual I know the positions per stock over time). I was ...
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1answer
45 views

Should a stock with high return autocorrelation be weighted more heavily in a portfolio?

Some say the presence of autocorrelation (aka serial correlation) in a stock's financial return time series helps with forecasting its next-day movements, unlike a stock that has low serial ...
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33 views

Generate random timeseries in Python

I'm trying to test a particular trading strategy under different assumptions and would like to do so on different random time series. I would like to be able to specify the following: Start price End ...
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35 views

Is it possible to use volume/dollar bars instead of time bars when analyzing multiple variables?

I recently read Marcos Lopez de Prado's book "Advances in Financial Machine Learning" where I was introduced to the concept of using volume/dollar bars instead of time bars. As far as I ...
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2answers
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Storing options EOD time series in Flat Files

I have purchased data for EOD settlements of options prices for USA futures for personal use. I will not need multiple user access or real time access. I am not an expert programmer but use C# and R ...
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Computing statistics from historical returns

I'm reading age 35 of "Advances in Machine Learning" by de Prado. Consider an IID multivariate Gaussian process characterized by a vector of means μ, of size Nx1, and a covariance matrix V, ...
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54 views

Cannot achieve generalization of machine learning model

I'm working on a balanced, binary classification problem in a time-series (financial) dataset. I am using K-fold cross validation that is adapted for time-series (so that I'm never using future data ...
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76 views

Best method to determine future success or to determine best linearity?

Long time viewer, but first time poster, so excuse me if i'm in the wrong place please. Anyway, I am working on a project that is pretty interesting. Through data mining, I am able to gather a ton of ...
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54 views

Estimating the variance of returns with aggregated data

Say I have an asset return time series: Jan2020: -5% Feb2020: +5% Mar2020: -5% Apr2020: +5% May2020: -5% Jun2020: +5% Q3 2020: +20% Oct2020: +5 Nov2020: -5 Dec2020: +5 Note that 3 months of data is an ...
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74 views

Style analysis and Kalman Filter

I am trying to implement a code that uses Kalman filter to improve the performance of traditional style analysis. I have come across a paper called "Return based style analysis with time varying ...
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31 views

Defining the Average Length of Business Cycle using AR(p) model

I'm currently reading through Analysis of Financial Time Series by Ruey Tsay. The AR model is introduced in chapter 2 and its properties in 2.4.1. The difference equations are explained and then its ...
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1answer
56 views

Predictive power of lagged features [closed]

I have to build a classification model to predict recessions. I have selected a set of features (some are economic and some are financial). I have noticed that it is good pratice often to add to the ...
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Interest Expense Optimization

So I have a problem I need to solve and no idea how to approach it. Its a verbal problem without any specific numbers given except for those below. So it is up to me to determine how to structure the ...
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1answer
64 views

Simulating correlated Geometric Brownian Motion with lag

I know that it is possible to simulate two correlated GBM in e.g. Matlab (Generating Correlated Asset Paths in MATLAB) based on cholesky decomposition. However, they take as input the correlation ...
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39 views

Do you need multi-period ahead covariance forecast, in order to construct portfolios with weekly/monthly rebalancing?

Suppose I want to rebalance my portfolio each week. Do I then need weekly covariance forecasts, from some multivariate volatility model to do this? Ie. Insert the weekly covariance forecast $\Sigma_{t+...
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29 views

Squared Residuals equal Variance of Dependent Variable (ARMA-GARCH)

My understanding of ARMA-GARCH models for a variable $X$ is as follows: I estimate a conditional mean of a variable $X$ by use of the ARMA part of the model. I estimate the conditional variance of ...
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29 views

Correlation of financial returns: how to account for different frequencies?

If you had to calculate a correlation between two financial return time-series, on what frequency would it make sense to do so? Yearly returns? Monthly? Weekly? Daily? What is the norm here? The issue ...
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30 views

Verifying period parameter selection in the seasonal decomposition (using moving averages) of time-series data

I am using the seasonal decomposition method from the statsmodels package to decompose time-series data into the trend, seasonality, and residual components. The issue is, I am trying to find a sound ...
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Cointegration where first differences are not jointly stationary

Note: This is a crosspost from this post on cross-validated, where it did not receive an answer. I thought I might have better luck here. I am looking for a rigorous and general treatment of ...
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34 views

Fitting ARMA Model on Short Time Series with Trend

I have a time series of returns, which has a clear trend in it, I give as an example the following example time series: ...
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1answer
111 views

Optimize Bollinger Bands Strategy

I was proving a very simple strategy with Bollinger Bands for a intraday timeframe (1 minute) that buy on lower band and sell in a higher band (Very common strategy), but in backtesting in E-Mini SP ...
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85 views

How to model financial HFT time-series data with multi scale autocorrelation

I work with tick level time-series univariate prices data. Tick level means that there are hundreds to thousands observations per second. The observations are timestamped, so one can use both wall ...
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1answer
110 views

Long-Term Energy Price Modelling: Log Returns, Distributions, Time-Weighting

I wish to forecast energy prices in the long-term (ca. 20 years) for energy-efficiency investments. While I understand that the energy carriers are particularly sensitive to external (geo-political) ...
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20 views

How to estimate Hodrick Standard Errors in R

Does anyone know how to implement Hodrick Standard errors in R? I could not find any package for it in R. Is anyone aware of the same or any open source code that implements it? I want to use Hodrick ...
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24 views

Is it possible to apply PCA to a time-series of covariances?

I understand that Principal Component Analysis (PCA) can be applied for cross-sectional as well as for time-series data. Nevertheless, I am trying to figure out if there is anything wrong with ...
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27 views

Why isn't prepayment modelling done on actual prepaid amounts?

When modelling prepayments in Securitized products, why is it that the standard model involves a transition matrix (Markov Chain) framework, where the probabilities of transitioning between different ...
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36 views

Any experience with synchronization of time series to adjust for daylight saving time?

I am currently working on a trading project where I essentially have two time series. One is high frequency intraday trading data that does not take daylight saving into account. The second one is a ...
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Is it possible to compare Forex data to similar random time series to measure how predictable it is?

In relation to my previous question (Who influences Forex prices and by how much?) I have an raw idea how to determine how much is Forex influenced externally and how much is its behavior given by its ...
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34 views

Simulating two correlated time series using GBM [duplicate]

My situation is the following: I have two time series TS1 and TS2, whereas TS1 is a stock price. According to literature, TS2 is positively correlated to TS1. Furthermore, since TS1 is a stock price, ...
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37 views

Chinese Stock Exchange Indexes data and descriptive statistics

I am trying to reproduce the following paper: https://link.springer.com/chapter/10.1007%2F11600930_48 In this study, daily prices from January 4, 2001 to December 31, 2004 for Shanghai Stock ...
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2answers
82 views

Spectral clustering in finance

What are some examples of applying spectral clustering to financial times series data or other areas of finance? Why spectral clustering was used for each application rather than other types of ...
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1answer
53 views

Clustering the observations in a price or returns series [closed]

Given one stock, what value would there be in clustering the individual sample observations within that stock's historical prices series, or its return series? is univariate clustering done in finance?...
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Applying GARCH to Panel Data

I have a panel consisting of some quantity - say earnings/cash flows/or something similar. I am interested in forecasting the volatility that is inherent to that respective measure. In a single time ...
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176 views

Does the Shannon entropy of stock returns change over time?

Shannon entropy, $H(X) = -\sum_{i=1}^n p(x) \ln p(x)$ is a probabilistic measure of randomness or disorder within a random variable's probability distribution or histogram. If we take rolling window ...
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43 views

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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Models that can improve FHS (with possible residuals manipulation)

The Filtered Historical Simulation (FHS) is a tough benchmark. By: choosing among the most complicated ARMA-GARCH variants with automatic model and lag selection, manipulating standardized residuals ...
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Preferred stock volatility model [closed]

If I want to forecast stock volatility, what would be the best GARCH model and why? (ARCH, GARCH-M, IGARCH, EGARCH, TARCH etc)
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58 views

Extract individual currencies

I have timeseries for a bunch of currencies. For example, USD_NOK, EUR_USD, EUR_NOK, EUR_SEK and so forth. About 75 of them going back about 20 years in Pandas. My goal is to isolate each currency ...
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3answers
82 views

Change in variance time series

I am analysing a time series (stock returns) and I am trying to check whether variance in the second half of my sample is different from the first half. I assigned a period to the observations. Here ...
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79 views

Variance Ratio Test shows mean-reverting trend but Hurst exponent is greater than 0.5

I believe Hurst Exponent greater than 0.5 indicates persistent series, meaning the values are not mean-reverting. However, when I run a variance ratio test, I get a graph clearly showing mean ...
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1answer
93 views

Transforming a time series

I have a time series that displays time varying volatility how would I take this time series an turn it into a more stationary process this is what the time series looks like , if one can provide r ...
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1answer
69 views

comparing volatility and correlation over time

I'm trying to figure out if some emerging markets change over time. First of all I am going to check for changes in volatility. What would be a good method to do this. And do you suggest comparing ...
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44 views

Price volatility short-term (10 seconds) forecast

Dataset: list of all realized trades (BTCUSDT) from a certain cryptoexchange with timestamps (15 days worth of data) Problem: predict the "price volatility" (standard deviation of realized ...
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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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Athens Stock Exchange GARCH-M (Paper replication)

I am trying to replicate one part of a paper which tries to model the Athens Stock Exchange daily returns. I do not have the original dataset, so some differences are expected, but when I fit the ...

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