scholarly journals Long Memory Process in Asset Returns with Multivariate GARCH Innovations

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Imène Mootamri
Keyword(s):  
Stock Returns ◽  
Long Memory ◽  
Asset Returns ◽  
Multivariate Garch ◽  
Time Varying ◽  
Memory Process ◽  
Conditional Moment ◽  
Conditional Mean ◽  
Long Memory Process

The main purpose of this paper is to consider the multivariate GARCH (MGARCH) framework to model the volatility of a multivariate process exhibiting long-term dependence in stock returns. More precisely, the long-term dependence is examined in the first conditional moment of US stock returns through multivariate ARFIMA process, and the time-varying feature of volatility is explained by MGARCH models. An empirical application to the returns series is carried out to illustrate the usefulness of our approach. The main results confirm the presence of long memory property in the conditional mean of all stock returns.

scholarly journals On tests for long-term dependence: India’s international tourism market

2010 ◽  
Vol 4 (5-6) ◽  
pp. 77-81
Author(s):  
Prasert Chaitip ◽  
Péter Balogh ◽  
Sándor Kovács ◽  
Chukiat Chaiboonsri
Keyword(s):  
Sri Lanka ◽  
Long Memory ◽  
Statistical Tests ◽  
International Tourism ◽  
Memory Process ◽  
Long Memory Process

There have been growing interest in studying behavior of long memory process in tourism market. In this research examine the behavior of India’s international tourism market based on long-memory analysis. The international tourism market of India combined with nine countries: USA, UK, Canada, Germany, France, Japan, Malaysia, Australia and Sri Lanka. Moreover, three statistical tests for longmemory process such as R/S test, Modified R/S test and GPH-test are employed to test in these market. The empirical findings in general provide more support for no long memory process or no long-term dependence in international tourism market of India.

scholarly journals On tests for long-term dependence: India ’s international tourism market

2011 ◽  
Vol 5 (1-2) ◽  
pp. 109-113
Author(s):  
Prasert Chaitip ◽  
Péter Balogh ◽  
Sándor Kovács ◽  
Chukiat Chaiboonsri
Keyword(s):  
Sri Lanka ◽  
Long Memory ◽  
Statistical Tests ◽  
International Tourism ◽  
Memory Process ◽  
Long Memory Process

There have been growing interest in studying behavior of long memory process in tourism market. In this research examine the behavior of India’s international tourism market based on long-memory analysis. The international tourism market of India combined with nine countries: USA, UK, Canada, Germany, France, Japan, Malaysia, Australia and Sri Lanka. Moreover, three statistical tests for longmemory process such as R/S test, Modified R/S test and GPH-test are employed to test in these market. The empirical findings in general provide more support for no long memory process or no long-term dependence in international tourism market of India.

Internet gambling stock returns: empirical evidence from the UK

2017 ◽  
Vol 13 (1) ◽  
pp. 36-49
Author(s):  
Daniel Perez Liston
Keyword(s):  
Stock Returns ◽  
Multivariate Garch ◽  
Online Gambling ◽  
Future Research ◽  
Time Varying ◽  
Conditional Correlation ◽  
Socially Responsible ◽  
Content Type ◽  
Starting Point ◽  
The Uk

Purpose The purpose of this paper is to quantify beta for an online gambling portfolio in the UK and investigates whether it is time-varying. It also examines the dynamic correlations of the online gambling portfolio with both the market and socially responsible portfolios. In addition, this paper documents the effect of important UK gambling legislation on the betas and correlations of the online gambling portfolio. Design/methodology/approach This study uses static and time-varying models (e.g. rolling regressions, multivariate GARCH models) to estimate betas and correlations for a portfolio of UK online gambling stocks. Findings This study finds that beta for the online gambling portfolio is less than 1, indicative of defensiveness toward the market, a result that is consistent with prior literature for sin stocks. In addition, the conditional correlation between the market and online gambling portfolio is small when compared to the correlation of the market and socially responsible portfolios. Findings suggest that the adoption of the Gambling Act 2005 increases the conditional correlation between the market and online gambling portfolio and it also increases the conditional betas for the online gambling portfolio. Research limitations/implications This paper serves as a starting point for future research on online gambling stocks. Going forward, studies can focus on the financial performance or accounting performance of online gambling stocks. Originality/value This empirical investigation provides insight into the risk characteristics of publicly listed online gambling companies in the UK.

A Random walk down the Dhaka Stock Exchange lane

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Md. Kamrul Bari ◽  
Dr. Melita Mehjabeen ◽  
Dr. A. K. Enamul Haque
Keyword(s):  
Random Walk ◽  
Stock Market ◽  
Market Efficiency ◽  
Long Memory ◽  
Stock Exchange ◽  
Reliable Estimate ◽  
Memory Process ◽  
Long Memory Process ◽  
Study Results ◽  
Adf Test

Market efficiency has always been a matter of keen interest to the researchers of finance. Since the advancement of this concept, researchers are consistently investigating the market efficiency of different financial markets. Bangladesh, being one of the emerging economies, has also attracted the attention of many researchers. The researchers have investigated the realities regarding the market efficiency of both the stock exchanges of the country. Most of their investigations reveal that the Dhaka Stock Exchange (DSE) and the Chittagong Stock Exchange (CSE) are inefficient. This research, however, did not stop at revisiting market efficiency alone. Whether the return series follows a long-memory process, has also been tested. Besides, non-parametric tests have also been conducted to confirm the results of the parametric tests and vice versa. It generated a more reliable estimate of market efficiency for the period under study. Results of the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model confirm that the return series does not follow a long memory process, and any shock in the system will eventually vanish. The findings of other tests (the run test, the Augmented Dickey-Fuller (ADF) test, the Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test, and the Kolmogorov-Smirnov (K-S) test) suggest that the return series of the DSE are time-series stationary, non-normal, and do not follow a random walk. Given these results, we must echo the prior researchers to conclude that the stock market of Bangladesh is not efficient for the period of 2015 to 2020. These findings add new knowledge to the existing knowledge pool about market efficiency and long memory of the stock market of Bangladesh.

On the properties of the periodogram of a stationary long-memory process over different epochs with applications

2010 ◽  
Vol 31 (1) ◽  
pp. 20-36 ◽  
Author(s):  
Valdério A. Reisen ◽  
Eric Moulines ◽  
Philippe Soulier ◽  
Glaura C. Franco
Keyword(s):  
Long Memory ◽  
Memory Process ◽  
Long Memory Process

Real-Time Monitoring Test for Realized Volatility

2013 ◽  
Vol 5 (1) ◽  
pp. 1-24
Author(s):  
Cindy Shin-Huei Wang ◽  
Cheng Hsiao
Keyword(s):  
Real Time ◽  
Long Memory ◽  
Structural Breaks ◽  
Brownian Bridge ◽  
Memory Process ◽  
Time Pattern ◽  
Finite Samples ◽  
Long Memory Process ◽  
Data Generating Process ◽  
Monitoring Test

AbstractThis paper proposes a monitoring cumulative sum of squares (CUSQ)-type test for structural breaks in real time via an autoregressive (AR) approximation framework where data generating process (DGP) is a long memory process. The limiting distribution of the monitoring test follows a Brownian bridge and is free of long memory parameters under the null hypothesis of no break. The test is easy to implement and avoids the issue of spurious breaks found for some retrospective tests for long memory process. Neither does it need to use the bootstrap procedure to find the critical values. Monte Carlo simulations appear to confirm that there exists negligible size distortion and satisfactory power performances in finite samples. The procedure is then applied to monitor the real-time pattern of realized volatilities of dollar–Deutschmark and dollar–Japanese Yen.

scholarly journals Estimating dynamic copula dependence using intraday data

2015 ◽  
Vol 19 (4) ◽  
Author(s):  
Lidan Grossmass ◽  
Ser-Huang Poon
Keyword(s):  
Stock Returns ◽  
Long Memory ◽  
High Frequency ◽  
Time Varying ◽  
Credit Crisis ◽  
Dynamic Copula ◽  
Tick Data ◽  
Out Of Sample ◽  
Intraday Data ◽  
Better Than

AbstractWe estimate the dynamic daily dependence between assets by applying the Semiparametric Copula-Based Multivariate Dynamic (SCOMDY) model on intraday data. Using tick data of three stock returns of the period before and during the credit crisis, we find that our dependence estimator better captures the steep increase in dependence during the onset of the crisis as compared to other commonly used time-varying copula methods. Like other high-frequency estimators, we find that the dependence estimator exhibits long memory and forecast it using a HAR model. We show that for out-of-sample forecasts, our dependence estimator performs better than the constant estimator and other commonly used time-varying copula dependence estimators.

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