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

learn more… | top users | synonyms

3
votes
2answers
497 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
2answers
81 views

Does heteroskedasticity of returns depend on the time frame?

Similarly to my last question, for which I obtained very interesting and useful answers, I would like to know if there has been any study regarding heteroskedasticity and time-frames of the returns. ...
3
votes
2answers
92 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
3answers
100 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 ...
3
votes
1answer
419 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 ...
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
242 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
110 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
1answer
524 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
166 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
1answer
3k views

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 prediction in the ...
3
votes
0answers
56 views

DCC GARCH - Specificating of ARCH and GARCH parameter Matrices STATA

The command in STATA to calculate the DCC model of two variables is: mgarch dcc ( x1 x2=, noconstant) , arch(1) garch(1) distribution(t) $$ \begin{bmatrix} ...
3
votes
0answers
92 views

Filtering out AR(1) effects before using stochastic volatility model

I wonder if I first filter out AR(1) (autoregressive model with lag 1) effects from univariate time series and then fit stochastic volatility model does above procedure introduce any bias at first or ...
3
votes
0answers
151 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
178 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 ...
3
votes
0answers
204 views

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

I want to fit the following model to a time series: $$ y_{t}=\alpha_{0}+\alpha_{1}y_{t-1}+\alpha_{2}y_{t-1}^{2}+\lambda h_{t}+\varepsilon_{t} $$ $$ ...
2
votes
3answers
412 views

Why do long-term equity return forecast models use dependent observations?

I've been reading up on different models used to forecast the equity risk premium, and I've seen a couple of papers that had questionable methods. For example, this paper by Javier Estrada goes into ...
2
votes
2answers
1k views

Squared and Absolute Returns

I've always wondered why do one use squared or absolute returns to determine if volatility modeling is required for the return series? We understand that there are various tests for its ...
2
votes
2answers
3k 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 ...
2
votes
3answers
494 views

Time Series or Regression

I'd like to research the impact of certain events and characteristics on the liquidity of the stocks over time. I've got a sample of 200 stocks and I use several measures of liquidity (Amihud, Bid-Ask ...
2
votes
3answers
265 views

Calibration of a GBM - what should dt be?

I have a time series of daily data that I want to calibrate GBM parameters $\mu$ and $\sigma$ to. Using the discretized solution $$ S_{t_{i+1}} = S_{t_i}\exp\left(\left(\mu - ...
2
votes
2answers
211 views

Intraday Data - Stylized Facts?

Can someone give an overview or literature on Intraday Data Stylized Facts? In particular for equity market returns or exchange rates.
2
votes
3answers
446 views

Transaction Data with Participant ID

For my master thesis, I need high-frequency data with the market participant ID or which identifies the trading parties, respectively. I don't need the entire orderbook but just the matched orders ...
2
votes
3answers
904 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 ...
2
votes
1answer
419 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: ...
2
votes
1answer
220 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 ...
2
votes
2answers
177 views

Does unit root stationary imply mean stationary and variance stationary?

Newbie question. I am reading about stationary series and understand that it has many forms: mean stationary variance stationary covariance stationary My question is does unit root stationary ...
2
votes
1answer
244 views

Testing for stationarity in large sample sizes

I keep struggling with testing 9 samples if they are stationary. Each of these samples is a real valued time series with 714.000 values. If I use the KPSS test with the each compleete sample set, the ...
2
votes
3answers
583 views

What data transformations to use in regression of credit spreads on equity prices?

Clearly there is a strong relationship between credit spreads and equity prices (both theoretically and empirically). But how would one go about formulating a regression which seeks to explain this ...
2
votes
1answer
122 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 ...
2
votes
1answer
332 views

How to interpret ACF and PACF plots

I just want to check that I am interpreting the ACF and PACF plots correctly: The data corresponds to the errors generated between the actual data points and the estimates generated using an ...
2
votes
2answers
242 views

What is the best way of updating data while using Empirical Mode Decomposition to analyze

I have a question about EMD updating new data points. For an entire time series, from beginning to the end, the EMD preforms quite good using the cubic spline function. The problem happens when new ...
2
votes
1answer
482 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 ...
2
votes
1answer
216 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 ...
2
votes
2answers
127 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 ...
2
votes
1answer
940 views

Counterintuitive time varying Beta with Kalman filter

If you're used to play with R, you'll enjoy the following reproducible code: ...
2
votes
2answers
166 views

What are the proper metrics to look at for checking discrepancies in these two time series

I am obtaining bid/ask price and volume market data from two different sources for the same ticker and for the same day and checking to see that at time intervals X they are "roughly the same". The ...
2
votes
1answer
382 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
67 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 ...
2
votes
1answer
112 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 ...
2
votes
1answer
142 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 ...
2
votes
2answers
200 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 ...
2
votes
1answer
50 views

What are the properties of the Expected Shortall measure when split in multiple time periods?

Suppose I have a single time series of losses $L$ that consists of two sub-parts $L_1$ and $L_2$. Is there a relationship that relates the expected shortfall of $L$ to the expected shortfall of $L_1, ...
2
votes
1answer
989 views

Value Weighted Return

I recently have started to look at some data from CRSP, and they have a metric called Value Weighted Return (two versions with and without distributions). When I looked it up, it seemed that this ...
2
votes
3answers
97 views

how to back out levels from a forecast of differenced series

I have a non-stationary series of bond yields $x_{t}$ that are logged and differenced $$y_{t}\equiv ln\left(x_{t}\right)-ln\left(x_{t-4}\right) $$ From that, I get a series of forecasted values ...
2
votes
1answer
355 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 ...
2
votes
1answer
225 views

Event studies using revenue data vs. measuring abnormal returns

This may be a silly question, but does there exist a methodology for examining the impact of "events" on companies that are not publicly traded? I suppose it would look at abnormal revenues rather ...
2
votes
2answers
214 views

How to synchronize put and call option-data?

I recently retrieved a large amount of European option data, for call and put prices, from OptionMetrics. Doing so for the same time period I get a file consisting of 62558 rows of call prices & ...
2
votes
1answer
358 views

Stepwise Cointegration

This is more of a general question at this point, but if my thought process makes sense I will follow up with an R implementation. I have read a number of papers on cointegration analysis for pairs ...
2
votes
1answer
743 views

Predict Quadratic Trend in Time Series

Can anyone kindly point out if I made any mistakes in making predictions using quadratic regression model in time series? I called the predict() function with the appropriate data vector and model, ...