Questions tagged [time-series]

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

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How to implement rolling granger causality

I am investigating two time series where the first is the daily closing stock price changes and the other is the daily changes in the PCE index. I want to investigate how much the PCE index explains ...
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Reasons for negative autocorrelation of forward prices

I am working on each trade day's forward prices of gasoline. I noticed that the autocorrelation at lag 6 is significantly negative. I know how to interpret negative autocorrelation in a statistical ...
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Regression taking in account size of earnings surprises

I'm trying to regress earnings surprises on variable x. However, absolute earnings surprises are mostly influenced by company total earnings and the number of shares outstanding. So I can't just use ...
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Forecasting VIX with GARCH(1,1)

Aim: Forecast VIX using GARCH(1,1) Reason: I want to be able to forecast VIX on several horizons, in order to be able to forecast the SP500 index through linear regression. Tools used: Python, ...
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Application of Gramian Angular Field to financial series?

I found this method to represent time series to improve performance of some ML models, any thoughts about this method? some applications or use cases in financial markets?
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Daily realized volatility and true daily volatility

Can someone help if I am thinking correctly? If $R(t,i)$ is the i'th log-return for $i = 1\ldots,M$ of day $t$ for $t = 1\ldots,T$. Can I assume that the daily realized volatility (denoted $RV(t)$) is ...
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Techniques for proxying time series / stock prices

What are some good techniques for proxying time series? My purpose is for risk management / modelling and I would like proxy to missing series. Given that I also have to account for volatility, ...
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Inconsistency between simulation and the probability of a "stock" hitting take profit before stop loss

Let's assume a stock at time $t$ is worth $X(t)$. If the returns of $X(t)$ are i.i.d. and normally distributed,the probability of $X(t)$ hitting a value $H>X(t)$ before $L<X(t)$ is $\frac{H-X(t)}...
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What are common ways to realistically simulate the stock market using historical market data?

I am currently using the FinRL library to try to automate Trading using Reinforcement Learning. However, I wanted to understand how FinRL simulates the stock market using historical data. I read here ...
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I.I.D log returns. What about their square?

If one assumes the underlying return process is I.I.D, is there a solution to the question of the autocorrelation of squared returns? Thanks.
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Looking for options to visualize large market timeseries data

I have a large dataset that includes my strategy back-test run data. The dataset columns include candle date, close price and many strategy related data. I’ve built a Mathplotlib visualization for my ...
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Filling in between data in finance

I'm trying to create a model on how different factors influence a particular asset. For some of these factors, like inflation, for example, I have monthly data, while for others, like exchange rates, ...
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How to determine which realized volatility estimator should be used?

There are so many realized measure have been invented in the past years like TSRV, MSRV, KRVTH, KRVC... But how to choose them in practice? I know we cannot find the "estimation error" of ...
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2-day ahead prediction of value at risk with GARCH(1,1) in R

Let's say I have a 10 year dataset of Tesla (example) and I am taking the percentage change of lag 2: ...
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Copula Models for Asset Returns

I'm learning about copulas and their applications in finance. When used to assess the dependence structure between two indices for example, can the copula models be estimated directly on the log-...
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How to find out the dates of the different financial quarters (e.g. Q1, Q2, etc.)?

Question: Is there any resource I can use to find a list of dates which constitute the start and end of the 'financial' quarters (e.g. Q1, ..., Q4) for the years 2006 onwards? I know sometimes they ...
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How to compute the combined probability of loss for 2 time series (consisting of historical stock prices)?

May I please ask the community's support with the following problem? I have 2 time series, with approximately 1000 observations each (same number of observations for both). They represent the daily ...
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PCA on portfolio depending on multiple time series

There is extensive documentation about PCA on specific time series (for example the UK yield curve). When you have a portfolio which only depends on the change of the UK yield curve then a PCA on the ...
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Simulating the Value-at-Risk with $t$ distributed returns

I want to understand how the value at risk and the simulating the VaR with simple Monte Carlo method. But I want just a confirmation and are welcome any comments, since I don't have the full picture ...
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Data science techniques for intraday trading

I am a Masters student in data science looking to get into a financial-themed project related to intraday trading. This will not be HFT, so the frequency will be somewhere around 1 or 5 minutes. I am ...
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What does M^L represent over this Sigma?

This is throwing me for a loop. in regards to this passage, does the M^L represent to perform this sum over every "overlapping window" individually? Would this mean "M symbols" are ...
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Conditional Value at Risk using GARCH models

In this paper: https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwjSlIHYnMj1AhWqNOwKHZfHDhkQFnoECAkQAQ&url=https%3A%2F%2Fwww.mdpi.com%2F2076-3387%2F9%...
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How to derive Level 2 Market data from Order book of energy trading market over custom intervals

I am looking for resources which provides details like which model/logic/algorithms being used by Energy Exchange and other OTC market to sequence and display best 5 or 6 bid and offer prices (Level ...
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Time series data for probability of default (or credit ratings)

I'm currently investigating potential correlations among ESG ratings and credit ratings; more in particular, i'm trying to understand whether such correlation evolved during the last 20 (?) years, and ...
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Why is the moving average called that way? [closed]

I am a beginner in time-series analysis. The moving average model uses past errors*parameter, so why is it called a moving average model? It seems counter-intuitive to me. The Auto-Regressive model ...
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How to deal with negative intercept terms on GJR-GARCH(1,1) model?

Recently, I have been studying the relationship between COVID-19 and stock returns using a GJR form of threshold ARCH model. However, I got some unusual estimation results I can't figure out whether ...
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Does it make any sense to normalize returns?

I have been going through a course for Time Series Analysis. First we learned to make returns from a time-series of stock index by (Xt - Xt-1)/Xt-1 . This makes the series stationary, which means we ...
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Persistence and stationarity together in volatility analysis

I am trying to analyse a time series. I want to get only quantitative results (so, I'm excluding things like "looking at this plot we can note..." or "as you can see in the chart ...&...
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Memory effect of log returns of S&P 500

I am trying to reproduce the analysis discussed in https://arxiv.org/pdf/cond-mat/9905305.pdf where they use high-frequency data (1-minute frequency) of S&P500 from 1984 to 1996. In particular, ...
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Machine learning models for sequential truncated time series ahead of a series of events

After some unsuccessful searches, I am turning to the community for the following issue: Assume I am interested in the dynamics of a stock prior to FOMC meetings. I am interested in the 20 days prior ...
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Disecting a log diff transformation for time series analysis and prediction

I have been working in a predictive ML model that uses financial time-series as predictor variables. In one of the academic papers I used as reference, and to do feature engineering for building the ...
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Calculate and study volatility time series

I am trying to study a time series. I have 10-year daily close prices for some stocks, so my time series is very simple: each day I have a close price for my company. The question is: how can I want ...
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How to create three variable system + test the hypothesis that the VAR residuals from two variables' equations can be treated as "structural" errors

I am currently doing an econometrics assignment and am completely stumped on a question. I have screenshotted the question and pasted below. Both questions are to be answered on EViews; having looked ...
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How is a return-adjusted nearby created?

I am reading Value-at-Risk Second Edition – by Glyn A. Holton https://www.value-at-risk.net/futures-nearbys-and-distortions/ From 6.6.1 "The standard means of obtaining continual time series from ...
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Suggestion on the models to estimate public indeces future returns

I would like to to estimate the future returns of some public indeces. I have several of them so it is a multivariate problem. The series are quarterly and the estimation should be of at least 15-20 ...
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Do we need to fractionally differentiated all features in ML prediction for finance time series?

I am reading Prof. Marcos Lopez de Prado's book Advances in Financial Machine Learning, and have a question on feature engineering. On page 88, he says: In practice, I suggest you experiment with the ...
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Is it safe to assume inflation rate and treasury yields are stationary?

I have YoY percent change in CPI and the nominal 10 year Treasury yield. I want to run some correlation analysis between them but worry they are not stationary. I ran a DF test and found that, ...
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Exponential Moving Average Data Set Average Age

Why is the smoothing coefficient of the EMA (exponential moving average) calculated as: $${\displaystyle \alpha =2/(N+1)}?$$ Brown R.G, on page 107 of "Smoothing, forecasting and prediction of ...
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Is this pattern for high trade prices in the NKE NYSE data correct?

The question is whether the pattern described here actually exists in the NYSE historical data for NKE (Nike). In over 63% of cases, HighTradePrice achieved between ...
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Forward Looking vs Backward Looking Returns for Forecasting

I have a general question about the best way to setup returns for a forecasting problem. Most of the time I see issue of studying returns carried out with the following formula: $ r_{t, k} = \frac{r_{...
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Good (non-random walk) financial time series to perform forecasting on

I would like to start with a brief caveat, namely that I am by no means a domain expert in financial markets. Therefore the question I am asking may sound silly to a practitioner but I am asking it ...
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An Intuitive Explanation of Multifractality in Financial Time Series

Can anyone please give an intuitive explanation of multifractality in financial time series? Most definitions I came across are either purely mathematical or not in relation to finance. As for the ...
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Information content of seasonally adjusted vs non-seasonally adjusted economic time series

I want to use the history of an economic time series to anticipate the behaviour of the economic variable. Let's suppose that I have monthly time series data for the past N months and I want to think ...
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3 answers
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database for economic & finance timeseries

I am looking for a technical solution to store economic and financial timeseries (nothing intraday for now, just daily/weekly/yearly) Most timeseries database I find do not seem to take into account ...
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Computing the average deviation range in a mean reverting series

Given a mean reverting time series, what's the appropriate measure to use to compute the range it deviates by before reversion? Assuming normal distribution, taking standard deviations of the actual ...
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Looking for a measure of a simple Trend and Strength Indicator

I'm not literally a Quant but rather an analyst working in Process Control and I have a problem that I think could be solved with the Financial tools. Basically I have a matric called DPM (Defect Per ...
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How to generate normalized factor scores for beta exposure

I'm working on building a time series momentum model (TSMOM) based on price alone for currency pairs. I'm implementing a paper that produces a buy/sell signal based on geometric brownian motion and a ...
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Moving Average Window Size Determination

Is there a "correct" way of determining a moving average window/smoothing parameter (or at least a starting guess for a financial time-series? I understand of course that in some sense, ...
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1 answer
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Understanding Volume Bars Threshold

I have been reading Advances in Financial Machine Learning by Marcos López de Prado and came across different Bar types, and simulating Volume Bars from execution data myself. My understanding of ...
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Continuous futures data roll adjustment

When I construct continuous futures data (Wheat futures for example), I get different results than barchart or tradingview. Examples below. The 1st image is my adjusted continuous data and the 2nd ...
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