Strong Evidence Of Long Memory Research Articles

Long Memory Modeling: Evidence From Mediterranean Stock Indexes

We study in this paper the presence of long memory of four Mediterranean stock markets namely Morocco, Turkey, Spain, and France, over the period 2000-2020. The presence of long memory propriety has tested by using the R/S analysis approach. Results show that the four processes have a long memory. furthermore, ARFIMA-FIGARCH, under different distribution assumptions as Normal, Student-t, and Skewed Student- t, was estimated in order to test the feature of long memory in the return and volatility of the stock markets simultaneously. Results show strong evidence of long memory in both returns and volatility for the Moroccan and French stock markets and only in volatility for The Spanish and Turkish ones. The long memory in returns indicates that their behavior is predictable implying the rejection of the efficient market hypothesis. The long memory in volatility shows that risk is an important parameter of the behavior of the future returns in the four stock markets.

Long Memory in Earthquake Time Series: The Case Study of the Geysers Geothermal Field

The present study aims at proving the existence of long memory (or long-range dependence) in the earthquake process through the analysis of time series of induced seismicity. Specifically, we apply alternative statistical techniques borrowed from econometrics to the seismic catalog of The Geysers geothermal field (California), the world’s largest geothermal field. The choice of the study area is essentially guided by the completeness of the seismic catalog at smaller magnitudes (a drawback of conventional catalogs of natural seismicity). Contrary to previous studies, where the long-memory property was examined by using non-parametric approaches (e.g., rescaled range analysis), we assume a fractional integration model for which the degree of memory is defined by a real parameterd, which is related to the best known Hurst exponent. In particular, long-memory behavior is observed ford> 0. We estimate and test the value ofd(i.e., the hypothesis of long memory) by applying parametric, semi-parametric, and non-parametric approaches to time series describing the daily number of earthquakes and the logarithm of the (total) seismic moment released per day. Attention is also paid to examining the sensitivity of the results to the uncertainty in the completeness magnitude of the catalog, and to investigating to what extent temporal fluctuations in seismic activity induced by injection operations affect the value ofd. Temporal variations in the values ofdare analyzed together with those of theb-value of the Gutenberg and Richter law. Our results indicate strong evidence of long memory, withdmostly constrained between 0 and 0.5. We observe that the value ofdtends to decrease with increasing the magnitude completeness threshold, and therefore appears to be influenced by the number of information in the chain of intervening related events. Moreover, we find a moderate but significant negative correlation betweendand theb-value. A negative, albeit weaker correlation is found betweendand the fluid injection, as well as betweendand the annual number of earthquakes.

Relative Efficiency of G8 Sovereign Credit Default Swaps and Bond Scrips: An Adaptive Market Hypothesis Perspective

This article is aimed at examining the degree of efficiency exhibited by the sovereign credit default swaps (SCDS) and the sovereign bonds (SBs) pertaining to the G8 countries, namely, US, UK, Japan, Germany, Italy, France and Russia, from an Adaptive Market Hypothesis (AMH) perspective. At the outset, the authors employ rolling AR(1)–GARCH(1,1) filter so as to remove short-term dependency in the different time series considered for this study. The AR(1)–GARCH(1,1)-filtered rolling standardized residuals were then subjected to Mandelbrot’s classical R/S test so as to obtain rolling Hurst exponents. Subsequently, the evolving efficiencies of G8 SCDS and SB scrips as reflected by the scrip-wise rolling Hurst exponents are made available. In doing so, scrip-wise transient inefficiencies, as characterized by periods that exhibit strong evidence of long memory, were identified. The authors then offer a ranking of G8 SCDS and SB scrips, in the decreasing order of relative efficiency, based on proportion of scrip-wise rolling windows that exhibited strong evidence of long memory. The findings pertaining to this study are as follows. First, SBs pertaining to UK, Japan, US, France and Russia were found to be the most efficient, while SBs pertaining to Russia were found to be the least efficient. Second, when it comes to SCDS, Russian SCDS scrips were found to be relatively more efficient than the Russian SBs. Having said so, G8 SCDS scrips pertaining to the other countries were found to be inefficient vis-à-vis their respective SBs. Of all the G8 countries, US was the only country wherein no strong evidence of long memory was witnessed in SCDS and/or SB scrips. Finally, there is discernable difference in the degree of efficiency exhibited by G8 SCDS scrips vis-à-vis their underlying reference obligations (ROs).

True or Spurious Long Memory?: Evidence from Russian Precious Metals Market

We examine the long memory property and structural break in the spot and futures gold volatility in Russia from 2008 through 2013. We find strong evidence of long memory in the volatility of both spot and futures gold series. The break dates are associated with the recent global financial crisis. Moreover, we investigate the volatility spillover effect between the Russian spot and futures gold markets using the corrected Dynamic Conditional Correlation model (cDCC). The findings show relatively high level of conditional correlation between spot and futures gold returns. This outcome decreases the portfolio diversification benefits for gold investors.

The volatility dynamics of spot and futures gold prices: Evidence from Russia

We examine the long memory property and structural break in the spot and futures gold volatility in Russia from 2008 through 2013. We find strong evidence of long memory in the volatility of both spot and futures gold series. The break dates are associated with the recent global financial crisis. Moreover, we investigate the volatility spillover effect between the Russian spot and futures gold markets using the corrected Dynamic Conditional Correlation model (cDCC). The findings show relatively high level of conditional correlation between spot and futures gold returns. This outcome decreases the portfolio diversification benefits for gold investors.

The Long Memory of Order Flow in the Foreign Exchange Spot Market

We study the long memory of order flow for each of three liquid currency pairs on a large electronic trading platform in the foreign exchange (FX) spot market. Due to the extremely high levels of market activity on the platform, and in contrast to existing empirical studies of other markets, our data enables us to perform statistically stable estimation without needing to aggregate data from different trading days. We find strong evidence of long memory, with a Hurst exponent [Formula: see text], for each of the three currency pairs and on each trading day in our sample. We repeat our calculations using data that spans different trading days, and we find no significant differences in our results. We test and reject the hypothesis that the apparent long memory of order flow is an artifact caused by structural breaks, in favor of the alternative hypothesis of true long memory. We therefore conclude that the long memory of order flow in the FX spot market is a robust empirical property that persists across daily boundaries.

Testing of Long Memory in Indian Stock Market using ARFIMA model

This paper examines the presence of long memory property and market cycles in the Indian stock market by using daily closing price of Nifty Index from May 2009 to April 2015. The study has used Unit Root Test, Autocorrelation Test, Rescaled Range (R/S) statistics and ARFIMA Models to determine the long memory property in Indian stock market. The result of the study shows that Indian stock market exhibits a high degree of positive long-term persistence. The results of ARFIMA model also indicates that stock price index exhibits strong evidence of long memory and contradicts the evidence against efficient market hypothesis. This implies that future stock price can be predicted. The study concludes that there is an arbitrage opportunities available for international investors and they can make abnormal profits by investing in Indian stock market.

The Long Memory of Order Flow in the Foreign Exchange Spot Market

We study the long memory of order flow for each of three liquid currency pairs on a large electronic trading platform in the foreign exchange (FX) spot market. Due to the extremely high levels of market activity on the platform, and in contrast to existing empirical studies of other markets, our data enables us to perform statistically stable estimation without needing to aggregate data from different trading days. We find strong evidence of long memory, with a Hurst exponent of approximately 0.7, for each of the three currency pairs and on each trading day in our sample. We repeat our calculations using data that spans different trading days, and we find no significant differences in our results. We test and reject the hypothesis that the apparent long memory of order flow is an artifact caused by structural breaks, in favour of the alternative hypothesis of true long memory. We therefore conclude that the long memory of order flow in the FX spot market is a robust empirical property that persists across daily boundaries.

True or spurious long memory in volatility: Further evidence on the energy futures markets

The main goal of this paper is to investigate whether the long memory behavior observed in many volatility energy futures markets series is a spurious behavior or not. For this purpose, we employ a wide variety of advanced volatility models that allow for long memory and/or structural changes: the GARCH(1,1), the FIGARCH(1,d,1), the Adaptative-GARCH(1,1,k), and the Adaptative-FIGARCH(1,d,1,k) models. To compare forecasting ability of these models, we use out-of-sample forecasting performance. Using the crude oil, heating oil, gasoline and propane volatility futures energy time series with 1-month and 3-month maturities, we found that five out of the eight time series are characterized by both long memory and structural breaks. For these series, dates of breaks coincide with some major economics and financial events. For the three other time series, we found strong evidence of long memory in volatility.

How do OPEC news and structural breaks impact returns and volatility in crude oil markets? Further evidence from a long memory process

Since its formation, OPEC through its conference decisions has been a major player in the world oil markets. The purpose of this paper is to examine the impacts of OPEC's different news announcements on the conditional expectations and volatility of crude oil markets in the presence of long memory and structural changes. To do so, we first discern OPEC's oil production behavior in response to its “cut”, “maintain”, and “increase” decisions. Then by applying the ARMA–GARCH class models to the two global benchmarks WTI and Brent over the period May 1987 through December 2012, we find strong evidence of long memory. The empirical evidence also shows that OPEC's announcements especially the “cut” and the “maintain” decisions have a significant effect on both returns and volatility of the crude oil markets, particularly that of the WTI. Moreover, we explore the possibility of structural breaks in the crude oil prices and detect five (six) breakpoints for the WTI (Brent) oil markets. The presence of structural breaks reduces the persistence of volatility. Accounting for OPEC's scheduled news announcements in the presence of structural changes reduces the degree of volatility persistence and enhances the understanding of this volatility in the oil markets. These results have several implications for policy makers, oil traders and other participants in the crude oil markets.

PERSISTENCE IN CONVERGENCE

In this paper, we examine the convergence hypothesis using a long memory framework that allows for structural breaks and does not rely on a benchmark country. We find that even though the long memory framework of analysis is much richer than the simple I(1)/I(0) alternative, a simple absolute divergence and rapid convergence dichotomy produced by the latter is sufficient to capture the behavior of the gaps in per capita GDP levels and growth rates results respectively. This is in contrast to the findings of Dufrénot, Mignon, and Naccache [The Slow Convergence of Per Capita Income between the Developing Countries: Growth Resistance and Sometimes Growth Tragedy. Discussion paper, University of Nottingham (2009)], who found strong evidence of long memory for output gaps. The speed of convergence as captured by the estimated long memory parameter d, is explained by differences in physical and human capital as well as fiscal discipline characteristics of economic policies pursued by different countries.

Long Memory Property In Return and Volatility: Evidence from the Indian Stock Markets

The paper examines the existence of long memory in the Indian stock market using ARFIMA, FIGARCH models. The data set consists of daily return of BSE and NSE stock indices and long memory tests are carried out both for the returns and volatilities of these series. The results of ARFIMA model suggests the absence of long memory in return series of the Indian stock market. The results of FIGARCH model indicate strong evidence of long memory in conditional variance of the stock indices. The long memory property of the BSE market is revealed to be stronger than NSE.

Modelling heavy tails and double long memory in North African stock market returns

Modelling heavy tails and double long memory in stock returns is very important for financial asset pricing, asset allocation and risk management. In this paper, we demonstrate that an α-stable distribution is better fitted to the North African stock return data in TUNINDEX (Tunisia), MASI (Morocco) and EGX30 (Egypt) than the normal distribution. The empirical results show that the asymmetric leptokurtic features presented in these markets can be captured by an α-stable distribution. Moreover, estimation of the tail index allows us to determine the long-memory behaviour of stock returns. Additionally, this study examines the long-memory property in mean returns and volatility of these markets. The results indicate that long-memory dynamics in the returns and volatility might be modelled by the joint ARFIMA–FIGARCH model. The results of the joint ARFIMA–FIGARCH model show strong evidence of long memory in both returns and volatility. The long memory in returns implies that stock prices follow a predictable behaviour, which is inconsistent with the efficient market hypothesis. The evidence of long memory in volatility, however, shows that uncertainty or risk is an important determinant of the behaviour of daily stock data in North African stock markets. The implication of the present work is that the assumption of non-normality provides better specifications regarding the long-memory property.

Persistence in some energy futures markets

AbstractIn this study, we examine the possibility of long‐range dependence in some energy futures markets for different maturities. In order to test for persistence, we use a variety of techniques based on non‐parametric, semi‐parametric and parametric methods. The results indicate that there is little or no evidence of long memory in gasoline, propane, oil and heating oil at different maturities. However, when we focus on the volatility process, proxied by the absolute returns, we find strong evidence of long memory in all the variables at different contracts. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:490–507, 2010

Long Memory in Oil and Refined Products Markets

We test for the presence of long memory in daily oil and refined products prices’ absolute return, squared return and conditional volatility, using several parametric and semiparametric methods. This study finds strong evidence of long memory (LM) in the daily absolute and squared spot and futures returns for crude oil, gasoline and heating oil but at different degrees. The FIGARCH model also demonstrates strong evidence of LM for volatility for most of oil and products prices’ returns, with also different resilience levels. Structural breaks have only the partial effects of slightly reducing persistence for just absolute and squared returns. Examining the forecasting behavior of two competing models, the less parsimonious ARFIMA which satisfies the LM property, and the parsimonious ARMA with short-term processes, the ARFIMA model provides significantly better out-of-sample forecasts at all forecasting horizons for all three petroleum types.

Dual long memory property in returns and volatility: Evidence from the CEE countries' stock markets

This paper investigates the presence of long memory in the eight Central and Eastern European (CEE) countries' stock market, using the ARFIMA, GPH, FIGARCH and HYGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of these series. The results of the ARFIMA and GPH models indicate the existence of long memory in five of eight return series. The results also suggest that long memory dynamics in the returns and volatility might be modeled by using the ARFIMA–FIGARCH and ARFIMA–HYGARCH models. The results of these models indicate strong evidence of long memory both in conditional mean and conditional variance. Moreover, the ARFIMA–FIGARCH model provides the better out-of-sample forecast for the sampled stock markets.

Long memory in the Portuguese stock market

PurposeThis paper's aim is to test for the presence of fractional integration, or long memory, in the daily returns of the Portuguese stock market using autoregressive fractionally integrated moving average (ARFIMA), generalised autoregressive conditional heteroskedasticity (GARCH) and ARFIMA‐FIGARCH models.Design/methodology/approachThe data cover two periods: 4 January 1993‐13 January 2006 (full sample), and 1 February 2002‐13 January 2006 (that is, data are considered after the merger of the Portuguese Stock Exchange with Euronext).FindingsThe results from the full sample show strong evidence of long memory in stock returns. When data after the merger are considered, weaker evidence of long memory is found. It is concluded that the Portuguese stock market is more efficient after the merger with Euronext.Originality/valueThe findings of this paper are helpful to financial managers and investors dealing with Portuguese stock indices.

Statistical properties of daily ensemble variables in the Chinese stock markets

We study dynamical behavior of the Chinese stock markets by investigating the statistical properties of daily ensemble return and variety defined, respectively, as the mean and the standard deviation of the ensemble daily price return of a portfolio of stocks traded in China's stock markets on a given day. The distribution of the daily ensemble return has an exponential form in the center and power-law tails, while the variety distribution is lognormal in the bulk followed by a power-law tail for large variety. Based on detrended fluctuation analysis, R/S analysis and modified R/S analysis, we find evidence of long memory in the ensemble return and strong evidence of long memory in the evolution of variety.

Analysing inflation by the fractionally integrated ARFIMA-GARCH model

This paper considers the application of long-memory processes to describing inflation for 10 countries. We implement a new procedure to obtain approximate maximum likelihood estimates of an ARFIMA-GARCH process; which is fractionally integrated I(d) with a superimposed stationary ARMA component in its conditional mean. Additionally, this long-memory process is allowed to have GARCH type conditional heteroscedasticity. On analysing monthly post-World War II CPI inflation for 10 different countries, we find strong evidence of long memory with mean reverting behaviour for all countries except Japan, which appears stationary. For three high inflation economies there is evidence that the mean and volatility of inflation interact in a way that is consistent with the Friedman hypothesis. Copyright 1996 by John Wiley & Sons, Ltd.