Questions tagged [time-series]

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

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71 views

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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20 views

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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51 views

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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81 views

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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1answer
178 views

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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1answer
137 views

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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1answer
112 views

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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1answer
143 views

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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57 views

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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36 views

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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112 views

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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17 views

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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45 views

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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31 views

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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88 views

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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2answers
188 views

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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33 views

Missing values in a multivariate futures model

I have OTC Naphtha dataset consisting of broker quotes received in the year 2021 for around 15 futures contracts expiring monthly. My dataset looks like this where each row represents average quote ...
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33 views

Multivariate ARIMA model with irregular time-series

I have a financial time-series dataset consisting of prices of 12 different products (financial futures contracts) that expire x months away from now. So if I plot these 12 contracts with end-of-day ...
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1answer
71 views

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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38 views

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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64 views

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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65 views

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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118 views

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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70 views

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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3answers
83 views

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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19 views

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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27 views

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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16 views

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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1answer
93 views

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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1answer
74 views

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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1answer
47 views

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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35 views

[PYTHON - Create a For-loop for multiple regressions within the same/or different dataframe/s (Funds returns with fama french)

hopefully somebody can help me out, this is my first question on here. I have a dataframe with dates (Index) as the Y axis and the X axis (columns) hold all the dependent variables (target variables) ...
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Fitting ARIMA + GARCH in R

I'm forecasting Electricity consumption Data. I have data for one year , so for every 15 minutes there is an observation. My data contains seasonality and I don't know how to fit SARIMA + GARCH into R,...
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2answers
300 views

How can momentum trading strategies work if returns are not serially correlated?

Returns are demonstrably not serially correlated in most financial time series (Day 1 returns are uncorrelated to Day 2 returns etc.) . Since this is the case, how can momentum trading strategies work?...
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28 views

Charting Annual Volatility From Start Date In a Line Plot

I'm pretty new to python/data viz and this is my first time asking a question on here but I have a df with monthly price data back to 2016 for 6 different instruments. I just want to be able to ...
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120 views

I am getting an $\alpha=0$ in the GARCH(1,1) model. Is this normal and how must I interpret it?

I am running a GARCH(1,1) on return data. For some data sets, I am getting an $\alpha=0$ and a $\beta$ of 0.999. Is this normal? If so how should I interpret it? Here is my code, here j are daily ...
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1answer
187 views

Understanding out-of-sample performance metrics for Realized Volatility

I fitted several models on a realized volatility process and then proceeded to obtain out-of-sample results. I'm struggling to interpret these results apart from to tell model A seems better than ...
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48 views

Bitcoin data (minutes time frame)?

Where can I find a correct data of BTC/USD with a minute time frame? I've downloaded a minutes data from this site I've compared (with the original one from the exchange Binance) the last day (from ...
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1answer
148 views

Why is $Z_t$ uncorrelated with $X_{t-1}$ in $X_t=\theta X_{t-1}+Z_t$?

In a solution to the problem below, the teaching assistant solves it by calculating $\mathbb{E}[X_t^2]$ and ends up with also having to calculate $\mathbb{E}[X_{t-1}Z_t]$ after expanding the square. ...
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58 views

How to annualize kurtosis of returns (in simple terms)?

I'm confused by this post on how to annualize kurtosis. I don't understand how to apply it to annualize the kurtosis for my data. In other words, if I evaluated the kurtosis of, say, monthly returns (...
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70 views

Which Times Series Database framework for Python is best for portfolio optimization project?

I am starting to build a portfolio optimization algorithm in Python and want to structure a database to manipulate financial data. Although I have Python experience, I have never used SQL or such ...
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1answer
94 views

What is a cumulative return series?

I guess this is pretty easy but I cannot find a definition anywhere. I am trying to reproduce a paper and they say they use a cumulative return series at some point. Does anyone know exactly what this ...
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65 views

What do I need the Error correction model for in the two step Engle Granger approach (bivariate Cointegration)

could someone kindly explain what I need the ECM for in a bivariate Cointegration test? I am currently trying to reproduce the results of Rad et al. (2015): "The profitability of pairs trading ...
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39 views

How to calculate price and volume samples of a multi-product series?

I am reading Marcos de Prado's Advances in Financial Machine Learning. In a section titled "the ETF Trick", he explains how to calculate periodic price and volume samples for a basket of ...
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1answer
42 views

Converting timeframe of a time series

So I've encountered a problem - I have a lot of 1 min data, but my strategy works better on longer timeframes and backtrader has some problems with backtesting on 1 mln rows. I want to convert it to ...
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1answer
226 views

Trading a Bouncy Stock

I came across the following question and am trying to understand it better. I was hoping you could share your intuitions. For a given stock, you are certain that for the next 100 days, it will move ...
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1answer
42 views

in time series analysis or finance people use log return for inference but returns can take negative value [closed]

in time series analysis or finance people use log return for inference but returns can take negative value. but log cant take negative values. so why we use it when log is not defined on most of ...
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2answers
675 views

Proof of the fact that roots lie outside the unit circle guarantee stationarity of the time series

For an AR(p) process $$\begin{align} y_t &= \mu + \phi_1 y_{t-1} + \phi_2 y_{t-2} + \cdots + \phi_p y_{t-p} + \epsilon_t \\[4ex] &y_t (1 - \phi_1 L - \phi_2 L^2 - \cdots - \phi_p L^p) =\mu + \...
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1answer
88 views

Prediciting outperformance - choice of statistical design?

I want to predict relative outperformance between a stock and an associated benchmark index using statistical time-series models (e.g. ARIMA) and some exogenous variables (day of the week, corporate ...
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2answers
169 views

GARCH(1,1) parameter estimation optimization method

In estimating a GARCH(1,1) model, $$\sigma_{t+1}^2 = \omega+\alpha \epsilon_t^2+\beta\sigma_t^2$$ Usually the parameter tuple $(\omega,\alpha,\beta)$ is estimated by the quasi-maximal likelihood. ...

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