• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.423-431
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• 2021

This study aims to examine the effect of liquidity, activity, leverage, and profitability on firm value, as well as the effect of disclosure of corporate social responsibility (CSR), which in this study is a moderator and company size as a control variable. The sampling technique used in this study is a purposive sampling method with certain criteria, to obtain a sample of 22 LQ45 index companies listed on the Indonesia Stock Exchange in 2014-2019. The data analysis method in this study used was the Multiple Linear Regression Analysis with the SPSS 18 Program. The results show that the ratios of liquidity, activity, leverage, and profitability are significant to firm value in accordance with the initial hypothesis of the study. Corporate Social Responsibility (CSR) plays a role as a moderating variable and company size variable as a control variable on the effect of financial ratios (liquidity, activity, leverage, and profitability) on firm value. The implication of this research is that CSR has a very important role in increasing company value. To attract more investors, companies must pay attention not only to financial performance but also to social performance. Large-scale companies tend to do more CSR so that the company value will increase.

• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.409-417
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• 2022

This research uses a panel data set of selected developed and emerging economies to investigate the relationship between firm value and the Islamic label. A low-debt company is a proxy for excellent governance, and good governance has a significant positive impact on a company's valuation. We can claim that the Islamic label may also be a proxy for excellent governance and will significantly impact a company's economic value because it reflects low debt Sharia-compliant companies. To explore this relationship, cross-country data from non-financial enterprises in Pakistan, the United States, Malaysia, and Indonesia was acquired from 2010 to 2015. The study's findings indicate that the Islamic label has a positive significant impact on the firm's worth in the whole sample, including all countries. With the exception of the United States, we have also collected the same information at the country level. We also discovered that the corporate governance index at the firm level has a positive significant impact on firm value. The findings show that the Islamic label reflects good governance and hence can be used as a proxy for good governance. The analysis differentiates between Islamic labeled and conventional enterprises in developed and emerging nations, adding to our understanding of who contributes to enhanced corporate financial performance.

• 디지털산업정보학회논문지
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• 제4권4호
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• pp.103-111
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• 2008

While the demand for ASP(Application Service Provider) focused on small and medium enterprises who are fully aware of needs of ICT readiness has been increasing, those who consider to adopt ASP are wondering whether their performance would be actually successful if they did. These concerns can be an important standard of judgement, when introducing new information systems, by analyzing ROI(Return on Investment) on the current enterprises. Therefore, to review the feasibility of investing IT and measuring the performance, this study suggests a framework for ROI analysis which estimates IT investment performance, through multi-criteria approach on both financial performance index and non-financial one. We applied methodology on ASP-based IT investment performance evaluation to sample manufacturing companies under 50 employees and deduced the main implications to be considered when introducing the system.

• East Asian Economic Review
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• 제21권2호
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• pp.147-165
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• 2017

This study quantifies the dynamic interrelationship between the KOSPI index return and search query data derived from the Naver DataLab. The empirical estimation using a bivariate GARCH model reveals that negative contemporaneous correlations between the stock return and the search frequency prevail during the sample period. Meanwhile, the search frequency has a negative association with the one-week- ahead stock return but not vice versa. In addition to identifying dynamic correlations, the paper also aims to serve as a test bed in which the existence of profitable trading strategies based on big data is explored. Specifically, the strategy interpreting the heightened investor attention as a negative signal for future returns appears to have been superior to the benchmark strategy in terms of the expected utility over wealth. This paper also demonstrates that the big data-based option trading strategy might be able to beat the market under certain conditions. These results highlight the possibility of big data as a potential source-which has been left largely untapped-for establishing profitable trading strategies as well as developing insights on stock market dynamics.

• Korean Journal of Mathematics
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• 제22권3호
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• pp.529-552
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• 2014

As we know, some indices and data are strong influence to the price movement of some assets now, but not to another assets and in future. Thus we define some asset models for several time intervals; intraday, weekly, monthly, and yearly asset models. We define these asset models by using Brownian motion with volatility and Poisson process, and several deterministic functions(index function, twitter data function and big-jump simple function etc). In our asset models, these deterministic functions are the positive or negative levels of auxiliary indices, of analyzed data, and for imminent and extreme state(for example, financial shock or the highest popularity in the market). These functions determined by indices, twitter data and shocking news are a kind of one of speciality of our asset models. For reasonableness of our asset models, we introduce several real data, figurers and tables, and simulations. Perhaps from our asset models, for short-term or long-term investment, we can classify and reference many kinds of usual auxiliary indices, information and data.

• 재무관리연구
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• 제19권2호
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• pp.211-231
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• 2002

본 연구의 목적은 VECM(Vector Error Correction Model)과 인공지능모형(Artificial Neural Networks)을 이용하여 우리나라 증권시장과 거시경제 변수들과의 장기적 관계에 대한 설명력을 비교해보고자 함에 있다. VECM이 APT(Arbitrage Pricing Theory)에 기초를 둔 선형동학모형이라고 한다면, 인공지능모형은 비모수적 비선형모형이라는 점에서, 두 방법론의 분석결과를 직접 비판하는 것은 의미있는 연구라고 할 수 있다. 인공지능모형을 주로 활용하는 선행연구들에 의하면, 증권시장은 시장의 특이패턴들로 인해 계량경제학적 접근인 선형 모형보다는 인공지능모형을 통해 증권시장의 움직임을 설명하고 예측하는 것이 더 바람직할 수도 있다는 것이다. 따라서, 본 연구에서는 VECM분석에서 자료의 안정성을 검증하고, 공적분 백터를 발견한 이후, 장기적 균형관계의 실증적 분석을 하였다. 그리고, 인공지능모형에서는 delta rule과 Sigmoid 함수를 이용한 GRNN(General Regression Neural Net)과 Back-Propagation등의 방법들을 활용하였다. 이러한 분석결과, Back-Propagation 모형이 다른 모든 모형들보다도 더 우수한 설명력을 보여주고 있었다. 이러한 결과들은 인공지능모형이 동태적인 선형 모형보다도 더 우수한 설명력을 제공할 수 있는 가능성을 보여주고 있었다.

• 경영과학
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• 제32권3호
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• pp.91-103
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• 2015

This study recognizes that there is a correlation between the movement of the financial market and the sentimental changes of the public participating directly or indirectly in the market, and applies the relationship to investment strategies for stock market. The concerns that market participants have about the economy can be transformed to the search terms that internet users query on search engines, and search volume of a specific term over time can be understood as the economic trend of big data. Under the hypothesis that the time when the economic concerns start increasing precedes the decline in the stock market price and vice versa, this study proposes three investment strategies using casuality between price of domestic stock market and search volume from Naver trends, and verifies the hypothesis. The computational results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior in domestic stock market.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제20권4호
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• pp.277-293
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• 2016

We develop an efficient numerical method for pricing the Derivative Linked Securities (DLS). The payoff structure of the hybrid DLS consists with a standard 2-Star step-down type ELS and the range accrual product which depends on the number of days in the coupon period that the index stay within the pre-determined range. We assume that the 2-dimensional Geometric Brownian Motion (GBM) as the model of two equities and a no-arbitrage interest model (One-factor Hull and White interest rate model) as a model for the interest rate. In this study, we employ the Monte Carlo simulation method with the Compute Unified Device Architecture (CUDA) parallel computing as the General Purpose computing on Graphic Processing Unit (GPGPU) technology for fast and efficient numerical valuation of DLS. Comparing the Monte Carlo method with single CPU computation or MPI implementation, the result of Monte Carlo simulation with CUDA parallel computing produces higher performance.

• 재무관리연구
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• 제25권4호
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• pp.117-144
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• 2008

This article examines the information transmission process between the KOSPI 200 futures market and its underlying stock market, using the 10-second quote and trade data. The VAR analysis reveals that quote revisions through limit orders in general lead trades through market orders. In addition, the VAR analysis shows that the futures market tends to lead the stock market in terms of quote revisions and trades, even though the other direction is also observable. Even when we focus on the events causing large movements in quote revisions and trades, those lead and lag relations between those markets and between quote revisions and order imbalances are confirmed.

• 재무관리연구
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• 제25권4호
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• pp.145-182
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• 2008

As the life expectancy increases resulting in the aged society, the post-retirement life became one of the most important concerns of people. The long-term investment vehicles such as retirement savings and pension plans have been introduced to meet such demand of society. This paper examines the impact of asset allocation strategies on the long-term investment performance. Because of the unusually long investment horizon and the compounding effect, a suboptimal asset mix in a retirement plan can be a very costly and irreversible mistake. Instead of relying on anecdotal evidence to evaluate the merits of different allocation strategies, this paper performs various tests including stochastic dominance tests using both actual data and Monte Carlo simulated data that best fit the historical experience. The results indicate 1) the long-term investments perform better than the short-term investments, 2) the optimal asset allocation strategy for the long-term investments should be highly equity dominated.