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

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339 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 ...
3
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1answer
937 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
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1answer
313 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} ...
3
votes
1answer
266 views

ARMA+GARCH prediction with package rugarch (R)

I am analyzing FTSE 100 series, from 2007-01-01 to 2010-12-31 (university exam homework). I have to use the data 'til 2010-11-30 as sample, and the remaining (23) observations as in-sample forecast ...
3
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0answers
80 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 $N(0,1)$. ...
3
votes
1answer
66 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 ...
3
votes
1answer
132 views

Applying Time Delay Neural Network to financial events

I have an IT background and I would like to use data from a forex calendar like this one to predict prices. The problem is that calendar news impacts can last for days or weeks or even can effect ...
3
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0answers
185 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
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0answers
117 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 ...
3
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0answers
102 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 ...
3
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0answers
192 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
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0answers
408 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
votes
3answers
467 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
votes
3answers
903 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
1k 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
votes
3answers
573 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
1answer
95 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
522 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
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2answers
249 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
524 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
2answers
135 views

Normalizing SPY ETF time series data with its sector ETFs?

I am looking to compare the returns of a sector rotation strategy between the various SPDR sector ETFs XLY, XLP, XLE, XLF, XLV, XLI, XLB, XLK, XLU vs. ...
2
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2answers
237 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
268 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
699 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
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2answers
47 views

Automate selection of BIC-minimizing ARIMA(1,0,X) model

I want to estimate an ARIMA(1,0,X) model. The MA(X) in the model is selected to minimize BIC. I have the following code employing the function auto.arima from ...
2
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1answer
60 views

distribution of AR, MA coefficients estimation in ARMA-GARCH models

could anyone give me an information about distributions of AR and MA coefficients via estimation? So, for example, I have ARMA(1,1)-GARCH(1,1) model with the same AR(1) and MA(1) parameters ...
2
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2answers
134 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
57 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
77 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
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2answers
569 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
votes
1answer
82 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
388 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
378 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
682 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
172 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
396 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
2answers
85 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
votes
1answer
106 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
votes
1answer
274 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
votes
1answer
101 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
votes
1answer
98 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
votes
2answers
168 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
221 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
79 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
votes
1answer
451 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
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1answer
56 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
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
104 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 ...