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

learn more… | top users | synonyms

0
votes
0answers
72 views

Interpretation of Cointegration results, pValues and t-Stat

This is a follow up to: Cointegration results interpretation validation? I ran another Engel Granger Test on a pair, The results I get: ...
3
votes
0answers
81 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 ...
15
votes
6answers
6k views

What is the intuition behind cointegration?

What is the intuition behind cointegration? What does the Dickey-Fuller test do to test for it? Ideally, a non-technical explanation would be appreciated. Say you need to explain it to an investor ...
1
vote
1answer
133 views

Normalization of Market Data in Time Series Correlation

Suppose we have 2 time series of market data, one for each security and we want to correlate between these 2 securities. My question is How do we handle gaps of missing data in the time series? ...
2
votes
3answers
203 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 - ...
1
vote
1answer
64 views

How to model the effect of earnings surprises on long-term returns?

I'm looking into modeling the relationship between EPS announcement surprises with long-term returns (1 quarter to 3 years with intervals). I've based my current methodology off papers looking at the ...
0
votes
0answers
19 views

Residual maturity vol

The following question is probably (from a practical point of view) more relevant for EM markets which typically exhibit a more pronounced forward volatility compared to spot volatility. Say I buy a ...
4
votes
3answers
238 views
1
vote
0answers
160 views

What machine learning method is more suitable for prediction of financial time series? [closed]

I have some time series from a stock exchange market. For each of them, I want to answer the question that whether the price will grow at least p percent in the d coming days or NOT(and during these ...
2
votes
1answer
49 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, ...
3
votes
0answers
139 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. ...
10
votes
3answers
361 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 ...
2
votes
2answers
194 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.
1
vote
1answer
155 views

detecting and measuring lead lag effect

Given two time series data. I remember there is one statistics that tells you one is the leading factor while the other is the lagging factor. However, i do not remember the exact details. correlation ...
1
vote
1answer
122 views

Explain drop in Correlation between two time series in consecutive periods

I have a time series for a security list with 2 parameters calculated for each time period. For example, for a stock XYZ, I have Param1 and Param2 calculated over various time periods stacked against ...
1
vote
1answer
418 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 ...
0
votes
0answers
336 views

Exporting Time Series Data For Securities Prices From Bloomberg to Excel

I have a list of securities over a thousand entries long that I want to construct a time series of prices for over a specified historical period (e.g. 2/01/10-2/20/10). Doing this manually would take ...
1
vote
0answers
59 views

Rule of Thumb for minimum length of time series for AR(1) estimation

I have a data set of 350 points, I want to estimate the lag 1 auto correlation for different sub-sets of the data. More precisely I want to take non overlapping windows of length 1,2,3....n and ...
1
vote
1answer
187 views

Estimate correlation of time series whose histories differ in length

Very often in quantitative analysis (e.g. calculating portfolio volatility) we have to analyze various time series - mostly returns - whose lenghts differ. Risk systems usually apply a one-factor ...
1
vote
1answer
209 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 ...
3
votes
3answers
97 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 ...
2
votes
0answers
95 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 ...
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. ...
1
vote
1answer
169 views

Simulate non-stationary time series with cointegration

how can I simulate/generate two non-stationary time series (with unit root) so that they can be also cointegrated (using R or Matlab). Thanks in advance.
6
votes
6answers
6k views

Why non-stationary data cannot be analyzed?

Searching online, i found out that non-stationary cannot be analyzed with traditional econometric techniques as in case of non-stationarity some basic model assupmtions are not met and correct ...
0
votes
1answer
164 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 ...
1
vote
1answer
171 views

High correlation will help detect spurious regression over cointegration?

I'm analyzing two financial time series with Johansen method. A high Correlation coefficient using the Pearson method will help me to detect spurious cointegration models to avoid? If this is not ...
2
votes
2answers
160 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 ...
1
vote
3answers
418 views

Handling Missing values in stocks returns when estimating the co variance matrix

What is the best way to handle missing values when stocks did not exist for the entire historical period?.
1
vote
0answers
71 views

Max Likelihood via Marquardt Optimisation

I asked a related question here: How to apply Levenberg Marquardt to Max Likelihood Estimation I tried the approach suggested it works for some of the parameters but not the variances. I spoke to ...
9
votes
4answers
3k views

R: Fast and efficient way of running a multivariate regression across a (really) large panel (First pass of Fama MacBeth)

I am attempting to run a rolling multivariate regression (14 explanatory variables) across a panel of 5000 stocks: For each of the 5000 stocks, I run 284 regressions (by rolling over my sample ...
3
votes
5answers
148 views
0
votes
0answers
89 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 ...
4
votes
1answer
165 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 ...
5
votes
2answers
170 views

Economic contagion to individual stocks (ideas for analysis)

I'm doing my undergraduate thesis on firm-level contagion. Specifically I look at a measure of performance over a financial crisis (e.g. raw stock returns), then run cross-sectional regressions with ...
4
votes
0answers
149 views

Calculating volatility of inhomogeneous time series

I am reading an article by Zumbach and Müller whose name is Operators on Inhomogeneous Time Series. This is interesting in general, but my main goal is to learn a good and efficient method to ...
1
vote
1answer
204 views

how to compute daily skewness of S&P daily return timeseries under no other more high - frequency time series?

As we all know , return time series marked features: fat tail or negative skewness and peakedness. For a similar problem of variance computation, we can compute variance by garch model and other ...
0
votes
3answers
280 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 ...
5
votes
0answers
93 views

2-state HMM / ARMA process?

I have issues with this problem: Let $\{X_t, t\in \Bbb N\}$ be a 2-state stationary Markov chain, with transition $M$ (and $M(1,2)\neq 0 \neq M(2,1)$), let $\{W_t, t\in \Bbb N\}$ be a strong Gaussian ...
4
votes
1answer
253 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 ...
6
votes
2answers
263 views

Why do I have a statistically significant slope regressing R(t) on R(t-1)

I am reading Cochrane's lecture note here He mentioned that when you regress annual return on time t on that of time t-1, you will have neither statistically significant nor economically significant ...
1
vote
1answer
128 views

Constant term in linear regresion

Can someone give a mathematical proof as to why including a constant in a linear regression equivalent is to running a regression with demeaned data and zero constant? More specifically, consider the ...
2
votes
1answer
2k 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
1answer
159 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
122 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
813 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
371 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 ...