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

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3
votes
1answer
163 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' ...
2
votes
2answers
124 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
916 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 ...
3
votes
1answer
380 views

How is the MA (moving average model) useful?

How is the MA model useful in modeling financial data, for example the stock indices? For example, from what i understand in the AR (auto-regressive) model portion, we can use the ADF test to check ...
1
vote
3answers
2k views

What does it mean by autocorrelation coefficient near 1?

It is said that the time series has a stochastic trend if the first autocorrelation coefficient will be near 1. Q1) What does it mean by the above statement? Q2) How do we calculate the first ...
6
votes
3answers
7k views

Are public historical time series available for ratings of sovereign debt?

The nice list of free online data sources Data sources online does not mention any data from ratings agencies. Are historical time series available for sovereign credit ratings (other than as ...
9
votes
3answers
2k views

How do I calculate the skewness of a portfolio of assets?

I need to calculate the skewness of a portfolio consisting of 6 assets. I know that for that I would need the co-skewness matrix between the assets. Does anybody know the formula for co-skewness or ...
3
votes
3answers
215 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 ...
2
votes
0answers
90 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 ...
2
votes
3answers
96 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 ...
0
votes
1answer
89 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 ...
3
votes
2answers
517 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 ...
2
votes
1answer
337 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 ...
1
vote
2answers
367 views

Optimizing Principal Component factor weightings over time

I was given the returns of a cross-asset class portfolio of ETFs and I conducted PCA to obtain factors on dates from T-n, T-3, T-2,..., T. What I would like to do is decompose the market moves from ...
4
votes
2answers
218 views

Multifractal Model, Generating Sample Paths with Correlations between Assets

I have studied option pricing using Geometric Brownian Motion to generate sample paths. Because of the normal distribution, it is easy to create a covariance matrix and get correlated asset returns. ...
1
vote
1answer
576 views

Lagged dependent variable, yes or no?

I read conflicting opinions about the inclusion of lagged dependent variables in modeling, and I guess it is partly up to the researcher and depending on the scope and goal of the research. I'm ...
-1
votes
1answer
255 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 ...
1
vote
1answer
384 views

Unsystematic/Idiosyncratic/Firm-specific volatility/variance in the market model?

I was asked to use idiosyncratic volatility as a regressor in a cross-sectional regression upon cross-sectional returns as the dependent variable. Returns can be thought of as the raw log stock return ...
3
votes
0answers
176 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 ...
1
vote
1answer
195 views

Examples of non-increasing variance of a time homogeneous Markovian process

This is an edit to the previous question, on stationary process, which was answered by Richard below. Let $x_t$ be a zero mean, time homogeneous Markovian process over time $t$ starting from ...
1
vote
1answer
293 views

Help with understanding a normal distribution/probability question

Could someone please help me translate what this is saying on page P15, section 4.2: http://www.ntuzov.com/Nik_Site/Niks_files/Research/papers/stat_arb/Ahmed_2009.pdf Specifically: When the ...
4
votes
0answers
177 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 ...
2
votes
0answers
173 views

Potential pitfalls in the use of correlation

Background: The red line is an index, which goes from 0 to 100, measuring uncertainty in the markets. The dark blue line is a price index, which has a lower bound at 0, and virtually no upper bound. ...
11
votes
3answers
482 views

What is a commonly accepted econometric model for volume?

What is the gold standard econometric model for volume? For example, a common model for price is the autoregressive (AR) model with GARCH(1,1) innovations. Do you know of any good survey articles ...
5
votes
2answers
920 views

What are common methods for modeling intraday trading volume?

What are the most common ways to model intraday trading volume, particularly for futures contracts? There are obviously a number of seasonal-type factors, like roll, economic news releases, time of ...
2
votes
1answer
335 views

Interpretation of cross-correlation matrix when one sample distribution is not normal

I am looking at the variance of (log) price changes in securities vs. the amount of social media discussion about them. I'm not interested in building a model. I'm just looking to see if there is a ...
13
votes
6answers
21k views

How to check if a timeseries is stationary?

I'm using KPSS Method to check if the series is stationary, but I would also like to use another test to confirm if the series is stationary or not, what method coudl I use?
5
votes
1answer
197 views

From $AR(p)$ to SDE

Let the Vasicek model to be $$\Delta r_{t}=k(\theta - r_{t-1})\Delta t+\sigma\Delta z_{t}$$ Due to the fact that $$\Delta r_{t}=r_{t}-r_{t-1}$$ if you let $\Delta t=1$, it is easy to see by ...
2
votes
3answers
490 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 ...
1
vote
1answer
1k views

How to apply Ljung Box Test?

I am checking the closing prices(about 9000+ prices) of the stocks data to test for randomness. The test I am using is Ljung Box test, in MFE toolbox for MATLAB, I used 300 data of closing prices, ...
0
votes
0answers
99 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?
22
votes
6answers
5k views

Time-series similarity measures

Suppose I have two time series $X$ and $Y$ of stock prices. How do I measure the "similarity" of $X$ and $Y$? (I'm being deliberately vague as I don't have a particular application, and I'm curious ...
2
votes
0answers
271 views

Test for stationarity and make use of non-stationary points in financial market?

I have two questions to ask: What are the best methods to determine stationarity in a financial market (such as stocks) using MATLAB? What methods would you recommend to use in order to change from ...
6
votes
2answers
4k views

Using variance ratios to test for mean reversion

Can you use the variance ratio test to determine whether or not a time series is mean reverting? I'm using the Lo.Mac function in the ...
2
votes
3answers
408 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 ...
11
votes
5answers
2k views

How to interpolate gaps in a time series using closely related time series?

I am trying to construct a daily time series of prices and returns for some large universe of securities. However, all I have available are a monthly time series of the prices/returns (as well as ...
6
votes
2answers
5k views

How GARCH/ARCH models are useful to check the volatility?

Below a R code wrote by the moderator @richardh (whom I want to thank again) about ARCH/GARCH models. ...
0
votes
0answers
287 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: $y_{t}=\beta_{t}x_{t}+\epsilon_{t}$. ...
-1
votes
1answer
152 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 ...
0
votes
0answers
276 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). ...
2
votes
0answers
960 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 ...
2
votes
1answer
906 views

Counterintuitive time varying Beta with Kalman filter

If you're used to play with R, you'll enjoy the following reproducible code: ...
0
votes
0answers
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 ...
6
votes
2answers
270 views

How to deal with zeroes in returns?

Suppose there are two time series that I want to analyze and compare. However, many, or most, of the data are zeroes for some reason. For example, consider a pair of intraday trading returns time ...
0
votes
0answers
258 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 ...
2
votes
1answer
350 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
3answers
628 views

How to annualize dividends paid at varying intervals?

I am attempting to write a function that will calculate the annualized rate of return for individual dividends made by illiquid investments. These dividends are paid at varying intervals and the ...
2
votes
1answer
729 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, ...
2
votes
3answers
887 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 ...
13
votes
4answers
11k views

Why are GARCH models used to forecast volatility if residuals are often correlated?

The answers to this question on forecast assessment suggest that if the sequence of residuals from the forecast are not properly independent, then the model is missing something and further changes ...