A sequence of events measured at disrete points in time.

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2answers
263 views

What's the difference between SA and SAAR?

I've only recently begun working in the quantitative finance field, and I've noticed that some time series I'm given are labeled "seasonally adjusted", and some labeled with "seasonally adjusted ...
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0answers
471 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 ...
2
votes
2answers
2k views

Calculating Portfolio Skewness & Kurtosis

I need to calculate the skewness and kurtosis of 2 asset portfolio, can someone please help me with the formulas and definition of terms? Thank you. I have been using the matrices method and I am not ...
4
votes
0answers
532 views

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 ...
3
votes
3answers
766 views

How to normalize Futures data(different leverage) for cointegration test?

For example I want to construct 2 time series, one for ES and the other for NQ and test for cointegration. ES one point equal to 50$. NQ one point equal to 20$. If I have the following data: ...
10
votes
2answers
359 views

How to “uncluster” a set of financial data?

I am attempting to evaluate and compare the profit factor of different "test runs" of a FOREX trading strategy. My problem is that, despite an average time between orders of 2hr+, some of these runs ...
2
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0answers
258 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 ...
5
votes
4answers
987 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 ...
5
votes
1answer
429 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 ...
7
votes
1answer
806 views

Why does the following data fail my cointegration test?

I have some closing price data for two Australian banks which track each other very closely. http://dl.dropbox.com/u/12337149/stat/CBA.csv http://dl.dropbox.com/u/12337149/stat/WBC.csv Code from ...
11
votes
2answers
771 views

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 ...
13
votes
1answer
396 views

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?
7
votes
2answers
529 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)? ...
12
votes
2answers
1k views

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 ...
6
votes
1answer
456 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. ...
20
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2answers
2k views

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 ...
7
votes
1answer
3k views

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 ...
2
votes
1answer
356 views

Techniques for forecasting short-frame data?

I'm having a problem in which a time series of 24 data points is given to forecast the next 12 data points. This 24 data points might be sparse (many are missing). Do you have any suggestion on what ...
2
votes
1answer
123 views

How to reconstruct a discontinued economic time series such as the Fed's CP rate?

The old 3-Month Commercial Paper Rate (CP3M) on FRED was discontinued in 1997. I would like to reconstruct this series in a reasonable fashion, so I can use it to analyze more recent events. I was ...
19
votes
3answers
5k 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?
7
votes
1answer
492 views

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 ...
5
votes
0answers
576 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 ...
5
votes
2answers
690 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 ...
3
votes
1answer
2k views

How to estimate a multivariate GJR or TARCH model in Eviews?

How do I specify the GARCH/TARCH equation in Eviews 6 in the variance regressors frame, if I want to find out whether there are volatilty spillovers from stock markets A and B to stock market C? P.S. ...
14
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2answers
1k views

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 ...
11
votes
1answer
1k views

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 ...
6
votes
1answer
564 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, ...
2
votes
1answer
214 views

Picking from two correlated distributions

Can anyone provide a simple example of picking from two distributions, such that the two generated time series give a specified value of Pearson's correlation coefficient? I would like to do this in ...
3
votes
3answers
234 views

estimating the accuracy of a method for forecasting the distribution

Say for a stock I want to do a simulation using 30 days of historical returns, and maybe generate 1000 paths, with 2 days as the forecast horizon. Say I have 100 of these 5 day blocks used for ...