# Questions tagged [time-series]

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

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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 ...
47 views

### Difference between Predicting stock returns and Forecasting stock Returns?

The data that is used are either Technical Indicators, Fundamentals Indicators or Macro Indicators which is time series in nature. Given, if we are estimating one-period ahead returns(t+1), is there a ...
76 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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### 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?
2k views

### Estimating correlation using EWMA

I am using an EWMA model to evaluate the correlation between yearly time series. I know Riskmetrics uses $\lambda=0.94$ for daily data and $\lambda=0.97$ for monthly data. Is there a value ...
387 views

### Block bootstrap to synthesize asset prices

I have a few basic questions on block bootstrapping on a financial time series ('TS'). Assuming my trade universe consists of 10 stocks, I would like to create a set of synthetic prices for all 10 ...
400 views

### How to synchronize put and call option-data?

I recently retrieved a large amount of European option data, for call and put prices, from OptionMetrics. Doing so for the same time period I get a file consisting of 62558 rows of call prices & ...
157 views

### Multivariate Markov Regime switching GARCH

I have a regression with 4 independent variables and a dependent variable. I want to implement a Regime switching GARCH model but have been unable to find a package in R,Python or Matlab. MSGARCH ...
123 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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### Bloomberg tick data timezone offset because mismatch in bloomberg api and excel bloomberg

i am trying to fetch intraday tick data for security->C Z9 COMB Comdty,startdatetime:2019-08-05 15:30:00 Enddatetime:2019-08-05 15:35:00 from excel and bloomberg Api but response is mismatching can ...
252 views

### Generating surface of Kernel Density Estimates over time

I have a 1-minutely OHLC dataset indexed by time as follows: ...
43 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 ...
147 views

### Can you use GARCH-MIDAS for intraday data?

I'm working on a project to forecast volatility and I'm using intraday data (1 min). I want to include exogenous variables to the model that have daily frequency. I was wondering if GARCH-MIDAS can be ...
54 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 ...
101 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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### 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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### 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) = -...
1k views

### Why quants think that the risk-neutral measure should not be used for financial forecasting?

In posts regarding the $\mathbb{P}$ vs $\mathbb{Q}$ debate (see 1, 2, 3 or 4), most answers conclude that historical-based methods are better suited than risk-neutral models for financial predictions. ...
2k views

### How to forecast high-frequency data?

Introduction: I have seen a plenty of articles/books regarding volatility forecasting applied to high frequency data, but none of them were dedicated to forecasting the actual prices (for example bid/...
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### 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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### 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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### 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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### 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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### 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 ...
170 views

### Filling a few missing data in time series?

I'm writing a paper about Uncertainty indices like VIX, etc. I already collected all data but it seems that some of the variables got a few or a little more missing data. I have daily and monthly data ...
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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 ...
64 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 ...
587 views

### Up and Down days in GBPUSD and a Filter

I want to study if the odds of an up or down day in a forex pairs is 50-50. I just count the total number of up and down days in X years and compare it with the total days. The results are very ...
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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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### Reverse chronological time-series / inverse time-series

If a timeseries follows a BM, is it true that the inverse ts and reverse chronological ts is also a BM? What if the ts exhibits mean reversion tendencies? Would these tendencies become a momentum ...
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### 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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### Auto-covariance function of station time series

How to show that for any stationary time series its auto-covariance function is symmetric about the origin, that is $\gamma_{k}=\gamma_{-k}$ where, $\gamma_k=cov(z_t,z_{t-k})$
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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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### 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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### Significance Of Missing Data for RMSE Estimation

I have a time series covering ten years of daily close prices, which I compare to a theoretical time series generated by a model. The original series has a handful of missing data points (~2%), some ...
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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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### 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) ...
175 views

### Volume or Dollar bars vs. volatility normalized and demeaned financial time series

In his book - Advances in Financial Machine Learning, Marcos Lopez de Prado familiarises the reader with a number of ways of normalizing our financial time series data. Below I provide a couple of ...
908 views

### Fitting Copula and Simulation

I would greatly appreciate any insights into the problem described below, regarding using the data obtained from applying the functions of the rugarch package ...
27 views

### 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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### 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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### 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 ...
66 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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### what are the criteria to select pairs?

I'm new to this forum, this is the first question I posted. I have many candidate pairs and I've used ADF test to make a first selection. There are more than 800 selected. The pairs are absolutely too ...
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### 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 ...