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

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1answer
798 views

Lagged dependent variable, yes or no?

I read conflicting opinions about the inclusion of lagged dependent variables in modeling, and I guess it is partly up to the researcher and depending on the scope and goal of the research. I'm ...
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1answer
136 views

How does one use the Johansen cointegration test in a linear time series model?

How does one use the Johansen cointegration test in a linear time series model? Should I only use normalized coeffients for interpretation? Or, once I know that the variables are cointegrated, do I ...
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0answers
33 views

How to choose a GARCH model which delivers iid standardized residuals?

For my thesis I first need to examine nine financial time series and fit a conditional volatility model such that the obtained standardized residuals ($z_t = \epsilon_t / \sigma_t$) are approximately ...
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0answers
41 views

serial correlation, Fama MacBeth (1973) procedure incorporating momentum

I have a question regarding the use of the Fama-MacBeth (1973) procedure on panel data. I am investigating the cross sectional determinants of expected REIT return following the procedure from: Chui, ...
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0answers
22 views

Marginal Distribution using GARCH model

I have n return series. I fitted AR(1)-GARCH(1,1) to each return series. Then used PIT(residuals) to transform the residuals to uniform. Then I fitted n dim copula to the data. I simulated 1000 points ...
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0answers
39 views

Distribution of AR and MA polynoms roots in ARMA/ARMA-GARCH models

I have another noob question. So, for example, I have ARMA(2,2) model: $$ x_{t} = \phi_{1}x_{t-1} + \phi_{2}x_{t-2} + e_{t} + \theta_{1} e_{t-1} + \theta_{2} e_{t-2}$$. So, I have 2 polynoms: $$1 - ...
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0answers
35 views

Problem with overlapping data when testing futures market efficiency

In my case non-overlapping data would represent the scenario where futures prices (3 months) do not correspond to the futures spot prices in terms of delivery date. For example, futures settlement ...
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0answers
33 views

Are there alternatives to the Box-Tiao decomposition in identifying mean reverting portfolios?

As documented in this paper, Box-Tiao decomposition (a way to decompose multiple time series into components with different speeds of mean reversion) can be used to identify mean reverting portfolios. ...
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0answers
52 views

Estimating Daily Dynamics using Hourly Data

This article gives a nice outline of how daily data can be used to estimate cointegration on a monthly horizon. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1404905 I'd like to use the same ...
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0answers
53 views

How to fit exogenous + GARCH Model In Python?

I am studying a textbook of statistics / econometrics, using Python for my computational needs. I have encountered GARCH models and my understanding is that this is a commonly used model. In an ...
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0answers
47 views

copulas and time series

Can anbody explain how Copulas are used to describe the dependency between, for example, the return on two different stocks? I understand how Copulas are the "glue" that binds the two marginals ...
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0answers
112 views

Application of time series analysis to Bitcoin prices

Various exchanges allow for the trading of Bitcoins. The price of Bitcoin was very volatile since the inception of the system, today it is 391.76 USD: I wonder whether time series analysis tools ...
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0answers
51 views

state space for affine yield curve

i would like to reproduce in R the working paper " Affine free arbitrage class of Nelson Siegel term structure". The authors considering the equation of nelson siegel plus an adjustment term(C(t,T)) ...
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0answers
51 views

Transforming Variables in time series regression

I have multiple quarterly time series data and trying to build a linear regression model using this dataset. Should the transformations on the LHS and RHS be the same i.e QoQ percent changes? Could ...
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0answers
49 views

labeling high frequency signal data

Was curious if anyone has methodologies they can recommend for systematically labeling (discrete) signals generated from intraday tick data for use in classification or detection models ?
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0answers
74 views

Cointegration and variance of time series

Given that $X_t , Y_t$ are two cointegrated random processes, what can we say about the relationship between variance of the two increments $var(X_{t+h}-X_t)$ , $var(Y_{t+h}-Y_t)$ for a given ...
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0answers
57 views

Modelling turnovers with a random walk. Is it right?

I need to analyse a bunch of weekly time series that reflect the turnovers of various companies. I already read that return rates or share prices show stochastic patterns that can be modelled by a ...
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0answers
109 views

modeling regime switching for Correlation matrix

I am trying to estimate covariance in multiple time series. However, I want to do this using a regime-switching framework. So, I start with fitting a GARCH(1,1) model and then de-volatalize the ...
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0answers
57 views

How to estimate constrained a constrained VAR(1) with MATLAB?

Suppose I want to estimate the following VAR(1) model: $$ Y_t = \mu + \Phi Y_{t-1} + \varepsilon_t $$ where $Y_t=(y_{1t}, y_{2t},…,y_{kt})'$, $\mu=(\mu_1,…,\mu_{k})’$ and $\Phi$ a matrix of ...
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0answers
269 views

What machine learning method is more suitable for prediction of financial time series? [closed]

I have some time series from a stock exchange market. For each of them, I want to answer the question that whether the price will grow at least p percent in the d coming days or NOT(and during these ...
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0answers
78 views

Rule of Thumb for minimum length of time series for AR(1) estimation

I have a data set of 350 points, I want to estimate the lag 1 auto correlation for different sub-sets of the data. More precisely I want to take non overlapping windows of length 1,2,3....n and ...
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1answer
310 views

Simulate non-stationary time series with cointegration

how can I simulate/generate two non-stationary time series (with unit root) so that they can be also cointegrated (using R or Matlab). Thanks in advance.
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0answers
79 views

Max Likelihood via Marquardt Optimisation

I asked a related question here: How to apply Levenberg Marquardt to Max Likelihood Estimation I tried the approach suggested it works for some of the parameters but not the variances. I spoke to ...
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1answer
230 views

how to compute daily skewness of S&P daily return timeseries under no other more high - frequency time series?

As we all know , return time series marked features: fat tail or negative skewness and peakedness. For a similar problem of variance computation, we can compute variance by garch model and other ...
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0answers
362 views

Time-varying correlation via state-space representation and Kalman filter

Let a linear time-varying mode like this one: $y_{t}=\alpha_{t}+\beta_{t}x_{t}+\epsilon_{t}$. You can also suppress the constant term to simplify this example: $y_{t}=\beta_{t}x_{t}+\epsilon_{t}$. ...
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0answers
292 views

Fluid dynamics for order book depth modelling

Would someone be able to give me an idea what type of fluid dynamics I could look at for modelling the order book? My background is more signals-related maths (correlation, covariance, fourier etc). ...
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0answers
474 views

Oscillatory time-series forecasting

I was wondering if this mean(160)-reverting/oscillatory time series "SUM" can be considered chaotic & forecastable to some extend short-term? ...
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1answer
123 views

Building predictive model for closing price using only previous days data

I am trying to determine which quantitative model to try and build a predictive model for the next day's closing price for all the S&P stocks based on their bar for that particular day. However, I ...
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5answers
4k views

Which library shall I use for time series analysis in Java?

I'm looking for a library to do some time series analysis in Java but I can't find anything suitable. I've found plenty of libraries such as Math3 of JSAT but there's much I can you for my problem. ...
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4answers
327 views

Intermarket analysis - related time series?

I'm about to embark on training a neural network on daily forex data, with a view to obtaining a predictive network. I'm also interested in using data other than the forex currency pair data itself, ...
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3answers
160 views
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1answer
211 views

Book recommendation for time series analysis

I have been trying to wrap my head around Engel-Granger test and jcitest etc. I have failed thus far. If possible can someone guide me about which books to start with and possibly reach to ...
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1answer
184 views

How to forecast bond price with time series

I have the goal of being able to develop a model that can forecast the future prices of european government bond (or other private bonds), particularly from the historical prices and returns of the ...
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3answers
328 views

Modeling Financial Time Series

Price time series are not stationary. So we difference them and get the return time series, which are stationary. Does this mean, it is always a good idea to model only the return series of financial ...
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1answer
633 views

Selecting timeframe for time series analysis

In technical analysis, we may use confluence of direction for 3 timeframes to roughly gauge bias of market now. Similarly, if we use time series forecasting methods to predict(say daily data-whether ...
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1answer
43 views

How to create time series with lagged in R [closed]

Would anyone else advise me, how to create time series with lagged in R. I would the result is the difference with lagged, there is a function Delt() but the result is the percentage change. Please ...
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1answer
80 views

Aggregating Tick Data

I have Level 1 data that has already been aggregated into 0.5s buckets by the exchange. I'd like to further aggregate the data into hourly and daily buckets. I plan to do this by simply taking a ...
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1answer
161 views

Transforming daily simple returns into weekly

I am trying to transform daily simple returns into weekly returns. I am using the following R code: ...
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1answer
156 views

Can I do a GARCH model to forecast a time series?

I read this paper https://research.aston.ac.uk/portal/files/240393/AURA_2_unmarked_Energy_demand_and_price_forecasting_using_wavelet_transform_and_adaptive_forecasting_models.pdf the two authors ...
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0answers
40 views

LSTM w/dropout Peer-reviewed or other authoritative lit for time-series/financial econometrics/Teh stock price/volatility/etc

So, I've been looking on Google Scholar for stuff using Long Short-Term Memory neural nets for time series. I was inspired by the interview with this 2nd place finisher in a recent Kaggle major: ...
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0answers
50 views

VECM model with GARCH (1,1) error in R

I should create a VECM model with 8 lags and with Garch (1,1) error in R but i don't know how to do it and which package to use. The VECM should also have covariates in it. Then I should perform a ...
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0answers
22 views

Guidance on machine learning approach to improve interpolation [duplicate]

I am thinking about doing a project on improving the accuracy of some stock signals. The signals are fundamentally derived scores on a per stock basis. They are updated on a weekly or monthly ...
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0answers
46 views

VAR(1) - GARCH(1,1) model estimation in R

Can someone please help in explaining the steps involved to estimate the parameters of VAR(1)-GARCH(1,1) model of Mcaleer 2003 in r. It is a multivariate GARCH model where the mean equation is ...
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0answers
31 views

White's reality check p-value

I am running a hypothesis test based on White's reality check p-value. I am getting a weird result for my univariate time series of returns. In essence, I am following a code on MATlab to run the test ...
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0answers
26 views

Eurostoxx50 data in USD

does anyone know how I can import from yahoo the Eurostoxx50 data denominated in USD (not Euros as listed on yahoo?)
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1answer
162 views

Augmented Dickey-Fuller Questions

I've been searching in bibliography about this test applied to an AR(p) model. $$Q(L)(Y_{t})=c+\epsilon_{t}$$ Where L represent the Lag Operator and $Q=1-\phi_{1}x-.....-\phi_{p}x^{p}$ is the ...
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1answer
50 views

adding dummy variable to ts object in r for particular quarter

I've looked all over and can't seem to get a clear idea of how to do this; I have ts data with quarterly frequencies. I simply want to add a dummy variable only for the data corresponding to Q4 but I ...
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0answers
31 views

In what situations would cross validations scores be inaccurate?

I'm trying to fit a SVM model on times series stock return data, predicting a buy, hold, or sell signal of the stock. I'm using 10-fold cross validation (using the R package ...
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0answers
22 views

Including intercept and trend in ADF of differenced series

When specifying that the trend and/or intercept be included in the ADF output, does the trend/intercept election follow through to the ADF tests of differenced data as well? To clarify further, I ...
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0answers
22 views

Download DGS3MO from FRED with getSymbols - error

I follow the course "Mathematical topics in finance" from MIT courseware. I opened R and rendered Dr. Kempthorne's Case Study 3: Time Series from September 30, 2013 I am able to render the code and ...