Questions tagged [time-series]

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

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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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37 views

Autocorrelation at lag 4. Is it AR(4)?

I have attempted this question can't solve it. What does it mean by displacement 4? Is it as AR(4) model? Question : For a first order autoregressive (AR) process $X_t = \phi X_{t-1} + Z_t$ the ...
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56 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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17 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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42 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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60 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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42 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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187 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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28 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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82 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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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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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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91 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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65 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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25 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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86 views

SARIMA+GARCH model

The model ARIMA+GARCH writing as this form with the rugarch package in R: ...
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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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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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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
183 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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51 views

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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58 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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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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86 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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102 views

How to handle Holidays in Time-Series Datasets?

Im currently analyzing a Dataset of the German Stock market. While Holidays like Christmas or New Year aren't a problem for Return Calculation or Portfolio Performance, im testing some regressions and ...
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What does A(B) mean in time series

So I have been reading some papers regarding time series, mainly from Granger and Engle. I am a bachelor econometrics student, but I have never seen such notation before. For example, A(B)(1-B)x(t) = -...
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119 views

Fama French Three Factor Model: How do I get the risk premia?

I try to calculate the cost of equity with the FF3 model and already estimated the beta factors for the market, size and value risk premia by using regressions and the data provided on the Kenneth ...
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1answer
73 views

generalisation of cointegrated stock pair strategies to multiple cointegration

Question: as it is well known, there are strategies to trade pairs of stocks which are known to be co-integrated. See for instance here: https://medium.com/auquan/pairs-trading-data-science-...
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54 views

Cross Effect in OLS

I am using cross effect in OLS regression for a time series problem for a multivariate regression. I want to quote reference for use of cross effect. Secondly, I want to explain why better to use ...
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1answer
115 views

How can stationary time series data be used as input in an ML model?

I am halfway through "Advances in Financial Machine Learning" by Marcos Lopez de Prado. I understand that a time series like stock prices can be transformed to make it sufficiently stationary. ...
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85 views

Exponential Smoothing - Alpha greater than 1

Simple stats question. I'm having trouble finding anything in the literature as to why the smoothing coefficient can never be greater than 1. This question was started by me doing time series ARIMA ...
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linear model of price changes

I came across the below equation for linear model of price changes in E.Chan book Algorithmic Trading which is the base for a strategy. ...
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Brownian motion from price-series, what is the time step?

If I assume a given empirical price-series is a brownian motion, I can estimate the drift and standard deviation as long as I know what the time step was when the process was 'generated'. But since ...
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68 views

Forecasting a seasonal series with R

I am working with the program "R". I used the command "seas (X-13)" to deseasonalize my quarterly series, then I did the forecast with it. Therefore my forecast is in deseasonalized terms. Now, I was ...
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Pricing a transfer option for oil

Need some input in how to attack this problem. Given are 8 timeseries: UK Oil price, Delivery Quarter 1 2020 UK Oil price, Delivery Quarter 2 2020 UK Oil price, Delivery Quarter 3 2020 UK Oil price, ...
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51 views

Log transformation of TS-stationary time series

I usually see the $log$ transformation of prices: $$p_{new}\left(t\right) = ln\left(\frac{p_t}{p_{t-1}}\right), t \in [2...N]$$. Let's our series be a trend stationary time series like: $$p\left(t\...
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Is this a good (partial) autocorrelation or bad?

I was playing with some data on deviation of close prices from its smoothed estimated and got these ACF and partial ACFs: I still struggle to get proper intuition to the ACF plots. What do the plots ...
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66 views

Misunderstanding of time series autocovariance

I'm reading the "Time Series: Theory and Methods (2nd ed.)" by P.J.Brockwell and R.A.Davis. I've stopped at the one moment at pp.218-219 (Chapter 7 "Estimation of the mean and the Autocovariance ...
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Fama-French 3, Carhart 4, Fama-French 5 Factor models return borderline 0% R2 (max. 6.6%). Time series regression

I am currently working on an industry specific time series analysis of European Equities between 201001 and 201812. I use the European Fama French factor returns (plus the momentum factor return) that ...
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1answer
97 views

when a co-integrated times series pair has broken the leash

I have two times series, say $T_i$ and $S_i$ over a reasonably large time window, and I have calculated their cointegration (using python's OLS and Adfuller) . Say that the test has passed with high ...
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Problem with Hurst exponent estimation for ARFIMA models

guys. I try to realize my ARFIMA model identification script in R. I try to find the best method for unbiased Hurst exponent estimation (fractional difference parameter could be found as Hurst - 0.5) ...
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Tools related to Granger Causality

I would like to know if there are some tools that can measure that one time series is "faster" than the second one. I talk about really similar time series related to high frequency trading (hundreds ...
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46 views

serial correlation and CUSUM results

I have the following CUSUM test resulted from autoregressive distributed lag models (ARDL). Does the CUSUM results show that the model is stable? I am a bit confused because the red line in CUSUM ...
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120 views

Calculating Ex-ante Sharpe Ratio in multi-period setting

I have built a return process $\{x_t, t = 1,\dots,T\}$ for an asset. Suppose I have generated $K$ sample paths $\{x_t^j, t=1,\dots,T\}, j=1,\dots,K$. I think of two ways to compute the Sharpe ratio. ...
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257 views

R Equilibrium FX using VEC or Behavioural Equilibrium Exchange Rate (BEER)

I dont have much experience with R. I would like to do create model for FX Equlibrium using VEC or BEER. I already know what variables I want to use in model: trade differential between UK and the ...
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108 views

Some basic examples for Granger causality

I have two time series, X and Y. The number of observations in each time series is the same and the variables would be price(logged). The goal of my research is to analyze if one variable X follows ...
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Is there such a thing as resonance in economic underliers?

In physics the occurence of resonance is explained and widely understood in its linear form and subject to research in nonlinear resonance. Example for instance are resonant frequencies of objects. ...
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Autoregressive Distributed Lag Models (ARDL) results analysis

When using autoregressive distributed lag models (ARDL), I usually get a counter-intuitive result for the selected lag. For example, when examining the relationship between GDP and Foreign Direct ...