• Convergence Security Journal
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• v.22 no.3
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• pp.79-86
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• 2022

Voice phishing is a cyber crime in which fake financial institutions, the Public Prosecutor's Office, and the National Police Agency are impersonated to find out an individual's Certification number and credit card number or withdraw a deposit. Recently, voice phishing has been carried out in a subtle and secret way. Analyzing the trend of voice phishing that occurred in '18~'21, it was found that there is a seasonality that occurs rapidly at a time when the movement of money is intensifying in the trend of voice phishing, giving ambiguity to time series analysis. In this research, we adjusted seasonality using the X-12 seasonality adjustment methodology for accurate prediction of voice phishing occurrence trends, and predicted the occurrence of voice phishing in 2022 using the ARIMA model.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.54-61
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• 2019

Recently, IITS (intelligent integrated transportation system) has been important topic in Smart City related industry. As a main objective of IITS, prevention of traffic jam (due to car accidents) has been attempted with help of advanced sensor and communication technologies. Studies show that car accident has certain correlation with some factors including characteristics of location, weather, driver's behavior, and time of day. We concentrate our study on observing auto correlativity of car accidents in terms of time of day. In this paper, we performed the ARIMA tests including ADF (augmented Dickey-Fuller) to check the three factors determining auto-regressive, stationarity, and lag order. Summary on forecasting of hourly car crash counts is presented, we show that the traffic accident data obtained in Korea can be applied to ARIMA model and present a result that traffic accidents in Korea have property of being recurrent daily basis.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.995-1005
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• 2009

Conditional correlation between financial time series plays an important role in risk management, asset allocation and portfolio selection and therefore diverse efforts for modeling conditional correlations in multivariate-GARCH processes have been made in last two decades. In particular, CCC (cf. Bollerslev, 1990) and DCC(dynamic conditional correlation, cf. Engle, 2002) models have been commonly used since they are relatively parsimonious in the number of parameters involved. This article is concerned with DCC modeling for multivariate GARCH processes in comparison with CCC specification. Various multivariate financial time series are analysed to illustrate possible advantages of DCC over CCC modeling.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.129-139
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• 2023

Forecasting volatility is essential to avoiding the risk caused by the uncertainties of an financial asset. Complicated financial volatility features such as ambiguity between non-stationarity and stationarity, asymmetry, long-memory, sudden fairly large values like outliers bring great challenges to volatility forecasts. In order to address such complicated features implicity, we consider machine leaning models such as LSTM (1997) and GRU (2014), which are known to be suitable for existing time series forecasting. However, there are the problems of vanishing gradients, of enormous amount of computation, and of a huge memory. To solve these problems, a causal temporal convolutional network (TCN) model, an advanced form of 1D CNN, is also applied. It is confirmed that the overall forecasting power of TCN model is higher than that of the RNN models in forecasting VIX, VXD, and VXN, the daily volatility indices of S&P 500, DJIA, Nasdaq, respectively.

• Management Science and Financial Engineering
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• v.20 no.2
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• pp.33-37
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• 2014

A flow shop scheduling problem involves scheduling jobs on multiple machines in series in order to optimize a given criterion. The flow time of a job is the amount of time the job spent before its completion and the stretch of the job is the ratio of its flow time to its processing time. In this paper, a hybrid genetic algorithm (HGA) approach is proposed for minimizing the total stretch in flow shop scheduling. HGA adopts the idea of seed selection and development in order to reduce the chance of premature convergence that may cause the loss of search power. The performance of HGA is compared with that of genetic algorithms (GAs).

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.15-24
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• 2018

The study examines the magnitude of economic spillover and the impact of foreign direct investment (FDI) inflows on the efficiency of the bank industry in China. This study employs unit root tests, cointegration tests and cointegrating regression analysis, including fully modified ordinary least squares (FMOLS), canonical cointegrating regression (CCR) and dynamic OLS (DOLS) to test the proposed hypotheses. The sample is restricted to the period of time in which monthly data is available and comparable among variables for the period from January 2002 to October 2013 (142 observations). All of the time series data was collected and retrieved from the People's Bank of China, China Monthly Statistics from the National Bureau of Statistics of China, and International Financial Statistics database from International Monetary Fund. The results of the Johansen cointegration test suggest that there is a long-run equilibrium relationship between FDI inflows, foreign exchange rate and banks performance in China. The results of cointegrating regression analysis using FMOLS, CCR and DOLS suggest that M2 supply and FDI inflows are significant at the 0.01 level. The results confirm that FDI inflows in the banking sector are positively related to the increase of banks productivity and performance and short-term loans in China. However, the results suggest that Chinese Yuan currency exchange rate to U.S. dollar is not significant in the banking and financial industry of China.

• Journal of the Korean Institute of Rural Architecture
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• v.14 no.3
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• pp.9-16
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• 2012

Both internally and externally environmental changes surround the rural areas such as rapid growth of the early-retired employee under the WTO, the Asian financial crisis in 1997, and the financial crisis in 2007 brought about much transformation in our rural residential environment. According to this changes and demands, the rural areas have been transformed from the area for farmer to the area for farmer and non farmer, that is, peoples that to leave the city to go back to farm or return to home village. Of this time, there needs a change in rural development policies which can make the urban residents migrate and settle in the rural areas as they are naturally embracing the rural life according to the social background and demand. In this point of view, we attempted, in this paper, to survey and analyze the changing trends of residential environment following the spatial composition with house types and rural villages in rural areas. The result of this study will be expected to be a reference for the direction of desirable residential environment in rural areas.

• Asia-Pacific Journal of Business
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• v.4 no.2
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• pp.41-53
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• 2013

Undoubtedly, the basic sinking fund formula gives the future value of a series of equal installments. The main underlying assumption for using this formula is that installment and compounding frequency must be in equal interval. But when installment for a deposit scheme or any other savings scheme and compounding frequency do not occur in an equal interval, which is treated as the complex annuity problems in Finance Literature, the basic sinking fund formula does not give the accurate result. As a result, the obtainable amount from different deposit schemes offered by different banks and financial institutions does not match with the amount of future value calculated through the basic sinking fund formula by the investors or savers. This study focuses the concealed facts for such type of mismatches in values and at the same time it provides a solution through developing a new formula by extending the basic formula intended not only to remove those mismatches but also get the accurate future value from a sinking fund provision in case of complex annuity. Besides, since banks and financial institutions calculate the interest on the average amount of equal installments deposited within a period of time due to complex annuity, the study also formulates an arithmetic formula for calculating the average amount of installment.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.53-60
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• 2021

Foreign direct investment (FDI) is especially important for developing countries. This study investigates the determinants of FDI in the case of Indonesia. Most empirical researches in this field used time series data of a single country or panel data of several countries. Although panel data analysis is more comprehensive, however results taken from cross-country analysis cannot be directly applied to any specific country in the dataset and therefore lacks practicality. In this research, panel data analysis of a single country is performed to overcome the aforementioned shortcomings. Five determinants of FDI are tested using panel data of 33 Indonesian provinces over 10-year period of time. Two methodologies are adopted, random/fixed effects model and Granger Causality. The results show that only market size significantly affects FDI when tested using both methodologies. Human capital and financial market development show significant result in one of the two methodologies. While, economic growth and infrastructure did not show any significant results at all. This research stresses the importance of comprehensive single country analysis since only one out of five commonly discussed determinants is applicable in the case of Indonesia. Governments should therefore carefully reconsider the use of cross-country analysis as a basis of their policy formulations.

• Korean Management Science Review
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• v.34 no.1
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• pp.71-84
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• 2017

The purpose of this study is to extract the characteristic cost through the time series analysis of each cost from 2003 to 2014, and to grasp the performance and relevance of the enterprise. Therefore, in this section, we analyzed the time-series analysis of selling, administrative, and non-operating expenses as described above. First, depreciation cost, advertising cost, transportation cost, research cost, current research cost, and ordinary development cost were extracted as the variables of interest to be verified in the empirical analysis. However, in the analysis of non-operating expenses, we could not extract the specific cost, but we could grasp the time-series flow of cost data before and after two epochs such as financial crisis and introduction of IFRS obligation. The results of this study show that sales management costs have a positive (+) effect on firm value. Empirical analysis confirms that management is trying to increase or decrease the cost This can be confirmed by the empirical results of this paper. At present, general enterprise accounting is done through ERP system. However, since the ERP system does not have an analysis system for each sales and management cost, the current system has difficulty in knowing the budget item for each cost each time the expenditure resolution for each cost item is made, It is a reality that the expenditure plan must be managed separately and it is inconvenient to keep it. However, if this practical difficulty is solved by the cost analysis system such as sales management cost, the present accounting information system will be further developed. Furthermore, the management will increase the profit item It is thought that coordination actions can also be prevented in advance.