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Questions tagged [time-series]

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

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2answers
717 views

Imposing Restrictions on Cointegrating Vectors, R example

The code given below estimates a VEC model with 4 cointegrating vectors. It is a reproducible code, so just copy and paste into your R console (or script editor). ...
10
votes
2answers
6k views

What time series database can be used with Python and Pandas?

I'm looking for a time series database that can be easily used with Python and Pandas objects such as DataFrame, Panel... But these objects will always contains time series. Ideally I'm looking for ...
10
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1answer
13k views

How to calculate the conditional variance of a time series?

I am reading a paper where the term conditional variance is mentioned, but I am not really sure what is meant by this and how this can be calculated: Fig. 2 shows the conditional variances of the ...
10
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2answers
259 views

Reference request: Quantitative approaches to market abuse detection

have been asked to look at some financial timeseries for potential suspicious activity. These are stocks (my background fixed income hybrids trading and not forensic analyst...) and most of the ...
10
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1answer
2k views

Time series price prediction and linear regression: using high/low rather than last quotes price

Discrete time series regression models, like ARIMA, are usually built around the assumption that we only have 1 available price for each period t, which I will call the Close. In reality asset time ...
10
votes
1answer
2k views

ARMA+GARCH prediction with package rugarch (R)

I am analyzing FTSE 100 series, from 2007-01-01 to 2010-12-31 (university exam homework). I have to use the data 'til 2010-11-30 as sample, and the remaining (23) observations as in-sample forecast (...
10
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0answers
6k views

How to use statsmodels' Granger causality test to measure the lag between two time series?

I am using the Granger causality test to measure the lag between pairs of time series where it is already apparent that one is following the other. So I am not expecting this test to tell me whether ...
10
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0answers
801 views

Markov-Switching Multifractal and FX Rates

Is there a better model than Markov-Switching Multifractal (MSM) for detecting regime shifts in FX rates across multiple time horizons? I am especially interested in the different aspects of the ...
10
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0answers
211 views

2-state HMM / ARMA process?

I have issues with this problem: Let $\{X_t, t\in \Bbb N\}$ be a 2-state stationary Markov chain, with transition $M$ (and $M(1,2)\neq 0 \neq M(2,1)$), let $\{W_t, t\in \Bbb N\}$ be a strong Gaussian ...
9
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2answers
7k views

Using variance ratios to test for mean reversion

Can you use the variance ratio test to determine whether or not a time series is mean reverting? I'm using the Lo.Mac function in the ...
9
votes
3answers
696 views

How to test for and how to simulate price rise/fall asymmetry in the stock market

One of the stylized facts of financial time series seems to be a fundamental asymmetry between smooth upward movements over longer periods of time followed by abrupt declines over relatively shorter ...
9
votes
3answers
882 views

Does Kalman filter always improve over linear regression?

If I have a simple linear regression that has statistical signification but I would like to improve the overall prediction results. Will a Kalman filter be always an improvement or as least achieve ...
9
votes
2answers
834 views

How do I incorporate time-variability in a pair trading framework?

Recently I have been looking at pair trading strategies from a cointegration perspective, as described in chapter 5 of Carol Alexander's Market Risk Analysis volume 2. As most quantitative finance ...
9
votes
1answer
342 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 ...
9
votes
1answer
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/...
9
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0answers
757 views

Alternative to Block Bootstrap for Multivariate Time Series

I currently use the following process for bootstrapping a multivariate time series in R: Determine block sizes - run the function b.star in the np package which produces a block size for each series ...
8
votes
2answers
3k views

What are common methods for modeling intraday trading volume?

What are the most common ways to model intraday trading volume, particularly for futures contracts? There are obviously a number of seasonal-type factors, like roll, economic news releases, time of ...
8
votes
4answers
2k views

How to compute momentum from equity time series?

Let's say I have time series of stock prices for many stocks. What's the best way to sort the stocks based on which have been going up/stayed the same relative to others? Can this be done with a ...
8
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2answers
2k views

How to simulate cointegrated prices

Is there any simple way to simulate cointegrated prices?
8
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1answer
727 views

Are shorter holding period strategies better?

Consider two statistically identical strategies (identical information ratios, sample size, ratio of transaction costs to total profit, etc.) except that one has a much shorter average holding period. ...
8
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2answers
793 views

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia?

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia on a security-by-security basis with a medium term horizon (say 3 month to 12 months horizon)? ...
8
votes
1answer
563 views

Why is the GARCH intercept supposed to be strictly positive?

Maybe it's a simple question but I don't really understand why it is theoretically required. Let's take the standard GARCH(1,1) $$\sigma^2_{t+1}=\omega+\alpha\epsilon^2_{t}+\beta\sigma^2_{t}$$ In most ...
8
votes
3answers
829 views

Is the average of independent Brownian Motions still a Brownian Motion?

If $W$ and $B$ are independent Brownian Motions (BM thereafter), then the average of $W$ and $B$ is $X_t=\frac{1}{2}(W_t+B_t)$. Where do I begin to show that indeed it is still a BM? Also, if both ...
8
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4answers
7k views

Is a stationary process necessarily mean-reverting?

Intuitively, a stationary stochastic process needs to be mean-reverting. This should follow immediately from the definition of stationarity: the mean of the process needs to be constant over time, so ...
8
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4answers
980 views

How is stock data objectively different to this random walk?

I have a random walk that is generated as so using python, numpy, and matplotlib ...
8
votes
1answer
409 views

Is there any measure that is a non-trivial combination of VWAP and TWAP?

Is there any measure that is a non-trivial combination of VWAP and TWAP? For example: \begin{equation} \textrm{VTWAP} = \frac{\textrm{VWAP}+\textrm{TWAP}}{2} \end{equation} I'm thinking about ...
8
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5answers
3k views

Thoughts on how quantitative hedge funds use machine learning to invest in the stock market (algorithms, examples of data, etc.)

I believe there are several post on this general topic but I thought I would start my own thread. I'm a former fundamental hedge fund investor (i.e. modeling a company's financials, forecasting the ...
8
votes
1answer
578 views

Applying models with normality assumption on tick data?

Beginner question. Having read a couple of papers and book chapters on high-frequency data forecasting, I'm surprised (and confused) that the same time series techniques can be applied to high-...
8
votes
1answer
655 views

Is this a viable method for testing market making strategies?

I found a video game market (steam community market) which allows for trading of in game items between users, most items are <0.25 USD each, and market capitalization appears to be maybe $5-$10 USD ...
8
votes
2answers
2k views

How to annualize Expected Shortfall?

I have a time series with monthly data from which I compute the expected shortfall empirically, following the classical definition which can be found, for example, in wikipedia's definition. That is, ...
8
votes
2answers
890 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 ...
8
votes
2answers
1k views

time series management system

I'm happy how we store a single time series but we somehow lack a system that glues them all together. I'm talking about a few million time series coming from ~50 data vendors and representing maybe ...
8
votes
0answers
170 views

Determining Hurst exponent of a Brownian motion

I am trying to determine the Hurst exponent of a simple Brownian motion, however, I seem to get a result that differs from 0.5. I am following the instructions given on the Wikipedia-page, and here is ...
7
votes
3answers
1k views

The Basis of Using Technical Indicators as Inputs

In the process of my research I very often come across academic papers regarding modelling and trading strategies that in one way or another incorporate some technical indicators. For example in some ...
7
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2answers
7k views

How GARCH/ARCH models are useful to check the volatility?

Below a R code wrote by the moderator @richardh (whom I want to thank again) about ARCH/GARCH models. ...
7
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2answers
382 views

Why do I have a statistically significant slope regressing R(t) on R(t-1)

I am reading Cochrane's lecture note here He mentioned that when you regress annual return on time t on that of time t-1, you will have neither statistically significant nor economically significant ...
7
votes
2answers
676 views

Choosing the time-frame to test for cointegration

Is there a technique to choose the time-frame for a cointegration test (eg Augmented Dickey-Fueller's)?
7
votes
1answer
631 views

How to use physics models in Time Series Analysis and Forecasting.

I have been studying methods of Technical Analysis for several years and I am disappointed. I actually do not consider it useful. I have not met anyone who can constantly win in the market using these ...
7
votes
1answer
364 views

Filtering out AR(1) effects before using stochastic volatility model

I wonder if I first filter out AR(1) (autoregressive model with lag 1) effects from univariate time series and then fit stochastic volatility model does above procedure introduce any bias at first or ...
7
votes
1answer
558 views

How can I compare 30 day implied volatility forecasts with GARCH forecasts?

I'm trying to understand whether there is a good way to compare forecasts for volatility from different sources i.e., implied volatility and GARCH. I'll outline a few statements that I believe and if ...
7
votes
2answers
1k views

Is it too important that my residuals be normal? I am Using an ARMA/GARCH model

I am trying to fit an ARMA/GARCH model to a time series. I found that the best candidate is an ARMA(1,0) + GARCH(1,1) with gaussian white noise It has coefficients with p-values near cero and the ...
7
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2answers
2k views

Value at Risk for Futures Contracts

I would like to know how you would compute Value at Risk on a portfolio of futures i.e rates futures, commodity futures and equity. How do you deal with the discontinuous form of commodity futures for ...
7
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0answers
353 views

Why are my GARCH forecasts biased?

I've run an ARMA(1, 1)-GARCH(1, 1) model with normal density on log returns for twelve stocks. I computed the one-step-ahead out of sample forecast for daily volatility on a rolling windows for 500 ...
7
votes
1answer
586 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 ...
6
votes
2answers
449 views

Multifractal Model, Generating Sample Paths with Correlations between Assets

I have studied option pricing using Geometric Brownian Motion to generate sample paths. Because of the normal distribution, it is easy to create a covariance matrix and get correlated asset returns. ...
6
votes
2answers
402 views

Is there any research on pyramiding techniques of entering/exiting a trend?

I am looking for any research about optimal strategies for gradually building (scaling in) positions inside a trend as well as optimal gradual exit strategies on pullbacks/reversals to minimise ...
6
votes
1answer
134 views

How to perform cross-sectional asset pricing regression?

I'm wondering is that possible to get insignificant beta estimates in the time-series context, but highly significant risk premium associated with that beta in the cross-sectional regression? Any ...
6
votes
2answers
262 views

Does predictability in a VAR process imply mean reversion or momentum?

There seems to be some disagreement in the literature about this. Define predicability of a stationary series to be $\sigma^2_{t-1} / \sigma^2_t$ Finding mean reverting portfolios using canonical ...
6
votes
1answer
1k views

Ornstein versus AR(1) for modeling stationary data

I've come across several posts regarding parameter estimation for O-U models given some stationary data (say, some sort of mean reverting spread), but I can't seem to find an answer as to why modeling ...
6
votes
1answer
480 views

Major FX pairs - Pentahedron Data Structure

I read an interview today with Stephane Coquillaud. He talked about this idea of formulating a data set of the G5 currencies as a pentahedron. The obvious benefit is the fact that there is more ...