Questions tagged [time-series]

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

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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 ...
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10 votes
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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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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 ...
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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 ...
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  • 191
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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 ...
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8 votes
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250 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 ...
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  • 181
8 votes
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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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  • 121
6 votes
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469 views

Calculating volatility of inhomogeneous time series

I am reading an article by Zumbach and Müller whose name is Operators on Inhomogeneous Time Series. This is interesting in general, but my main goal is to learn a good and efficient method to ...
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Asymmetric Volatility Modeling (Interpretation)

I am currently writing a paper on asymmetric volatility modeling of brent, gold, silver, wheat, soybean and corn from 1986-2012 and divided them into 4 sub-sample periods (i.e. 1986-1991, 1991-1997, ...
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  • 111
5 votes
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177 views

How to model financial HFT time-series data with multi scale autocorrelation

I work with tick level time-series univariate prices data. Tick level means that there are hundreds to thousands observations per second. The observations are timestamped, so one can use both wall ...
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5 votes
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344 views

Fourth moment of ARCH(2)

I am studying the ARCH(2) process given by $$X_t = \sqrt{h_t} \varepsilon_t$$ where $$h_t = \alpha_0 + \alpha_1 X_{t-1} ^2 + \alpha_2 X_{t-2} ^2$$ and $\varepsilon_t$ follows $N(0,1)$. ...
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GMM time-series regression factor model with factors that are not returns

Factor models with factors that are not returns are usually estimated and tested by cross-sectional regressions. However, there is a way to use time-series regression to estimate and test the model. ...
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  • 151
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Hasbrouck's information share

Given a cointegrated set of price series, I am trying to compute the Hasbrouck's information share, as described in page 12-13 of this article. page 7-8 of this article I have the vector error ...
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4 votes
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360 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 ...
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4 votes
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136 views

Comparison of normalization methods on market returns

I am looking to use a multi-factor model to make target-return predictions. Since the factor-returns come from different scales I need to normalize first. There are different ways to normalize ...
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4 votes
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Is non-stationarity an issue during copula estimation?

In this paper (1), on page 14 (section 4), the author presents an empirical experiment on the computation of a copula through the use of kernels. To do so, he uses the following stochastic process (...
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4 votes
2 answers
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Are there alternatives to the Box-Tiao decomposition in identifying mean reverting portfolios?

As documented in this paper, (Identifying Small Mean Reverting Portfolios, by Alexandre d’Aspremont, February 26, 2008) Box-Tiao decomposition (a way to decompose multiple time series into components ...
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4 votes
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Time series (stochastic process) estimating parameters using characteristic function

I have a time series of assets ${A_1, A_2, ..., A_n}$, which is described by a sophisticated distribution having the following characteristic function: $\phi(u; t;\theta)$, where $\theta$ is a vector ...
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4 votes
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212 views

Is it random walk?

I would like to ask a question about random walk. Campbell, Lo & Mackinlay defined the random walk, in the following way (RW3): $$ cov[f(r_{t}),g(r_{t+k})]=0,\qquad k\neq0 $$ for all $f(\cdot)$ ...
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4 votes
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589 views

Algorithms for predicting a couple points in the future

I'm familiar with supervised learning algorithms like regression and neural networks which look at a bunch of input points and learn a function which outputs a value (the value varying depending on ...
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4 votes
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332 views

What does T statistics of Information Coefficient indicate?

Hi I am looking for a clear explanation of T statistics concept. Especially in quantitative equity portfolio management context, what does T statistics of monthly Information Coefficient for one ...
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3 votes
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253 views

Does the Shannon entropy of stock returns change over time?

Shannon entropy, $H(X) = -\sum_{i=1}^n p(x) \ln p(x)$ is a probabilistic measure of randomness or disorder within a random variable's probability distribution or histogram. If we take rolling window ...
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3 votes
1 answer
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GARCH(1,1)-M MLE optimization with fmincon in R

I've searched thru dozens of papers and did not find in any of them satisfying and enough theoretical answers to my concerns. So I've combined everything what I found below. Please indicate if my ...
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3 votes
0 answers
99 views

Expected Shortfall for ARMA-GARCH Model

I need to find an analytical solution for the 99% confidence expected shortfall (CVaR) for a long position of 100 dollars at time $t$ for an asset with returns modeled by an ARMA(1,1)-GARCH(1,1) model ...
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3 votes
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86 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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3 votes
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132 views

Detecting leading stocks using lag correlation

I am working on a project to find leading stocks in a stock market by using lag correlation. Say I want to compare 2 stocks, X and Y, and I have the time series of stock prices. Assume that the ...
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3 votes
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39 views

Binary probit model: relevant which outcome is 1?

I'm currently working on predicting bear and bull phases with a dynamic probit model in the form of $y_t=\beta_1X_t+\gamma_1y_{t-1}+\epsilon_t$. So far I've written all my code in matlab and it works ...
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  • 115
3 votes
0 answers
106 views

VAR models when examining relationships between financial markets

When researchers examine lead-lag relationships between credit default swaps and (as an example) stock markets, many use Vector Autoregressive Models (VAR). They want to find out what market "is ...
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3 votes
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'GARCH - extreme value theory - copula' approach to estimate risk measures in R

I'm reading about this approach of using GARCH-EVT-copula methodology to separate univariate and joint estimation and then estimate for example VaR and ES. I wanted to try something similar, but my ...
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3 votes
0 answers
244 views

Marginal Distribution using GARCH model: How to do inverse probability transform?

I have $n$ return series. I fitted AR(1)-GARCH(1,1) to each return series. Then used probability integral transform, PIT(residuals), to transform the residuals to have a uniform distribution. Then I ...
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3 votes
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231 views

When to use SV or a GARCH model

So i have been searching for this answer for a question if there is a rule or something that would say when to use GARCH type model or use an stochastic volatility model to predict the volatility of ...
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3 votes
0 answers
193 views

State Space models with Short Time Series

My problem is that I have a state space model that I estimate using the Berndt–Hall–Hall–Hausman (BHHH) algorithm. The state space model is relatively simple in that the hidden part follows a pure AR(...
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3 votes
0 answers
211 views

Derivation of variance of Zhou (1996) volatility estimator

Does anyone know how to derive the Variance of Bin Zhou's volatility estimator (Theorem 1) in 'High-Frequency Data and Volatility in Foreign-Exchange Rates' (1996) Zhou 1996 Any help would be ...
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3 votes
0 answers
674 views

Test for stationarity and make use of non-stationary points in financial market?

I have two questions to ask: What are the best methods to determine stationarity in a financial market (such as stocks) using MATLAB? What methods would you recommend to use in order to change from ...
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3 votes
0 answers
88 views

Is there an appropriate sequence to tests during model diagnosis?

How should one order (sequence) the following tests? Stationarity test Johansen cointegration test Normality/Histogram test Autocorrelation test Heteroskedasticity test Multicollinearity test Or, ...
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3 votes
0 answers
568 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? http://sg.myfreepost.com/sgTOTO_analysispower.php?...
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2 votes
0 answers
134 views

Copula Models for Asset Returns

I'm learning about copulas and their applications in finance. When used to assess the dependence structure between two indices for example, can the copula models be estimated directly on the log-...
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2 votes
0 answers
90 views

Fitting ARIMA + GARCH in R

I'm forecasting Electricity consumption Data. I have data for one year , so for every 15 minutes there is an observation. My data contains seasonality and I don't know how to fit SARIMA + GARCH into R,...
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2 votes
0 answers
82 views

What do I need the Error correction model for in the two step Engle Granger approach (bivariate Cointegration)

could someone kindly explain what I need the ECM for in a bivariate Cointegration test? I am currently trying to reproduce the results of Rad et al. (2015): "The profitability of pairs trading ...
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2 votes
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65 views

Electricity Futures Risk Premiums With ARIMA

I am attempting to model long-term electricity prices using today's futures prices. Unlike most futures, electricity is delivered over a period of time (usually a month), rather than at a point in ...
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2 votes
0 answers
92 views

Defining the Average Length of Business Cycle using AR(p) model

I'm currently reading through Analysis of Financial Time Series by Ruey Tsay. The AR model is introduced in chapter 2 and its properties in 2.4.1. The difference equations are explained and then its ...
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2 votes
0 answers
109 views

Cointegration where first differences are not jointly stationary

Note: This is a crosspost from this post on cross-validated, where it did not receive an answer. I thought I might have better luck here. I am looking for a rigorous and general treatment of ...
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2 votes
0 answers
33 views

Models that can improve FHS (with possible residuals manipulation)

The Filtered Historical Simulation (FHS) is a tough benchmark. By: choosing among the most complicated ARMA-GARCH variants with automatic model and lag selection, manipulating standardized residuals ...
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  • 2,046
2 votes
0 answers
201 views

Variance Ratio Test shows mean-reverting trend but Hurst exponent is greater than 0.5

I believe Hurst Exponent greater than 0.5 indicates persistent series, meaning the values are not mean-reverting. However, when I run a variance ratio test, I get a graph clearly showing mean ...
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2 votes
0 answers
44 views

Non-Linear Time-Dependent Volatility

My data consist of monthly electricity futures contracts. Unlike other commodities, electricity is delivered throughout a month (rather than on a specific date), which means that, as the active month ...
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2 votes
0 answers
497 views

How to set up the dummy variable for OLS event study regression

I've been going back and forth with how I should work to find an event effect. would be so grateful for some clarification. I have daily time series of exchange rates for different countries ( 1 for ...
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2 votes
0 answers
75 views

What is the correct order of operations when cleaning and structuring financial time series?

I'm studying Lopez' Advances in Financial Machine Learning where he talks about how to sample and structure financial data, as well as how to apply machine learning models to the data. I am also ...
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2 votes
0 answers
135 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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2 votes
0 answers
91 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)...
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2 votes
0 answers
88 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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