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

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3
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371 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 ...
2
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3answers
457 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
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2answers
2k 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
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3answers
774 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?.
2
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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
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2answers
769 views

Speed of mean reversion of an interest rate model

I would like to have a bit more of intuition about the concept of "speed of mean reversion" for an interest rate model, e.g. Vasicek or CIR. In particular, is a negative speed of mean reversion ...
2
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3answers
560 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
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1answer
91 views

Garch models and assumption of stationarity ?

I found big inconsistency in the GARCH models and their underlying assumption of stationarity. GARCH models require that data must be stationary, where stationary means both mean and variance are ...
2
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3answers
442 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 - ...
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2answers
239 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
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3answers
510 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
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1answer
221 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
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2answers
223 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
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1answer
258 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
677 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
2answers
89 views

Augmented Dickey-Fuller Test/ Unit Root test on multiple time series dataframe in R

I have a dataset/dataframe in which I have calculated the daily log returns of five thousand companies and these companies are as column as well. I want carry out ADF test on this dataframe. I have ...
2
votes
1answer
45 views

Estimating Carma(2,1) parameters (using yuima package)

I am very new to R, and particularly to the yuima package, so I was hoping someone would be able to help me. I have some data (daily prices) that I wish to fit to ...
2
votes
1answer
75 views

Define polynomials of an ARMA process

I just started out with financial time series and I'm a bit stuck with ARMA models. I have the following ARMA process: $-4X_t + X_{t-2} = Z_t + 0.2 Z_{t-1}$ Now I am being asked for the polynomials ...
2
votes
2answers
445 views

Bloomberg tick data timezone offset

I am using python to access the Bloomberg Desktop API and am running into issues with the timezone conversion for their tick data. The data they deliver is supposed to be UTC but there is something ...
2
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1answer
80 views

What do I need to do with my data before fitting the ARIMA model?

I'm fitting a stock price time series data to ARIMA model and I have a question about the assumption. Is it that ARIMA only applies to stationary data? The ACF and PACF of the data (and the logged ...
2
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1answer
356 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
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2answers
341 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
610 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
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1answer
1k views

Counterintuitive time varying Beta with Kalman filter

If you're used to play with R, you'll enjoy the following reproducible code: ...
2
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2answers
170 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
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1answer
389 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
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2answers
77 views

Is there an implementation of VAR-EGARCH model in R or Stata?

I am writing my undergrad honor thesis and want to run a multivariable VAR-EGARCH model. Is there any package in R or formulas in Stata 14 that allows me to implement directly? If not, could you ...
2
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1answer
86 views

what are the criteria to select pairs?

I'm new to this forum, this is the first question I posted. I have many candidate pairs and I've used ADF test to make a first selection. There are more than 800 selected. The pairs are absolutely too ...
2
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1answer
214 views

2-step estimation of DCC GARCH model in Python

Embedded in this thread are multiple questions. I'm currently im the process of implementing a DCC GARCH forecast model on quantopian (a python-powered trading platform). The two step consists of ...
2
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1answer
89 views

FORECASTING Model AR(1) in an Autoregressive Form The Pi´s Parameters

Ive been implementing a little exercise to obtain the first 2 forecasting points of an AR(1) process. And i want to have the forecasting ponts using the three forms: Im folowing this pdf ...
2
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1answer
94 views

Estimating correlation using EWMA

I am using an EWMA model to evaluate the correlation between yearly time series. I know Riskmetrics uses $\lambda=0.94$ for daily data and $\lambda=0.97$ for monthly data. Is there a value ...
2
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2answers
146 views

Extracting Signal from Noisy Data

Consider a scenario in which Y_t represents the % change in price and we want to use X_t to predict Y_t. We assume that X_t is information we get before Y_t is revealed. Suppose that in reality Y_t ...
2
votes
1answer
184 views

High frequency price forecast model ARMA GARCH or another?

Can you reccomend model for high frequency data (1 second and less) (returns and volatility forecasting)? Most papers use ARMA, GARCH etc in 1 minute and lower time frame. PROBLEM ARMA does not know ...
2
votes
1answer
68 views

remove seasonality in future contracts

very new to commodities. I have raw agriculture future data, and I need to remove the seasonality (de-seasonalize) from the data, what is the general approach ? Thanks for the help!
2
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1answer
381 views

using garch to forecast volatility but getting low persistence model

I am using a GARCH(1, 1) model to try model volatility for a certain stock. I have a GARCH function in matlab that returns the three parameters, omega, alpha & beta. I then use this parameters ...
2
votes
1answer
54 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
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1answer
2k 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
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3answers
101 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
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1answer
266 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
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2answers
234 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
407 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
863 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
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3answers
714 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
159 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 ...
2
votes
1answer
134 views

How to reconstruct a discontinued economic time series such as the Fed's CP rate?

The old 3-Month Commercial Paper Rate (CP3M) on FRED was discontinued in 1997. I would like to reconstruct this series in a reasonable fashion, so I can use it to analyze more recent events. I was ...
2
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0answers
41 views

When to use SV or a GARCH model

So i have been searching for this answer for a question if there is a rule or something that would say when to use GARCH type model or use an stochastic volatility model to predict the volatility of ...
2
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0answers
69 views

Fourth moment of arch(2)

I am studying the ARCH(2) process given by $$X_t = \sqrt{h_t} \varepsilon_t$$ where $$h_t = \alpha_0 + \alpha_1 X_{t-1} ^2 + \alpha_2 X_{t-2} ^2$$ and $\varepsilon_t$ follows $N(0,1)$. Assuming the ...
2
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0answers
71 views

Imposing Restrictions on Cointegrating Vectors, R example

The code given below estimates a VEC model with 4 cointegrating vectors. It is a reproducible code, so just copy and paste into your R console (or script editor). ...
2
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0answers
31 views

Specifying integration level of time series [closed]

Following model was estimated on 200 observations. How to specify the level of integration of $X_t?$ In brackets there are standard errors and p-value of Breusch-Godfrey test is also shown. ...
2
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0answers
46 views

Return.portfolio error from PerformanceAnalytics package

When using the PerformanceAnalytics package of R, I am getting an error from the Return.portfolio function whenever I ask it to rebalance_on any frequency. If the rebalance parameter is removed, the ...