Questions tagged [time-series]

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

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37 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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79 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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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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21 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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25 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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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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17 views

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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25 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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34 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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40 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
50 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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26 views

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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162 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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34 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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15 views

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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34 views

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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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
74 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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55 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
92 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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39 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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27 views

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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Combining multiple securities' Net Asset Value time-series into one total NAV series

I have a number of individual securities that each have a Net Asset Value (NAV) time-series. For example: ...
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22 views

Use of ugarchroll vs ugarchforecast: setting parameters

I would like to generate 21 day ahead forecast volatility with ugarchroll. I know it is similar to ugarchforecast with the exception that ugarchroll is a rolling average which considers initially the ...
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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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26 views

BEKK Garch for time-varying beta in python

I am currently trying to analyse stocks of the S&P500 for their time-varying beta using BEKK Garch in python(jupyter). Unfortunately, I can't find any good packages and the documentation for bekk ...
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3answers
94 views

Consistent offset/lag in time-series prediction using Neural Network (all code provided)

I'm using a neural network (keras package) to predict Bitcoin prices 48 hours in advance. The issue is that for some reason, my predictions are "correct" but they are lagging behind the true ...
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47 views

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
60 views

Do stationary prices need to be differenced for VaR?

I have a time series of electricity futures prices that I have shown to be stationary via the Augmented Dickey Fuller test (alpha = 0.05). Does that mean that, in calculating their individual values-...
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1answer
56 views

Working with 1 minute bar returns - do I throw out the first return of the day?

I am doing some academic work and using 1 minute bar data. I am wondering if when calculating the return time series, do I need to throw out the first return of the day because it is the return ...
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38 views

how to interpret the results of a GARCH model fit R/python

I have got the following output from a gjrGARCH model, and I need help to interpret it in order to decide whether it is already a good model and proceed with the forecast. ...
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2answers
66 views

How to use autocorrelation plot to interpret time series data?

how can we use auto correlation plot or correlogram to interpret time series data? I have 6 different acf plots (a,b,c,d,e,f), from this 6 plots what kind of informations and patterns can I identify? ...
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27 views

What can one do with cross-sectional relationships?

This is somewhat of a broad question, but I think we all would like to find signals that predict something in the future. However, often times, we are just left with cross-sectional relationships (...
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93 views

How to connect Bloomberg's xbbp api to “Bloomberg Anywhere”

Due to COVID's remote work situation I found myself unable to access my physical terminal so I've had to use bloomberg anywhere (bba), the issue I'm having is that when I try to use python's xbbg on ...
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53 views

Modelling volatility for higher frequency data

I'm doing some academic work on volatility forecasting. I've got 1-minute bar data. It is not clear to me what model is best suited for forecasting volatility when higher frequency data is available. ...
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38 views

Non-Linear Time-Dependent Volatility

My data consist of monthly electricity futures contracts. Unlike other commodities, electricity is delivered throughout a month (rather than on a specific date), which means that, as the active month ...
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1answer
48 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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19 views

Interpretation of Impulse Responses of VAR

Sorry for the dumb question. My model includes oil prices in level. So, for example CPI is log differences. I calculated IRFs of one standard deviation shock of real oil prices. How should I interpret ...
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53 views

Optimal Change Point Detection Problem for a timeseries

W. T. Ziemba, S. Lleo and M. V. Zhitlukhin suggested an Exit Model for selling an asset based on Change Point Detection Theory from the field of Statistical Quality Control https://ideas.repec.org/h/...
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1answer
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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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24 views

How to Compute the Return for a Series of Investments with Payouts?

I am looking for a metric to track the performance of investments in a security over time. I know what I have in mind but I am not sure how to map it onto a known metric. I want to answer the ...
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50 views

Cumulative returns are more correlated than non-cumulative

I was just comparing two daily returns series and noted that the correlation between them is a lot higher if they are cumulated (about .95 for cumulative returns, vs .15 for non-cumulative). I feel ...
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65 views

Conditional and unconditional variance, autocovariance and autocorrelation of an ARMA process

Given an ARMA(1,1) process $x_t = a + bx_{t-1} + \varepsilon_t + \theta\varepsilon_{t-1}$, how can we find the conditional variance, i.e. $Var_{t-1}(x_t)$, find the unconditional variance, i.e. $Var(...
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1answer
90 views

Why are my Neural Network predictions “correct”, but offset from true value? Not using any past lagged values

Please bear with me through the whole question - I just want to make it very clear what I've done so far and why I'm so perplexed. I am working with a neural network with the Keras package in R, ...
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19 views

Do volume/dollar bar series always have less observations than time (bar) series?

Traditionally, financial returns are derived from prices that have been sampled based on constant time intervals. These are known as time bars, and a series of returns based on time bars are what we ...
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13 views

How to simulate the cross-section

I am looking to simulate the whole cross-section of daily return series for 20 to 60 days. The purpose is to test some risk measures based no maximum drawdown. Thus, it needs the whole time series. ...
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47 views

Using unsupervised classification to find support and resistance levels

I do not have a specific question, it's more of a general & conceptual one. What would be the optimal approach to finding support and resistance levels? Have you approached this problem ...

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