A sequence of events measured at uniform intervals of time.
3
votes
0answers
74 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
votes
0answers
39 views
Comparing Investments: Selling land vs. starting a business [closed]
I have a situation where I need to compare some investing alternatives.
We and my partners own a piece of land with high commercial value, that was bought 7 years ago. Now the real estate market ...
3
votes
1answer
81 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 ...
2
votes
0answers
52 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
3answers
258 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
...
1
vote
1answer
70 views
How does one use the Johansen cointegration test in a linear time series model?
How does one use the Johansen cointegration test in a linear time series model?
Should I only use normalized coeffients for interpretation? Or, once I know that the variables are cointegrated, do I ...
2
votes
0answers
50 views
Is there an appropriate sequence to tests during model diagnosis?
How should one order (sequence) the following tests?
Stationarity test
Johansen cointegration test
Normality/Histogram test
Autocorrelation test
Heteroskedasticity test
Multicollinearity test
...
0
votes
0answers
67 views
How can I cope missing data values with excel? or any other software? [closed]
I have to compute Amihud (2002) illiquidity measure for US stock market and I have some missing values in the time-series.
Many papers suggest to use linear interpolation for fitting missing values; ...
2
votes
2answers
101 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 & ...
3
votes
2answers
187 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
2answers
106 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 ...
1
vote
0answers
127 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 ...
3
votes
0answers
106 views
Fitting a non linear AR + GARCH(1,1)-M model
I want to fit the following model to a time series:
$$
y_{t}=\alpha_{0}+\alpha_{1}y_{t-1}+\alpha_{2}y_{t-1}^{2}+\lambda h_{t}+\varepsilon_{t}
$$
$$
...
0
votes
2answers
245 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
161 views
How to use Newey West covariance corrector?
I have implemented the following model:
daily_vol(t+1) = A*daily_vol(t) + B*weekly_vol(t) + C*monthly_vol(t) + error
where vol means volatility, and A, B, C are ...
3
votes
2answers
55 views
Imputed values in a multi-index
I have an equal-weighted index on a number of different Indices (from US, Europe and Asian markets). This compound index is constructed from a time series that has missing values (for example, those ...
3
votes
1answer
151 views
time in time series database - UTC or local
I strictly store UTC time stamps inside time series files or databases, mainly to allow processing several time series together. Timezone information is kept with each time series file or item, so ...
2
votes
1answer
156 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 ...
1
vote
1answer
324 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, ...
5
votes
3answers
266 views
The Basis of Using Technical Indicators as Inputs
In the process of my research I very often come across academic papers regarding modelling and trading strategies that in one way or another incorporate some technical indicators. For example in some ...
5
votes
0answers
156 views
Alternative ways to understand time-varying comovement between two time-series?
I have been looking into ways to better understand how the dependencies/correlations/etc between two time series can vary over time.
I first thought about using a Kalman/particle filter over a ...
2
votes
2answers
125 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 ...
0
votes
1answer
152 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 ...
4
votes
0answers
146 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, ...
2
votes
3answers
156 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
564 views
How to fit ARMA+GARCH Model In R?
I am currently working on ARMA+GARCH model using R. I am looking out for example which explain step by step explanation for fitting this model in R. I have time series which is stationary and I am ...
5
votes
4answers
306 views
Regressor: Nominal return, continuous return or first difference?
Suppose the application is linear models in financial econometrics. If we want to analyze stocks, the standard approach is to take the continuous/log return: $\ln{ \frac{P_t}{P_{t-1}} }$. Suppose, ...
3
votes
1answer
174 views
How do I estimate the parameters of an MA(q) process?
It is relatively easy to estimate the parameters of an autoregressive $AR(p)$ process. How do I do with a moving average $MA(q)$ process?
1
vote
1answer
167 views
Why does $\hat{\epsilon}'\hat{\epsilon}$ of a factor model measure risk?
$\hat{\epsilon}'\hat{\epsilon}$ from the market model: $R_{it} - \hat{\alpha} - \hat{\beta}R_{mt} = \hat{\epsilon}$, or from a factor model such as the Fama-French 3 factor model, is often used in the ...
2
votes
0answers
102 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 ...
5
votes
1answer
290 views
Major FX pairs - Pentahedron Data Structure
I read an interview today with Stephane Coquillaud.
He talked about this idea of formulating a data set of the G5 currencies as a pentahedron. The obvious benefit is the fact that there is more ...
1
vote
1answer
420 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?
...
5
votes
2answers
125 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 ...
1
vote
0answers
98 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 ...
2
votes
0answers
75 views
Difference between kappa and delta in mixed-effects model
(This question is a crosspost from Cross Validated)
I have a following stochastic model describing evolution of a process (Y) in space and time. Ds and Dt are domain in space (2D with x and y axes) ...
2
votes
1answer
166 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} ...
5
votes
0answers
193 views
Can Hurst exponent be used to characterize nonlinear dependence in time series?
It appears to me that the answer is no, because Hurst exponent measures persistence in terms of autocorrelation, which is a linear measure. So even if a time series of asset returns is driven by ...
0
votes
0answers
36 views
The observed negative interest rates should be modelled as the observed positive ones?
The presently observed negative interest rates for the recently emitted negative interest bonds by France, etc seem to increase in magnitude with the term. This might suggest that their modelling is ...
8
votes
1answer
389 views
Meta-view of different time-series similarity measures?
While I spend most of my StackExchange time on MathematicaSE, I'm in the business and follow the questions and answers on this site with great interest.
Recently questions like the following (and ...
6
votes
2answers
340 views
0
votes
0answers
35 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 ...
8
votes
3answers
209 views
Are there any standard techniques for adding realistic synthetic microstructure noise to a price series?
This may seem like a strange question, but for my particular application we need to actually add synthetic microstructure noise to real time charts. The signal should still be representative of the ...
9
votes
1answer
207 views
Is a linear combination of GARCH processes also a GARCH process?
If two time series follow a GARCH process, and a third is a linear combination of them, is the third also GARCH process?
2
votes
3answers
415 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 ...
8
votes
1answer
276 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
1answer
340 views
How to model time series of illiquid stocks - 400 observations (transactions) per 8 hours?
How to model time series which are illiquid - 400 observations (transactions) per 8 hours ? Are there models suitable for this situation which incorporate not only size of the transactions but also ...
2
votes
1answer
124 views
Good reference on sample autocorrelation?
I'm not a statistician but I'm writing my thesis on mathematical finance and I think it would be neat to have a short section about independence of stock returns. I need to get better understanding ...
3
votes
2answers
321 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 ...
5
votes
2answers
349 views
Choosing the time-frame to test for cointegration
Is there a technique to choose the time-frame for a cointegration test (eg Augmented Dickey-Fueller's)?
3
votes
2answers
248 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 ...
