• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.863-871
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• 2010

Until now, many studies related circular data are carried out, but the focuses are mainly on mildly peaked symmetric or asymmetric cases. In this paper we studied a modeling process for sharply peaked asymmetric circular data. By using wrapped Laplace, which was firstly introduced by Jammalamadaka and Kozbowski (2003), and its mixture distributions, we considered the model fitting problem of multi-modal circular data as well as unimodal one. In particular we suggested EM algorithm to find ML estimates of the mixture of wrapped Laplace distributions. Simulation results showed that the suggested EM algorithm is very accurate and useful.

• Journal of Distribution Science
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• v.17 no.2
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• pp.5-11
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• 2019

Purpose - This paper examines how corporate social responsibility of the Korean retail industry affects the degree of asymmetric information. Recent theories predict that a firm's active engagement in socially responsible activities lowers the degree of asymmetric information of the firm. Research design, data, and methodology - This paper uses the sum of environmental and social scores (ES), published by the Korean Corporate Governance Service in order to proxy the degree of socially responsible management practices of Korean retail firms. This paper uses the ordinary least square method to investigate the above predictions. The publicly traded Korea retail firms listed in the Korean Exchange are analyzed from 2011 to 2016. To measure the degree of asymmetric information, this paper adopts the analyst dispersion and price impact measures. Results - This paper shows that the ES score has significantly positive relationships with these two measures of information asymmetry. The environmental score seems to increase the analyst dispersion measure and the social score appears to raise the price impact measure mores significantly. Conclusions - The results do not support the prior theory expecting a negative relationship between corporate social responsibility and the degree of asymmetric information. Environmental and social scores are found to affect the measures of information asymmetry differently.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.393-402
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• 2021

This study aims to examine whether symmetric effects or asymmetric effects of exchange rates exist in determining the money demand in Indonesia. Simple-sum money and Divisia money were included in different models for comparison due to the financial developments in Indonesia. This study uses time-series data from 1996Q1 to 2019Q4 for the estimation. The nonlinear autoregressive distributed lag (NARDL) model is utilized to verify the asymmetric effects of exchange rates on money demand. The Augmented Dickey-Fuller and Phillips-Perron unit root tests were performed to verify the order of integration of the variables. The findings of this study revealed that the exchange rate is one of the most important determinants of money demand in Indonesia and the effect is asymmetric. The findings further indicated that money demand function, which incorporates Divisia monetary aggregate is parsimonious. Monetary targets such as money supply and interest rates are critical for monetary policy conduct to achieve inflation levels set by government. As the adoption of an inflation targeting framework needs to be in keeping with the flexible exchange rate system, the asymmetric effect of exchange rate changes can be used in exchange rate policy conduct to achieve financial system and price stability.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.39-48
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• 2024

In this paper, we introduce an extended GARCH model designed to address asymmetric leverage effects. The variance in the standard GARCH model is composed of past conditional variances and past squared residuals. However, it is not possible to model asymmetric leverage effects with squared residuals alone, so in this paper, we propose a new extended GARCH model to explain the leverage effects using the Yeo-Johnson transformation which adjusts transformation parameter to make asymmetric data more normal or symmetric. We utilize the reverse properties of Yeo-Johnson transformation to model asymmetric volatility. We investigate the characteristics of the proposed model and parameter estimation. We also explore how to derive forecasts and forecast intervals in the proposed model. We compare it with standard GARCH and other extended GARCH models that model asymmetric leverage effects through empirical data analysis.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.237-245
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• 2007

Nonlinear asymmetric time series models have the growing interest in econometrics and finance. Threshold model is one of the successful asymmetric model. We consider a smooth transition ARMA model which converges a.s. to a threshold ARMA model and show that the smooth transition ARMA model admits a stationary measure, provided a suitable condition on the coefficients of the autoregressive parts of the different regimes is satisfied. Stationarity of a smooth transition GARCH model is also obtained.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.793-798
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• 2012

In this paper, we propose regression methods based on the likelihood function. We assume Arnold-Beaver Skew Normal(ABSN) errors in a simple linear regression model. It was shown that the novel method performs better with an asymmetric data set compared to the usual regression model with the Gaussian errors. The utility of a novel method is demonstrated through simulation and real data sets.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.115-128
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• 2019

The study aims to investigate the pattern of relationships such as symmetric or asymmetric, between exchange rate and foreign direct investment in Bangladesh by applying Autoregressive Distributed Lagged (ARDL) and nonlinear ARDL. In this study, we employed quarterly data for the period of 1974Q1 to 2016Q4. Data were collected and aggregated from various sources namely, Bangladesh Economic Review published by Ministry of Finance and statistical yearbook published by Bangladesh Bureau of Statistics and an annual report published by Bangladesh Bank. The relationship between exchange rate and FDI inflows attract immense interest in the recent periods, especially for developing countries' perspective. The results of the study ascertain the long run relationship between FDI, exchange rate, monetary policy, and fiscal policy. Considering the asymmetric assumption, the findings from NARDL confirm the existence of a long-run asymmetric relationship in the empirical equation. In the long run, it is observed that positive change that is the appreciation of exchange rate against USD decrease FDI inflows and negative shocks results in grater inflows of FDI, however, the positive shocks produce higher intensity that negative shocks in Exchange rate. For directional causality, the coefficients of error correction term confirm long-run causality, in particular, bidirectional causality unveiled between FDI and exchange rate.

• Journal of Korea Multimedia Society
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• v.25 no.7
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• pp.922-931
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• 2022

Recently, the need for health information management platforms has been increasing for efficient medical and IT technology research. However, health information is requiring security management by law. When permissioned blockchain technology is used to manage health information, the integrity is provided because only the authenticated users participate in bock generation. However, if the blockchain server is attacked, it is difficult to provide security because user authentication, block generation, and block verification are all performed on the blockchain server. In this paper, therefore, we propose a Health Information Management Server, which uses a permissioned blockchain algorithm and asymmetric cryptography. Health information is managed as a blockchain transaction to maintain the integrity, and the actual data are encrypted with an asymmetric key. Since using a private key kept in the institute local environment, the data confidentiality is maintained, even if the server is attacked. 1,000 transactions were requested, as a result, it was found that the server's average response time was 6,140ms, and the average turnaround time of bock generation was 368ms, which were excellent compared to those of conventional technology. This paper is that a model was proposed to overcome the limitations of permissioned blockchains.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1537-1545
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• 2015

Support vector quantile regression (SVQR) can be obtained by applying support vector machine with a check function instead of an e-insensitive loss function into the quantile regression, which still requires to solve a quadratic program (QP) problem which is time and memory expensive. In this paper we propose an SVQR whose objective function is composed of an asymmetric quadratic loss function. The proposed method overcomes the weak point of the SVQR with the check function. We use the iterative procedure to solve the objective problem. Furthermore, we introduce the generalized cross validation function to select the hyper-parameters which affect the performance of SVQR. Experimental results are then presented, which illustrate the performance of proposed SVQR.

• Journal of Internet Computing and Services
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• v.4 no.5
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• pp.51-60
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• 2003

Asynchronous iteration is a way to reduce performance degradation of some parallel algorithms due to load imbalance or transmission delay between computing nodes, which requires asymmetric communication between the nodes of different speeds. To implement such asynchronous communication on distributed memory systems, we suggest an MPMD method that creates an additional separate server process on each computing node, and compare it with an SPMD method that creates a single process per node.