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Questions tagged [time-series]

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

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0answers
23 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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6answers
50k views

How to fit ARMA+GARCH Model In R?

I am currently working on ARMA+GARCH model using R. I am looking out for example which explain step by step explanation for fitting this model in R. I have time series which is stationary and I am ...
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1answer
613 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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2answers
919 views

Online algorithm for calculating EWMA at irregular intervals?

What is a fast online algorithm for calculating the EWMA (exponentially weighted moving average) of an input variable observed at irregular intervals? I know the formula for when sampling at regular ...
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1answer
63 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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3answers
315 views

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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1answer
78 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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1answer
113 views

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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2answers
160 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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3answers
2k views

Analyze raw tick data

I'd like to work with raw tick data and naturally this data is unevenly spaced (for example, a couple of quotes are at the same second etc.) For example ...
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0answers
456 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 ...
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1answer
288 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 ...
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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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1answer
282 views
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25 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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0answers
60 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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0answers
18 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
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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0answers
64 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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0answers
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....
6
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1answer
89 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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1answer
47 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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0answers
38 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
193 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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5answers
24k views

Why are GARCH models used to forecast volatility if residuals are often correlated?

The answers to this question on forecast assessment suggest that if the sequence of residuals from the forecast are not properly independent, then the model is missing something and further changes ...
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0answers
30 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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0answers
101 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 ...
29
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4answers
8k views

What is a stationary process?

How do you explain what a stationary process is? In the first place, what is meant by process, and then what does the process have to be like so it can be called stationary?
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2answers
149 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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2answers
214 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 ...
2
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1answer
98 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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1answer
130 views

Standard GARCH(1,1) model with external regressors

I have a queastion how does a standard GARCH(1,1) model with external regressors in mean and variance euqations look like ? I know that standard GARCH(1,1) model without external regressors has the ...
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0answers
79 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 ...
66
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8answers
26k views

Is R being replaced by Python at quant desks?

I know the title sounds a little extreme but I wonder whether R is phased out by a lot of quant desks at sell side banks as well as hedge funds in favor of Python. I get the impression that with ...
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0answers
35 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
113 views

SARIMA+GARCH model

The model ARIMA+GARCH writing as this form with the rugarch package in R: ...
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0answers
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)...
2
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0answers
38 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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0answers
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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0answers
18 views

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?
3
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1answer
3k 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 ...
2
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3answers
415 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 & ...
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2answers
239 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 ...
2
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0answers
54 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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1answer
61 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
170 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
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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2answers
103 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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1answer
76 views

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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5answers
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. ...