• The Korean Journal of Financial Management
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• v.24 no.3
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• pp.63-89
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• 2007

This study aims at empirically verifying whether long memory properties exist in returns and volatility of the financial time series and then, empirically observing influential factors of long-memory properties. The presence of long memory properties in the financial time series is examined with the Hurst exponent. The Hurst exponent is measured by DFA(detrended fluctuation analysis). The empirical results are summarized as follows. First, the presence of significant long memory properties is not identified in return time series. But, in volatility time series, as the Hurst exponent has the high value on average, a strong presence of long memory properties is observed. Then, according to the results empirically confirming influential factors of long memory properties, as the Hurst exponent measured with volatility of residual returns filtered by GARCH(1, 1) model reflecting properties of volatility clustering has the level of $H{\approx}0.5$ on average, long memory properties presented in the data before filtering are no longer observed. That is, we positively find out that the observed long memory properties are considerably due to volatility clustering effect.

• East Asian Economic Review
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• v.18 no.4
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• pp.367-394
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• 2014

In this study, we examined the fractal structure of the Nikkei225, HangSeng, Shanghai Stock Exchange and Straits Times Index of Singapore. Empirical analysis was performed via non-parametric, semi-parametric long memory tests and also fractal dimension calculations. In order to avoid spurious long memory features, besides the Detrended Fluctuations Analysis (DFA), we also used Smith's (2005) modified GPH method. As for fractal dimension calculations, they were conducted via Box-Counting and Variation (p=1) tests. According to the results, while there is no long memory property in log returns of any index, we found evidence for long memory properties in the volatility of the HangSeng, the Shanghai Stock Exchange and the Straits Times Index. However, we could not find any sign of long memory in the volatility of Nikkei225 index using either the DFA or modified GPH test. Fractal dimension analysis also demonstrated that all raw index prices have fractal structure properties except for the Nikkei225 index. These findings showed that the Nikkei225 index has the most efficient market properties among these markets.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.23-26
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• 2000

It is noted that many econometric time series have long-memory properties. A long-memory process, or strongly dependent process, is characterized by hyperbolic decaying autocorrelations and unbounded spectral density at the origin. Since the long-memory property can be observed by data obtained from rather a long period, there is some possibility of parameter change in the process. In this paper, we consider the estimation of change-point when there is a change in the variance of a long-memory process. The estimator is based on some reasonable statistic and the consistency is shown using Taqqu's strong reduction theorem

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.255-269
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• 2020

Purpose - This paper analyzes the market efficiency focusing on the long memory properties of the domestic futures market. By decomposing futures prices into yield and volatility and looking at the long memory properties of the time series, this study aims to understand the futures market pricing and change behavior and risks, specifically and in detail. Design/methodology/approach - This study analyzes KOSPI 200 futures, KOSDAQ 150 futures, 3 and 10-year government bond futures, US dollar futures, yen futures, and euro futures, which are among the most actively traded on the Korea Exchange. To analyze the long memory and market efficiency, we used the Variance Ratio, Rescaled-Range(R/S), Geweke and Porter-Hudak(GPH) tests as semi- parametric methods, and ARFIMA-FIGARCH model as the parametric method. Findings - It was found that all seven futures supported the efficiency market hypothesis because the property of long memory turned out not to exist in their yield curves. On the other hand, in futures volatility, all 7 futures showed long memory properties in the analysis, which means that if new information is generated in the domestic futures market and the market volatility once expanded due to the impact, it does not decrease or shrink for a long period of time, but continues to affect the volatility. Research implications or Originality - The results of this paper suggest that it can be useful information for predicting changes and risks of volatility in the domestic futures market. In particular, it was found that the long memory properties would be further strengthened in the currency futures and bond rate futures markets after the global financial crisis if the regime changes of the domestic financial market are taken into account in the analysis.

• Journal of Distribution Science
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• v.14 no.1
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• pp.93-102
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• 2016

Purpose - The purpose of paper is studying the static and dynamic side for long-term memory storage properties, and increase the explanatory power regarding the long-term memory process by looking at the long-term storage attributes, Korea Composite Stock Price Index. The reason for the use of GPH statistic is to derive the modified statistic Korea's stock market, and to research a process of long-term memory. Research design, data, and methodology - Level shifts were subjected to be an empirical analysis by applying the GPH method. It has been modified by taking into account the daily log return of the Korea Composite Stock Price Index a. The Data, used for the stock market to analyze whether deciding the action by the long-term memory process, yield daily stock price index of the Korea Composite Stock Price Index and the rate of return a log. The studies were proceeded with long-term memory and long-term semiparametric method in deriving the long-term memory estimators. Chapter 2 examines the leading research, and Chapter 3 describes the long-term memory processes and estimation methods. GPH statistics induced modifications of statistics and discussed Whittle statistic. Chapter 4 used Korea Composite Stock Price Index to estimate the long-term memory process parameters. Chapter 6 presents the conclusions and implications. Results - If the price of the time series is generated by the abnormal process, it may be located in long-term memory by a time series. However, test results by price fixed GPH method is not followed by long-term memory process or fractional differential process. In the case of the time-series level shift, the present test method for a long-term memory processes has a considerable amount of bias, and there exists a structural change in the stock distribution market. This structural change has implications in level shift. Stratum level shift assays are not considered as shifted strata. They exist distinctly in the stock secondary market as bias, and are presented in the test statistic of non-long-term memory process. It also generates an error as a long-term memory that could lead to false results. Conclusions - Changes in long-term memory characteristics associated with level shift present the following two suggestions. One, if any impact outside is flowed for a long period of time, we can know that the long-term memory processes have characteristic of the average return gradually. When the investor makes an investment, the same reasoning applies to him in the light of the characteristics of the long-term memory. It is suggested that when investors make decisions on investment, it is necessary to consider the characters of the long-term storage in reference with causing investors to increase the uncertainty and potential. The other one is the thing which must be considered variously according to time-series. The research for price-earnings ratio and investment risk should be composed of the long-term memory characters, and it would have more predictability.

• East Asian Economic Review
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• v.20 no.3
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• pp.365-390
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• 2016

This paper quantitatively compares the intrinsic features of the daily USD-GBP exchange rates in two different periods, the 1920s and the 2010s, under the same freely floating exchange rate system. Even though the foreign exchange markets in the 1920s seem to be much less organized and developed than in the 2010s, this paper finds that both the long memory volatility property and the structural break appear to be the common intrigue features of the exchange rates in the two periods by using the FIGARCH model. In particular, the long memory volatility properties in the two periods are found to be upward biased and overstated because of the structural breaks in the exchange markets. Thus this paper applies the Adaptive-FIGARCH model to consider the long memory volatility property and the structural breaks jointly. The main finding is that the structural breaks in the exchange markets affect the long memory volatility property significantly in the two periods but the degree of the long memory volatility property in the 1920s is reduced more remarkably than in the 2010s after the structural breaks are accounted for; thus implying that the structural breaks in the foreign exchange markets in the 1920s seem to be more significant.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.639-645
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• 2009

Fractional Brwonian motion(fBm) has properties of behaving tails and exhibiting long memory while remaining Gaussian. In particular, it is well known that interest rates show some long memories and non-Markovian. We present no aribitrage condition for HJM model under the multi-factor fBm reflecting the long range dependence in the interest rate model.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.156-157
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• 2007

For tens of years many advantages of Phase-Change Random Access Memory(PRAM) were introduced. Although the performance improved gradually, there are some portions which must be improved. So, we studied new constitution of $Ge_1Se_1Te_2$ chalcogenide material to improve phase transition characteristic. Actually, the performance properties have been improved surprisingly. However, crystallization time was as long as ever for amorphization time. We conducted this experiment in order to solve that problem by doping-Sb.

• Earthquakes and Structures
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• v.23 no.2
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• pp.207-219
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• 2022

Seismic response control has always been a grave concern with the damage and collapse of many buildings during the past earthquakes. While there are several existing techniques like base isolation, viscous damper, moment-resisting beam-column connections, tuned mass damper, etc., many of these are succumbing to either of large displacement, near-fault, and long-period earthquakes. Keeping this viewpoint, extensive research on the application of smart materials for seismic response control of buildings was attempted during the last decade. Shape Memory Alloy (SMA) with its unique properties of superelasticity and shape memory effect is one of the smart materials used for seismic control of buildings. In this paper, an exhaustive review has been compiled on the seismic control applications of SMA in buildings. Unique properties of SMA are discussed in detail and different phases of SMA along with crystal characteristics are illustrated. Consequently, various seismic control applications of SMA are discussed in terms of performance and compared with prevalent base isolators, bracings, beam-column connections, and tuned mass damper systems.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1329-1330
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• 2007

Phase-change random access memory(PRAM) has many advantages compare with the existing memory. For example, fast programming speed, low programming voltage, high sensing margin, low power consume and long cyclability of read/write. Though it has many advantages, there are some points which must be improved. So, we invented and studied new constitution of $Ge_{1}Se_{1}Te_{2}$ chalcogenide material. Actually, the performance properties have been improved surprisingly. However, crystallization time was as long as ever for amorphization time. In this paper, we studied in order to make set operation time and reset operation voltage reduced. In the present work, by alloying Sb in $Ge_{1}Se_{1}Te_{2}$. we could confirm that improved its set operation time and reset operation voltage. As a result, the method of Sb-alloyed $Ge_{1}Se_{1}Te_{2}$ can be solution to decrease the set operation time and reset operation voltage.