• The Journal of Asian Finance, Economics and Business
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• v.4 no.1
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• pp.59-66
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• 2017

The purpose of this paper is to review the quality of corporate governance from the prior empirical literature. This study finds that most of the researchers developed the self structured corporate governance index and few researchers used the corporate governance index provided by rating agencies. This study also finds that there is no uniform basis to measure the corporate governance quality and observed the variation in terms of overall and individual attributes of corporate governance; sub-indices of corporate governance; scoring system; weighted and un-weighted method; statistical method; time period; financial and non financial companies; code of corporate governance; listing requirement; disclosure practices; legal environment; firms characteristics; and country perspective. This study also observed that overall corporate governance quality is very low in most of the studies and even quality of corporate governance varies in the firms within the same country. This study recommends that the boundary of corporate governance quality should be defined based on the agreed set of rules and regulation, code of governance and practices. This study also suggests that the regulator and policy makers should more emphasize on code of corporate governance and regulatory framework and monitoring to improve the quality of corporate governance.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.45-56
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• 2018

The paper aims to examine relationships between search-based sentiment and stock market reactions in Vietnam. This study constructs an internet search-based measure of sentiment and examines its relationship with Vietnamese stock market returns. The sentiment index is derived from Google Trends' Search Volume Index of financial and economic terms that Vietnamese searched from January 2011 to June 2018. Consistent with prediction from sentiment theories, the study documents significant short-term reversals across three major stock indices. The difference from previous literature is that Vietnam stock market absorbs the contemporaneous decline slower while the subsequent rebound happens within a day. The results of the study suggest that the sentiment-induced effect is mainly driven by pessimism. On the other hand, optimistic investors seem to delay in taking their investment action until the market corrects. The study proposes a unified explanation for our findings based on the overreaction hypothesis of the bearish group and the strategic delay of the optimistic group. The findings of the study contribute to the behavioral finance strand that studies the role of sentiment in emerging financial markets, where noise traders and limits to arbitrage are more obvious. They also encourage the continuous application of search data to explore other investor behaviors in securities markets.

• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.71-85
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• 2021

Purpose - Prior studies have found that the characteristics of managers, corporate governance structure, corporate social responsibility and so on affect firm value. This study explores whether managerial overconfidence affects firm value through empirical analysis. Design/methodology/approach - Korean-listed non-financial companies from 2011 - 2017 are collected as the research sample. Firm value is measured by Tobin's Q, and managerial overconfidence is measured using a composite index encompassing various financial data. OLS and fixed effect model are used to investigate the relationship between managerial overconfidence and firm value. Findings - Managerial overconfidence is positively associated with firm value. Additional analysis reveals the following: (1) In the three subsamples of large, backbone, and small- and medium-sized enterprises, managerial overconfidence is beneficial to firm values. (2) Managerial overconfidence increases firm value on the t+1 year. Research implications or Originality - We use a comprehensive index with higher trust and feasibility to measure manager overconfidence and empirically confirm that managerial overconfidence can become a factor to improve firm value. Thus, it is necessary for shareholders to adopt an objective and neutral attitude and reasonably understand the psychological characteristics of managers when selecting CEOs. In addition, it is necessary to continue to optimize the measurement method of managerial overconfidence.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.63-71
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• 2010

Business entrepreneurs reflect their views of domestic and foreign economic activities on their operation for the growth of their business. The decision, forecasting, and planning based on their economic sentiment affect business operation such as production, investment, and hiring and consequently affect condition of national economy. Business survey index(BSI) is compiled to get the information of business entrepreneurs' economic sentiment for the analysis of business condition. BSI has been used as an important variable in the short-term forecasting models for business cycle analysis, especially during the the period of extreme business fluctuations. Recent financial crisis has arised extreme business fluctuations similar to those caused by currency crisis at the end of 1997, and brought back the importance of BSI as a variable for the economic forecasting. In this paper, the meaning of BSI as an economic sentiment index is reviewed and a GUIDE regression tree is constructed to find out the factors which affect on BSI. The result shows that the variables related to the stability of financial market such as kospi index(Korea composite stock price index) and exchange rate as well as manufacturing operation ratio and consumer goods sales are main factors which affect business entrepreneurs' economic sentiment.

• Management Science and Financial Engineering
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• v.21 no.2
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• pp.13-23
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• 2015

This study addresses the question as to whether the option prices have useful predictive information on the direction of stock markets by investigating a forecasting power of volatility curvatures and skewness premiums implicit in S&P 500 index option prices traded in Chicago Board Options Exchange. We begin by estimating implied volatility functions and risk neutral price densities every minute based on non-parametric method and then calculate volatility curvature and skewness premium using them. The rationale is that high volatility curvature or high skewness premium often leads to strong bullish sentiment among market participants. We found that the rate of return on the signal following trading strategy was significantly higher than that on the intraday buy-and-hold strategy, which indicates that the S&P500 index option prices have a strong forecasting power on the direction of stock index market. Another major finding is that the information contents of S&P 500 index option prices disappear within one minute, and so one minute-delayed signal following trading strategy would not lead to any excess return compared to a simple buy-and-hold strategy.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.9-21
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• 2020

The aim of this paper is to predict the Borsa Istanbul (BIST) 30 index movements to determine the most accurate buy and sell decisions using the methods of Artificial Neural Networks (ANN) and Genetic Algorithm (GA). We combined these two methods to obtain a hybrid intelligence method, which we apply. In the financial markets, over 100 technical indicators can be used. However, several of them are preferred by analysts. In this study, we employed nine of these technical indicators. They are moving average convergence divergence (MACD), relative strength index (RSI), commodity channel index (CCI), momentum, directional movement index (DMI), stochastic oscillator, on-balance volume (OBV), average directional movement index (ADX), and simple moving averages (3-day moving average, 5-day moving average, 10-day moving average, 14-day moving average, 20-day moving average, 22-day moving average, 50-day moving average, 100-day moving average, 200-day moving average). In this regard, we combined these two techniques and obtained a hybrid intelligence method. By applying this hybrid model to each of these indicators, we forecast the movements of the Borsa Istanbul (BIST) 30 index. The experimental result indicates that our best proposed hybrid model has a successful forecast rate of 75%, which is higher than the single ANN or GA forecasting models.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1182-1188
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• 2014

Recently, the research on database outsourcing has been actively done with the popularity of cloud computing. However, because users' data may contain sensitive personal information, such as health, financial and location information, the data encryption methods have attracted much interest. Existing data encryption schemes process a query without decrypting the encrypted databases in order to support user privacy protection. On the other hand, to efficiently handle the large amount of data in cloud computing, it is necessary to study the distributed index structure. However, existing index structure and query processing algorithms have a limitation that they only consider single-column query processing. In this paper, we propose a grid-based multi column indexing scheme and an encrypted query processing algorithm. In order to support multi-column query processing, the multi-dimensional index keys are generated by using a space decomposition method, i.e. grid index. To support encrypted query processing over encrypted data, we adopt the Hilbert curve when generating a index key. Finally, we prove that the proposed scheme is more efficient than existing scheme for processing the exact and range query.

• Geomechanics and Engineering
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• v.21 no.4
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• pp.391-399
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• 2020

Brittleness is one of the most important properties of rock which has a major impact not only on the failure process of intact rock but also on the response of rock mass to tunneling and mining projects. Due to the lack of a universally accepted definition of rock brittleness, a wide range of methods, including direct and indirect methods, have been developed for its measurement. Measuring rock brittleness by direct methods requires special equipment which may lead to financial inconveniences and is usually unavailable in most of rock mechanic laboratories. Accordingly, this study aimed to develop a new strength-based index for predicting rock brittleness based on the obtained base form. To this end, an innovative algorithm was developed in Matlab environment. The utilized algorithm finds the optimal index based on the open access dataset including the results of punch penetration test (PPT), uniaxial compressive and Brazilian tensile strength. Validation of proposed index was checked by the coefficient of determination (R²), the root mean square error (RMSE), and also the variance for account (VAF). The results indicated that among the different brittleness indices, the suggested equation is the most accurate one, since it has the optimal R², RMSE and VAF as 0.912, 3.47 and 89.8%, respectively. It could finally be concluded that, using the proposed brittleness index, rock brittleness can be reliably predicted with a high level of accuracy.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.405-413
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• 2015

The purpose of this study is to measure the level of competition in the degree of Regional Public Hospital that can provide a basis for establishing an effective management strategy and analysis of the financial performance. Investigation period of the Regional Public Hospital HHI(Herfindahl-Hirschman Index) over three years from 2010, which was unknown until 2012, index and management performance evaluation criteria, a total of 31 were selected as Regional Public Hospital surveyed. In the conclusions, it showed that the most concentrated market with high financial performance, a significant correlation between the degree of local competition and financial indicators showed. The Regional Public Hospital for trends according to the degree of competitive local medical market and therefore is required to establish policies and practices to ensure competitiveness and public interest in the region. The Regional Public Hospital in order to preempt the lead for the competitiveness of other institutions will be considered in the strategy, such as improving medical services and capital investment.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.429-442
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• 2015

Volatility forecasting in financial markets is an important issue because it is directly related to the profit of return. The volatility is generally modeled as time-varying conditional heteroskedasticity. A generalized autoregressive conditional heteroskedastic (GARCH) model is often used for modeling; however, it is not suitable to reflect structural changes (such as a financial crisis or debt crisis) into the volatility. As a remedy, we introduce the Markov regime switching GARCH (MRS-GARCH) model. For the empirical example, we analyze and forecast the volatility of the daily Korea Composite Stock Price Index (KOSPI) data from January 4, 2000 to October 30, 2014. The result shows that the regime of low volatility persists with a leverage effect. We also observe that the performance of MRS-GARCH is superior to other GARCH models for in-sample fitting; in addition, it is also superior to other models for long-term forecasting in out-of-sample fitting. The MRS-GARCH model can be a good alternative to GARCH-type models because it can reflect financial market structural changes into modeling and volatility forecasting.