Questions tagged [time-series]
A temporal sequence of events measured at discrete points in time.
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Building Financial Data Time Series Database from scratch
My company is starting a new initiative aimed at building a financial database from scratch.
We would be using it in these ways:
Time series analysis of: a company's financial data (ex: IBM's total ...
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Efficiently storing real-time intraday data in an application agnostic way
What would be the best approach to handle real-time intraday data storage?
For personal research I've always imported from flat files only into memory (historical EOD), so I don't have much ...
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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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How are correlation and cointegration related?
In what ways (and under what circumstances) are correlation and cointegration related, if at all? One difference is that one usually thinks of correlation in terms of returns and cointegration in ...
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Time-series similarity measures
Suppose I have two time series $X$ and $Y$ of stock prices. How do I measure the "similarity" of $X$ and $Y$?
(I'm being deliberately vague as I don't have a particular application, and I'm curious ...
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How much data is needed to validate a short-horizon trading strategy?
Suppose one has an idea for a short-horizon trading strategy, which we will define as having an average holding period of under 1 week and a required latency between signal calculation and execution ...
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How do I graphically represent the evolution of a covariance matrix over time?
I am working with a set of covariance matrices evaluated at various points in time over some history. Each covariance matrix is $N\times N$ for $N$ financial time-series over $T$ periods. I would ...
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What is the intuition behind cointegration?
What is the intuition behind cointegration? What does the Dickey-Fuller test do to test for it? Ideally, a non-technical explanation would be appreciated.
Say you need to explain it to an investor ...
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Performance of Open Source Time Series Database for Financial Market Data
We would like to store financial tick data in a database (potentially billions of rows) and then create aggregated (open-high-low-close) bar data from it (e.g. 1min or 5min bars).
It was mentioned ...
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What is the best data structure/implementation for representing a time series?
I was wondering what is best practice for representing elements in a time series, especially with large amounts of data. The focus/context is in a back testing engine and comparing multiple series.
...
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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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How to quickly estimate a lower bound on correlation for a large number of stocks?
I would like to find stock pairs that exhibit low correlation. If the correlation between A and B is 0.9 and the correlation between A and C is 0.9 is there a minimum possible correlation for B and C? ...
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4
answers
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Can the concept of entropy be applied to financial time series?
I am not familiar with the concept of entropy for time series. I am looking for good reference papers and examples of use.
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6
answers
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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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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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2
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Is there a standard method for getting a continuous time series from futures data?
I would like to be able to analyse futures prices as one continuous time series, so what kinds of methods exist for combining the prices for the various delivery dates into a single time series?
I am ...
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How random are financial data series?
Pseudorandom number generators are often tested using e.g. a test suite like Diehard tests or Dieharder. If one would run these tests e.g. on stock market time series or other financial data, would ...
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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 forecast are better suited than risk-neutral models for financial predictions....
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How to check if a timeseries is stationary?
I'm using KPSS Method to check if the series is stationary, but I would also like to use another test to confirm if the series is stationary or not, what method coudl I use?
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How to update an exponential moving average with missing values?
Say you have an Exponential Moving Average being continuously updated over a time series using 1-second-long time periods. What should happen if there is no value for the next second, e.g. there were ...
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Why non-stationary data cannot be analyzed?
Searching online, i found out that non-stationary cannot be analyzed with traditional econometric techniques as in case of non-stationarity some basic model assupmtions are not met and correct ...
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How to detect regime change when estimating asset correlation from historical time series?
Suppose I have two asset time series, $X_t$ and $Y_t$, and I'm estimating their correlation from historical data. I'd like to apply some systematic criterion to estimate what time window I should use ...
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How to generate a random price series with a specified range and correlation with an actual price?
I want to generate a mock price series. I want it to be within a certain range and have a defined correlation with the original price series.
If I choose, say, oil, I want as many time series which ...
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How to forecast expected volatility from high-frequency equity panel data?
I'm wading through the vast sea of literature on realized volatility estimation and expected volatility forecasting (see, e.g. Realized Volatility by Andersen and Benzoni, which cites 120 other papers,...
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Why do we usually model returns and not prices?
I think this is a quite similar question for most of you, however it is not completely understandable for me at the moment:
Why do we usually use returns and not prices to model financial data in ...
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How do I calculate the skewness of a portfolio of assets?
I need to calculate the skewness of a portfolio consisting of 6 assets. I know that for that I would need the co-skewness matrix between the assets. Does anybody know the formula for co-skewness or ...
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answer
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Meta-view of different time-series similarity measures?
While I spend most of my StackExchange time on MathematicaSE, I'm in the business and follow the questions and answers on this site with great interest.
Recently questions like the following (and ...
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What is a good topic on financial time series analysis for master thesis?
Can someone suggest a topic or some reasonably narrow area in financial time series analysis (e.g. statistical, machine learning, etc.) which can make a good topic for a master thesis? By 'good' I ...
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Are two identical time series cointegrated?
I did cointegration test on two identical time series, and the result shows that they are not cointegrated, but intuitively, I think they are.
Can anyone share some thoughts on this? Thanks!
user752
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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 ...
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Time Series Regression with Overlapping Data
I am seeing a regression model which is regressing Year-on-Year stock index returns on lagged (12 months) Year-on-Year returns of the same stock index, credit spread (difference between monthly mean ...
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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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1
answer
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What should be considered when selecting a windowing function when smoothing a time series?
If one wants to smooth a time series using a window function such as Hanning, Hamming, Blackman etc. what are the considerations for favouring any one window over another?
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Is a linear combination of GARCH processes also a GARCH process?
If two time series follow a GARCH process, and a third is a linear combination of them, is the third also GARCH process?
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5
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How to interpolate gaps in a time series using closely related time series?
I am trying to construct a daily time series of prices and returns for some large universe of securities. However, all I have available are a monthly time series of the prices/returns (as well as ...
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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 ...
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R: Fast and efficient way of running a multivariate regression across a (really) large panel (First pass of Fama MacBeth)
I am attempting to run a rolling multivariate regression (14 explanatory variables) across a panel of 5000 stocks:
For each of the 5000 stocks, I run 284 regressions (by rolling over my sample period)...
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3
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Literature on generating synthetic time series for testing
I have some market data (daily time series) for bond prices and CDS indices and I would like to generate synthetic versions of these which are statistically "similar" for testing trading strategies. ...
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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 ...
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GARCH model and prediction
I have a question about the prediction of volatility and returns of a time series. Basically it is a question about predict in the ...
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1
answer
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Can we use White's reality check to compare two Sharpe ratios?
I read a paper from Ledoit and Wolf that proposes a method to compare two Sharpe ratios and a paper from White that proposes a method to compare $n$ trading rules.
My question is: Can we use White's ...
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Are public historical time series available for ratings of sovereign debt?
The nice list of free online data sources What data sources are available online? does not mention any data from ratings agencies.
Are historical time series available for sovereign credit ratings (...
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What methods do I need to learn in order forecast asset price movements?
What are the standard models used to forecast asset price movements? For example, if I were to trade an option, what model would I use in conjunction with option pricing models to forecast the stock ...
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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).
...
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Thesis using Momentum strategies in R, tips on good books, guidelines etc on how to do the programming?
I am quite new to R and will be doing an empirical analysis of momentum strategies in R using a dataset from the index OSEAX from 1980 to 2014. The momentum strategy will for the most part resemble ...
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Alternative ways to understand time-varying comovement between two time-series?
I have been looking into ways to better understand how the dependencies/correlations/etc between two time series can vary over time.
I first thought about using a Kalman/particle filter over a ...
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Can Hurst exponent be used to characterize nonlinear dependence in time series?
It appears to me that the answer is no, because Hurst exponent measures persistence in terms of autocorrelation, which is a linear measure. So even if a time series of asset returns is driven by ...
user2163
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3
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What is a commonly accepted econometric model for volume?
What is the gold standard econometric model for volume? Base model for price changes is the autoregressive (AR) model and GARCH(1,1) for volatility. Is there any survey about econometric models used ...
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How to detect structural breaks in variance?
I'm looking for a method to automatically detect structural breaks, I tried the Chow test, It
works good but it doesn't work for breaks in variance.
Do you know a test to check structural break in ...
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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 ...
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