A sequence of events measured at disrete points in time.

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457 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? ...
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1answer
101 views

Book recommendation for time series analysis

I have been trying to wrap my head around Engel-Granger test and jcitest etc. I have failed thus far. If possible can someone guide me about which books to start with and possibly reach to ...
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3answers
245 views

Modeling Financial Time Series

Price time series are not stationary. So we difference them and get the return time series, which are stationary. Does this mean, it is always a good idea to model only the return series of financial ...
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376 views

Selecting timeframe for time series analysis

In technical analysis, we may use confluence of direction for 3 timeframes to roughly gauge bias of market now. Similarly, if we use time series forecasting methods to predict(say daily data-whether ...
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23 views

Time series analysis of PnL with an increasing variance and large negative values [on hold]

PnL can take large negative values, and its variance increases over time as the firm grows. If we do differencing, an increasing variance remains. If we take log, negative values cannot be defined. ...
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96 views

How does Volatility Pairs Trading work?

I've read some material related to pairs trading for equities and I understand the process of finding non-stationary pairs price series that can be cointegrated to form a stationary series. The basic ...
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1answer
139 views

Should I analyze the tick data day by day?

Let assume that we have one month of tick data which were traded at NYSE. We want to model the price changes as a function of the last p lags of price changes and the last q lags of the time duration ...
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49 views

Identifiability for Time Invariant State Space Models

Kevin Murphy's Kalman Filter toolbox (for Matlab) contains an example where it's the fact that the state space system in not identifiable causes problems. I include the example in it's entirety but ...
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1answer
78 views

Intermarket analysis - related time series?

I'm about to embark on training a neural network on daily forex data, with a view to obtaining a predictive network. I'm also interested in using data other than the forex currency pair data itself, ...
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87 views

Fitting Egarch Model

I am performing a monte-carlo simulation in MATLAB for the first order EGARCH model in which case I am simulating 100 paths of size 500 assuming Gaussian and Student's-t distributions for the ...
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1answer
78 views

Can we model components in a set of multivariate multi-period time-series data?

There are N data sets in periods occurring weekly/monthly, across a 10-year historical timeline. In each period, five dates are observed (labelled a to e), where a denotes the day the period ...
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93 views

Modelling interest rate: AR(2) modelling

I have a time series of spread that follows an $AR(2)$ (Autoregressive model of Order 2). I need an interest rate model that represents that dynamics. What model should I use?
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119 views

Should the standard deviation points of CML x-axis be calculated with excess returns?

By excess returns, I'm referring to the current nominal treasury rate minus the log returns of the security. I'm working to construct a dynamic CML / CAPM application, but am uncertain how standard ...
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67 views

Rank financial instruments by price movement stability and outliers

I have a lot of financial instruments and I need to rank them based on price movement "stability", i.e. instruments with with big outliers will have lowest ranks and instruments with stable and ...
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0answers
207 views

Time-varying correlation via state-space representation and Kalman filter

Let a linear time-varying mode like this one: $y_{t}=\alpha_{t}+\beta_{t}x_{t}+\epsilon_{t}$. You can also suppress the constant term to simplify this example: $y_{t}=\beta_{t}x_{t}+\epsilon_{t}$. ...
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240 views

Fluid dynamics for order book depth modelling

Would someone be able to give me an idea what type of fluid dynamics I could look at for modelling the order book? My background is more signals-related maths (correlation, covariance, fourier etc). ...
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36 views

How to make a historical index of a group of materials in which the set of materials changes every month?

The question may sound simple however for the moment it is a brainteaser to get it right, let me explain: the exercise is to be done on +/- 200 groups of materials (matgroups) one matgroup can ...
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236 views

Simple EOD computations for tick data

As part of End-Of-Day calculations once a particular market/exchange has closed for all the tickers traded on that market one may typically compute the following properties: OHLC Bid/Ask Price ...
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40 views

Inferring Returns From Minimal Data Points [duplicate]

Possible Duplicate: How much data is needed to validate a short-horizon trading strategy? Suppose I have daily returns for a trading strategy against one month of data. Before starting ...
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1answer
122 views

Calculate the total returns from the total return index [closed]

I have the Total Return Index(RI) for several companies. I know that I can calculate the log retunrs with $ln(RI_t/RI_{t-1})$. Therefore my first guess would be to ...
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1answer
108 views

Converting time series returns into euro

I am trying to convert various series of returns into one currency (euro). I saw from aprevious post that soemone suggested using conversion factors, where would I find these? Also, given that the ...