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

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3answers
118 views

Modelling currency exchange rates timeseries data across re-denomation dates

I am working with data for an exotic currency, that has been re-denominated a couple of times during the twenty years of data that I have. What is the best way of 'normalising' the data, so that I ...
4
votes
1answer
343 views

Ornstein versus AR(1) for modeling stationary data

I've come across several posts regarding parameter estimation for O-U models given some stationary data (say, some sort of mean reverting spread), but I can't seem to find an answer as to why modeling ...
4
votes
1answer
1k views

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 ...
4
votes
1answer
206 views

ARIMA model, cannot get rid of low order ACF spike

I've gone through all the steps to fit a good ARIMA model - I plotted the data, I looked at the ADF tests, I looked at the ACF plot with no AR and MA terms just a constants. I came up with an ...
4
votes
3answers
1k views

Pairs trading: Question on non-negative profits, size of the positions and trading signals

I'm trying to backtest Pairs Trading but have become a bit confused on the different methods of selecting pairs, how to look for trading signals and what size of the positions to take in the assets. ...
4
votes
1answer
436 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 ...
4
votes
1answer
101 views

Is that a good way to work with the ARMA model?

I would like to share with you what I am doing to get your point of view, and to make a better trading system in collaboration. I am working on EURUSD forex, and I am trying to find a way to place ...
4
votes
2answers
240 views

How to trade a Ratio?

I came across a ratio plotting of Corn And Soybeans contracts, notice it's in a historical low, an intuitive question came to my mind, how should I trade this ratio (or relationship)? It's unlike flat ...
4
votes
1answer
182 views

Simulating state space model with AR(1) dynamics

I asked a question similar to this previously: https://dsp.stackexchange.com/questions/16341/simulating-a-state-space-model However I think I have a better handle on it now and want to re-ask it: I ...
4
votes
1answer
218 views

Fitting a non linear AR + GARCH(1,1)-M model

I want to fit the following model to a time series: $$ y_{t}=\alpha_{0}+\alpha_{1}y_{t-1}+\alpha_{2}y_{t-1}^{2}+\lambda h_{t}+\varepsilon_{t} $$ $$ ...
4
votes
0answers
201 views

How to forecast high-frequency data?

Introduction: I have seen a plenty of articles/books regarding volatility forecasting applied to high frequency data, but none of them were dedicated to forecasting the actual prices (for example ...
4
votes
1answer
178 views

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 ...
4
votes
1answer
294 views

Measuring momentum as AR(1) process

I would like to measure the momentum in the price of a stock from the time the market opens until the time I trade each day. I want to use this momentum number in post-trade analysis (regression of ...
4
votes
0answers
200 views

How can I introduce exogenous variables in the equation of the conditional variance?

Is it possible to introduce dummy variables or explanatory variables in the GARCH variance equation (garchset and garchfit).This is done in the mean (ARMAX) equation through the input 'Regress' in ...
4
votes
0answers
158 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 $f(\cdot)$ ...
4
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0answers
646 views

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, ...
4
votes
0answers
499 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 ...
4
votes
0answers
748 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
2answers
207 views

Relationships between white noise and random walk

I would like to ask 5 questions about relations between these processes. 1) Could white noise be also a random walk? 2) Could random walk be also a white noise? 3) Could white noise be stationary? ...
3
votes
2answers
723 views

How to remove outliers in financial times series?

I have a bunch of time series; i need to clean them before modelling. So far I just know the “filtering/smoothing” method : -Ex: moving average methodology (filter the data with a moving average ...
3
votes
3answers
220 views

Is the number of outstanding shares a stationary series?

I'm doing a panel data analysis where the log of the freefloat number of outstanding shares is one of the explanatory variables, but it fails the Augmented Dickey Fuller and Person Phillips unit root ...
3
votes
1answer
490 views

knowing the order of GARCH model

I want to ask if there is a situation to know the order of GARCH(p, q) from the result. For example, in the case of AR(p), one can know the value of p by plotting pacf(). In case of MA(q), one can ...
3
votes
5answers
167 views

economic facts that causes the financial time series to be heavy tailed

When reading a tutorail on extreme value theory, I once meet the following claim ...
3
votes
2answers
324 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 ...
3
votes
3answers
1k views

Analyze raw tick data

I'd like to work with raw tick data and naturally this data is unevenly spaced (for example, a couple of quotes are at the same second etc.) For example ...
3
votes
2answers
523 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 ...
3
votes
1answer
454 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: ...
3
votes
1answer
171 views

Shannon's entropy for financial times-series (return)

I'm looking at Shannon entropy, and generaly at ways to tell noise from signal when observing intraday returns (at the minute level for now). In python, e.g. I've implemented the fomula (sum of ...
3
votes
4answers
311 views

Unsmoothing of returns

The following problem arises in the context of private equity, which typically report "smoothed" returns (think of it as a moving average). As you can imagine, "smoothed" returns would have a much ...
3
votes
1answer
187 views

rollapply with Arima model: testing for stability of coefficients

I am trying to fit an arima model on a rolling window using rollapply.My aim is to plot a graph of the evolution of the coefficient, plot the error and the standard deviation. well i encountered the ...
3
votes
1answer
285 views

Stress Testing Methods

I'm working on the following task: Given quarterly data: a time series representing the 1-year realized (10 years of data) rates of default on a portfolio of mortgages a slew of ...
3
votes
1answer
130 views

Volatility updating rule using r

I'm trying to program a volatility updating rule using iteration. I start with the well know Heston-Nandi model where the returns dynamics are : with is iid standard normal randome variable, where ...
3
votes
1answer
178 views

Estimating Beta from unevenly spaced price history

I have a certain non-stock asset that has 1 transaction every 1 to 8 months. I also have a price index of that class of asset compiled by another party on monthly basis. If I regress $price = \alpha' ...
3
votes
2answers
137 views

What impact does arbitrage have on realised volatility estimates?

Doing some research modeling/estimating volatility in the bitcoin market. There is quite a bit of scope for arbitrage within crypto-currency markets. Wonder if this has any impact on my volatility ...
3
votes
1answer
460 views

How should we select efficiently orders parameters in time series modelling?

A common way to select orders parameters (ex: to choose the number of AR terms to be included in the model ) in time series modelling is to rely on some Information Criteria (AIC, BIC, Hannan ...
3
votes
1answer
3k 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. ...
3
votes
3answers
243 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 ...
3
votes
1answer
93 views

volume-returns cross correlation interpretation

I want to find the relationship between volume and price returns in the S&P500. My first thought was to run a cross correlation in order to find who leads and who lags in the relation. It´s my ...
3
votes
1answer
74 views

compute technical indicators from candle data

i have a rookie question but can't find the answer anywhere so..what is the right way to compute a simple moving average when you have an array of (open,close,low,high) tuples ? From what i saw so ...
3
votes
1answer
134 views

What is the best data structure/implementation for representing a time series in C#?

I'm looking for a tick by tick high performance container. So far I've been using List where Tick is a simple struct with a DateTime and double field. I'm using Linq for date lookups but it's ...
3
votes
1answer
96 views

Accuracy of GARCH& ARCH forecast

I'm learing ARCH&GARCH model. I have four questions that I don't know the answers 1st: ARCH & GARCH are often used to evaluate equities. Does it mean that ARCH and GARCH are fitter for high ...
3
votes
1answer
129 views

What are recent important papers on credit portfolio risk modeling?

I'm interested in papers which consider mathematical models of risks of different portfolios of retail credit. This is not my area of research, so I may be misusing some terms. The idea is simple: I ...
3
votes
2answers
286 views

How to find the best fitting GARCH model for a portfolio composed of 3 ETFs in R?

I am doing a project for my class Financial Time Series in which I am trying to forecast my portfolio log returns using a GARCH fit. I am having a bit of trouble determining the best way to fit this ...
3
votes
1answer
786 views

How to Calculate Confidence Intervals for Moving Averages Given Nonindependence?

I've plotted 30-year moving averages across time for a couple of portfolios, and I was wondering how to calculate a 95% CI for the these moving average data (i.e., across all moving average data ...
3
votes
1answer
307 views

Average beta of index consitutents w.r.t. the index is 0.60

I have 1 year time series data of 300 constituents of the Australian All Ordinaries index (which is composed of 491 firms). The missing firms are mostly smaller firms. I run the market model $R_{it} ...
3
votes
1answer
108 views

Applying Time Delay Neural Network to financial events

I have an IT background and I would like to use data from a forex calendar like this one to predict prices. The problem is that calendar news impacts can last for days or weeks or even can effect ...
3
votes
0answers
174 views

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. ...
3
votes
0answers
111 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 ...
3
votes
0answers
98 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 ...
3
votes
0answers
190 views

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 ...