A sequence of events measured at disrete points in time.

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7
votes
0answers
342 views

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 ...
2
votes
1answer
141 views

Good reference on sample autocorrelation?

I'm not a statistician but I'm writing my thesis on mathematical finance and I think it would be neat to have a short section about independence of stock returns. I need to get better understanding ...
27
votes
5answers
3k views

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 ...
3
votes
2answers
419 views

Entry and exit points for very short mean-reverting timeseries

I have a model specifying a cointegration relationship on a number of transaction-level timeseries. I would like to specify entry and exit points for trades where these points ideally would be just ...
4
votes
1answer
304 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 ...
6
votes
2answers
438 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)?
3
votes
2answers
276 views

central limit theorem and VAR

If I have a lot of data points and number of different dependent variables, can I use central limit theorem to assume data is multivariate normal and compute my VAR? Is this the appropriate use of ...
2
votes
1answer
541 views

a simpler test for normality given skewness, kurtosis and autocorrelation and size of time series

I typically do a JB (Jarque Bera) test and DW (Durbin Watson) tests for check for normality given skewness, kurtosis and autocorrelation of the data. However this requires a CHI distribution table ...
10
votes
3answers
548 views

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. ...
2
votes
1answer
310 views

Is there a measure for the 'degree' of cointegration

Is there a standard (or maybe even intuitive?) way of ranking pairs of cointegrated time series so that one could make statements like the following: ...
10
votes
6answers
1k views

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 ...
8
votes
3answers
448 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 ...
3
votes
1answer
361 views

Linear regression and assets direction prediction

I have the following asset returns Y and the predictions for the same periods Y': Y = { 10, 200, -1000, -1, -7 } Y' = { 1, 2, -3, -4, -5 } The OLR R-squared for ...
10
votes
3answers
302 views

How to account for market movement when some exchanges are closed?

Daily data, such as open and close prices, is often available for much longer periods than high-frequency data. However, whenever backtesting any strategy that examines instruments traded in different ...
7
votes
1answer
1k 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 ...
15
votes
6answers
2k views

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 ...
5
votes
1answer
479 views

How to apply quasi-Monte Carlo to path-dependent options?

Following up on my recent question on variance reduction in a Cox-Ingersoll-Ross Monte Carlo simulation, I would like to learn more about using a quasi-random sequence, such as Sobol or Niederreiter, ...
15
votes
3answers
2k views

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.
8
votes
2answers
811 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 ...
4
votes
2answers
212 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 ...
4
votes
0answers
450 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
448 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
715 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
352 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
votes
0answers
251 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
868 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
401 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
758 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
709 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
386 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
473 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)? ...
11
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
438 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
votes
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
342 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
119 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 ...
18
votes
3answers
4k 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
473 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
556 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
677 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
votes
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
501 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
210 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
233 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 ...