Questions tagged [time-series]

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

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20 views

Decay factor and volatility (2 assets): do you keep simple correlation to calculate vol? or exponentially weighted correlation?

I have calculated exponentially weighted variances (and volatilities) for a future and the underlying index. This has been done by: Calculating daily returns for 1 year (262 days to follow ...
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1answer
29 views

Can ARMA and GARCH models be estimated separately in ARMA/GARCH?

Can I use the residuals of the ARMA model to build a GARCH model(with Zero mean)? If so, does this mean that this GARCH model(with Zero mean) has no effect on ARMA's estimates. For example, if I want ...
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1answer
36 views

How to apply decay factor in the volatility calculation for 1 asset?

I read somewhere that the decay factor is (1-lamba)*lamba^t where t is first return, second return, third return, ... I also found this formula which I have difficulty to understand: How do I ...
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1answer
44 views

Use futures contracts of different lengths to predict spot prices

So I am trying to see how future contracts prices with different time to maturity are able to predict the actual spot price of crude oil at the time of maturity for the contracts. I have the simple ...
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How to use multi-periods and mult-factors to predict stock price by linear regression?

Give data in $t_n$ denoted by $[x_1^n, x_2^n, ... x_d^n]$ and label $y_n$ to be predicted. We can just train a $d$-dimensional linear regression $y_n=\sum b_ix_i^n$ to make a prediction. However, I ...
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1answer
50 views

Predicting time series based on another

This is more of a generic question, but I'm sure it has a best answer/methodology which is what I'm trying to reach. I'm trying to figure out a solid line of thought when looking at a time series X ...
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1answer
76 views

R: Finding peaks on a stock price chart

I would like to do is what I thought to be a simple task: find the locations of peaks for a certain stock, and mark those peaks on a chart. I was surprised by a lack of appropriate examples on the ...
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37 views

GARCH(1,1)-M MLE optimization with fmincon in R

I've searched thru dozens of papers and did not find in any of them satisfying and enough theoretical answers to my concerns. So I've combined everything what I found below. Please indicate if my ...
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27 views

R-Help..Question regarding working day Frequency in Time series

I have a data where there are observations based on working days in a year. The working days are not same in each year. These are 248 (say in 2018) observations in first year and then may be 246 ...
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1answer
31 views

Relationship between Data Size and Arima Prediction Interval Width?

When we use Arima model to acquire Interval Predictions, will the width of prediction intervals decrease if we use more data (longer history) to fit the model?
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Updated Time Series Prediction Model When acquiring new data Points - Basic Question

Suppose I have a Time Series Model (assume ARIMA) and use it to make one-step ahead prediction. If I acquire a new data point, (for example I was originally using the first 100 days to fit an Arima ...
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117 views

Process Transforms (Fractional Difference)

Let's say I have a process $X_t$ with unknown variance process $V_t$. Then, I write $\mathrm{EMA}[X_t]$ to be the 5 sec exponential moving average of $X_t$. Consider the transformation $$\sum (X_t-\...
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37 views

How to compute prediction interval if using simple moving average t o predict?

If I want to use simple moving average to make a prediction. For example given h=1 and m=13. $\hat{x}_{t+1}=\frac{\sum_{j=1}^{13}x_{t-j+1}}{13}$. What is the prediction interval going to be? How to ...
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Log Transforming My TS Data for a First Difference Regression

I'm currently working with a ts of monthly yields where $Yield = \frac{Expense}{Blance}$. I am trying to understand the change in yield given a change in the market rate. My regression is $Y = \...
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Calculating the total return on an Interest Rate Swap (with 1 year of duration)

Say I am the fixed rate payer on an interest rate swap and have 1 year of duration of exposure. When I entered into the IRS (say yesterday), the quoted rate on Bloomberg was 15%. Say tomorrow the ...
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1answer
38 views

Subscription Based Revenue Prediction

My dataset is on revenues from subscription-based (no commitment, can cancel any time). We have people signing up every year, continue paying for a few years and then gradually cancel the subscription....
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Can this be taken as a panel data?

I have a data set of different time periods but same length. For example, I have a data set of GDP and energy consumption for five countries. For country A, I have the data from 1995 to 2000. But for ...
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36 views

Why ARIMA is better for shorter term forecasting compared to ECM?

I'm reading up about the Error Correction model and was confused by the statements below, from here: In order to still use the Box–Jenkins approach, one could difference the series and then ...
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42 views

Expected Shortfall for ARMA-GARCH Model

I need to find an analytical solution for the 99% confidence expected shortfall (CVaR) for a long position of 100 dollars at time $t$ for an asset with returns modeled by an ARMA(1,1)-GARCH(1,1) model ...
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1answer
87 views

Random Forest on financial time-serie?

Is it okay to apply Random Forest to a non-stationary financial serie? Or would it be correct to first difference the serie and then apply Random Forest to the new serie?
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26 views

How to approximate expectation and variance of an integral from a discrete Time series financial dataset?

I have discrete time series financial data, with time($u$), price($S$) and someVariable($q$) which looks something like this. ...
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1answer
66 views

Two commodities which are normal distributed and perfectly correlated

The daily price change in commodity 1 is distributed $N(0,0.15^2)$ and the daily price change in commodity 2 is distributed $N(0,0.3^2)$. The two commodities are 100% correlated. 1) Does the relative ...
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87 views

Is Ornstein–Uhlenbeck process the continuous-time correspondence of AR(1) process?

I see the AR(1) process (with $|\alpha| < 1$) can be written in the following way: $$x_{t+1} = \alpha x_t + \epsilon_t$$ $$\Delta x_t = - (1 - \alpha) x_t + \epsilon_t$$ which looks quite like the ...
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193 views

Differencing vs Detrending financial time series

I'm quite newbie to time series analysis and I have to understand what's the difference between differencing time series (i.e considering $Y_t= X_t-X_{t-1}$) and detrending (using linear regression ...
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35 views

Normalization of Time Series

I want to start quantitative research on the SPY, I got the data and want to start time serie analysis. The thing is that I don't know how to start. I know that a have to normalized the data in order ...
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27 views

Pricing Data/Regressions in R

I'm working on a project for my econometrics class and trying to replicate a few papers relating to Fama-French factor models. I got data from CRSP and Compustat, but I'm a bit unsure how to ...
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62 views

Log returns vs normal returns with weekly prices

I am constructing equity factors and I am given weekly prices for several thousand stocks. Every year the portfolio should be rebalanced, so I am always calculating the returns for a single year. Now ...
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19 views

ARMA being used instead of ARIMA despite not rejecting KPSS

I was just reading this paper and on page 4 it says "The results of the above Phillips-Perron, KPSS and Leybourne-McCabe tests show that the price indices of Dow Transportation, S&P 500 and VIX ...
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1answer
43 views

Calculating and visualising the future value of 100USD invested in fixed income securities and bonds in R [closed]

I have uploaded TB3MS to R and would like to visualise the future value if i invest 100USD in it. The interval is from 2014 to 2019, monthly frequency. I would like it to be comparable to a plot i ...
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66 views

Annualizing Sharpe Ratio using small time frames

I have coded a strategy that works 5m time frame. I know you multiply it by 252 but i am using 5m or sometimes 1h time frame. Which number do i have to chose to multiply? There are 72576 five minutes ...
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23 views

Coming up with a statistic that is responsive to changes in a time series, yet not too volatile

Let's say I have a fairly volatile time series $X_t$ - it doesn't have any reason to show an upward / downward trend, but it does show drops and spikes from time to time. It can also change level (e.g....
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1answer
61 views

How to get formulas for EWMA model with M-day records

Given following formula in exponential weighted moving average (EWMA) model i: stock i t: time t rit: actual return for stock i at time t If we only know latest M-day situation, how can we derive ...
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199 views

Determining if a time series is random

I originally posted this in the Data Science Stack Exchange. Another poster suggested I post it here. The idea would be to identify "orderly" segments within a market time series and use them to ...
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32 views

Clusters evolution over time

I have a dataset of stock prices and I want to group stocks that share similar characteristics together using cluster analysis. I'm interested in following the evolution of each cluster over time, but ...
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1answer
94 views

Error message when backtesting GARCH in R

I am trying to backtest my ARCH model using ugarchroll from rugarch package in R, but I am getting this warning message ...
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114 views

Why OLS in Fama French time series regression?

I read many papers on asset pricing and have some basic doubts regarding Fama French Time series regression: We have time series data, but still it is a simple OLS we run in FF model. Then why it is ...
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41 views

How can I estimate a dynamic GARCH model using a Kalman filter methodology in R or MATLAB?

Does anyone know of any R or MATLAB packages for estimating GARCH models using Kalman filtering or any other state-space methodology? I would like to estimate a GARCH so that not only the variance, ...
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1answer
104 views

time series data modeling for deep learning

what is the best format to feed the input data, which are time series with varying density over time, to a deep learning network, while at any iteration we want to feed a batch of data including a ...
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115 views

Combining SARIMA and GARCH model for prediction in python

I need to understand the concept of combining (S)ARIMA and (G)ARCH model for the predicting time-series data. I understand that after fitting the arima model ...
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0answers
45 views

Hurst exponent of stock using R/S analysis

I am attempting to use R/S analysis to estimate the Hurst Exponent on a single stock. At first I directly use the stock price ( instead of stock return) and the Hurst component calculated is > 0.9 ( ...
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1answer
133 views

SARIMA+GARCH model

The model ARIMA+GARCH writing as this form with the rugarch package in R: ...
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47 views

tick/book data vs bar data, worth the infrastructure investment?

For reference, I am talking on behalf of a small group of math/stats graduate students as well as software engineers (we are 6 total), we know each other for years and decided to make a small (private)...
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41 views

how to model NGARCH using 5min frequency data?

NGARCH model using 5-min High-frequency data in R I wanted to analyze some 5 minute frequency data of stock market. My teacher asked me to use NGARCH to model, but I didn't know how to program.Here ...
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34 views

Serial Correlation in Rolling Change Linear Regression Models

1.) Lets say I have two time series GDP, BUSINV from (1948, 2019); Frequency of Data is Quarterly. 2.) Say I want to predict GDP i.e. GDP ~ BUSINV 3.) Since GDP is not stationary (i.e. level) and ...
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How to implement Time varying EWMA cross correlation in STATA?

I have read this question, I know about lambda, demeaned subindexes. But not able to implement in STATA?
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2answers
349 views

Absorption Ratio

I'm actually trying to implement Mark Kritzman's absorption ratio (Principal Components as a Measure of Systemic Risk by Kritzmam, Li, Page and Rigobon, 2010, SSRN 1633027) using Python, but I'm not ...
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modelling known regime shifts

I wish to model a price time series with a known regime shift: electricity price before during and after the introduction of a carbon price. The time series looks like this: you can see the jump in ...
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1answer
81 views

Can MACD be calculated for values other than 12 and 26?

I am working on time-series classification problem using Convolutional Neural Networks in Python. The data-set used is financial stock market data (like yahoo finance). I am using some technical ...
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2answers
255 views

Why do we need event-driven backtesters?

I am reading this article at quantstart regarding event-driven backtesters. It seems to me that the main advantage of using an event-driven backtesters is that it avoids look-ahead bias. Usually I ...
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1answer
92 views

Trading 3 stocks X Y Z where X cointegrated to Y, Y to Z, but no other cointegration is available

Suppose you have 3 stocks, say X Y Z. You also know that X is cointegrated to Y using some test (say ADF) and Y is cointegrated to Z. However, no transitivity, and no threesome cointegration ...

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