• Journal of Multimedia Information System
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• v.8 no.3
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• pp.183-190
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• 2021

In this paper, we implement a system for a fund recommendation based on the investment propensity and for a future fund price prediction. The investment propensity is classified by scoring user responses to series of questions. The proposed system recommends the funds with a suitable risk rating to the investment propensity of the user. The future fund prices are predicted by Prophet model which is one of the machine learning methods for time series data prediction. Prophet model predicts future fund prices by learning the parameters related to trend changes. The prediction by Prophet model is simple and fast because the temporal dependency for predicting the time-series data can be removed. We implement web pages for the fund recommendation and for the future fund price prediction.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.142-147
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• 2021

In this paper, we propose an intelligent research fund management system that applies artificial intelligence technology to an integrated research fund management system. By defining research fund management rules as work rules, a detection model learned using deep learning is designed, through which the disapproval status is presented for each research fund usage history. The disapproval detection system of the RCMS implemented in this study predicts whether the newly registered usage details are recognized or disapproved using an artificial intelligence model designed based on the use of an 8.87 million research fund registered in the RCMS. In addition, the item-detail recommendation system described herein presents the usage details according to the usage history item newly registered by the artificial intelligence model through a correlation between the research cost usage details and the item itself. The accuracy of the recommendation was shown to be 97.21%.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.36-40
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• 2013

The paper discusses the problem of how to allocate the fund to a large number of individuals in a higher school so as to bring a higher utility return based on the theory of uncertain set. Suppose that experts can assign each invested individual a corresponding nondecreasing membership function on a close interval I according to its actual level and developmental foreground. The membership degree at the fund $x{\in}I$ is called utility degree from fund x, and product (minimum) of utility degrees of distributed funds for all invested individuals is called united utility degree from the fund. Based on the above concepts, we present an uncertain optimization model, called Maximal United Utility Degree (or Maximal Membership Degree) model for fund distribution. Furthermore, we use nondecreasing polygonal functions defined on close intervals to structure a mathematical maximal united utility degree model. Finally, we design a genetic algorithm to solve these models.

• The Journal of Industrial Distribution & Business
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• v.9 no.1
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• pp.9-23
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• 2018

Purpose - The purpose of this paper is to investigate the potential benefits or detriments of team management on fund performance in the mutual fund market. An additional purpose of this study is to examine the optimal number of managers in a fund industry for superior performance. Research design, data, and methodology - This paper investigates the effect of managerial structure on fund performance in the Korean active mutual fund market between 2001 and 2008. For this, we analyze two risk-adjusted performances measures- the capital asset pricing model (CAPM) and the three-factor model of Fama & French (1993). Results - First, we found that single-managed funds exhibited superior performance. Second major finding was that as the number of managers in a fund increases, the fund performance deteriorates. Finally, the results reveal that the sharpest performance drop occurs when team size increases from a 5-person team to a 6-person team. Conclusions - The results suggest that the management structure can be a source of competitive advantage for fund performance. As considering fund performance is the outcome of managers' decision-making, this study contributes to not only the financial literature but also the literature in other areas, such as management and general business.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1049-1060
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• 2009

The expansion of volatility in Korean Stock Market made it more difficult for the individual to invest directly and increased the weight of indirect investment through a fund. The purpose of this study is to construct the EIF(enhanced index fund) model achieves an excessive return among several types of fund. For this purpose, this paper propose portfolio optimization model to manage an index fund by using GA(genetic algorithm), and apply the trading amount and the closing price of standard index to earn an excessive return add to index fund return. The result of the empirical analysis of this study suggested that the proposed model is well represented the trend of KOSPI 200 and the new investment strategies using this can make higher returns than Buy-and-Hold strategy by an index fund, if an appropriate number of stocks included.

• The Journal of Information Systems
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• v.28 no.4
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• pp.333-358
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• 2019

Purpose The study aims to develop a data-based decision model for private bankers when recommending hedge funds to their customers in financial institutions. Design/methodology/approach The independent variables are set in two groups. The independent variables of the first group are aggressive investors, active investors, and risk-neutral type investors. In the second group, variables considered by private bankers include customer propensity to invest, reliability, product subscription experience, professionalism, intimacy, and product understanding. A decision-making variable for a private banker is in recommending a first-rate general private fund composed of foreign and domestic FinTech products. These contain dependent variables that include target return rate(%), fund period (months), safeguard existence, underlying asset, and hedge fund name. Findings Based on the research results, there is a 94.4% accuracy in decision-making when the independent variables (customer rating, reliability, intimacy, product subscription experience, professionalism and product understanding) are used according to the following order of relevant dependent variables: step 1 on safeguard existence, step 2 on target return rate, step 3 on fund period, and step 4 on hedge fund name. Next, a 93.7% accuracy is expected when decision-making uses the following order of dependent variables: step 1 on safeguard existence, step 2 on target return rate, step 3 on underlying asset, and step 4 on fund period. In conclusion, a private banker conducts a decision making stage when recommending hedge funds to their customers. When examining a private banker's recommendations of hedge funds to a customer, independent variables influencing dependent variables are intimacy, product comprehension, and product subscription experience according to a categorical regression model and artificial neural network analysis model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1201-1208
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• 2019

The government has operated financing fund under the National Finance Act for the smooth conduct of national policy. But, It is exposed to problems such as the possibility of abuse of fund and the lack of after-loan management. In this paper, It uses fintech such as the blockchain and machine learning to solve these problems. The fund operation procedure is designed as a consortium blockchain, and it suggests the application of PBFT negotiation algorithm and the smart contract. In case of the fund management, it suggests utilizing multilayer artificial neural network model of machine learning and a module of result interpretation. The introduction of this research approach will improve the transparency and efficiency of the financing fund, ensure the credibility and also contribute to the improvement of the fund management and the establishment of the fund policy.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.433-442
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• 2020

This study investigates the impact of fiscal transfer, specifically the Village Fund Transfer, on rural income inequality and rural poverty. Studies on fiscal transfer offers contrasting outcomes, some argues that fiscal transfer suppresses wealth disparity, while others argue that it tends to widen disparity. This study employs descriptive analysis in estimating the elasticity of income inequality and poverty rate before and after the Village Fund Transfer. It develops multiple regressions model on panel datasets of 33 provinces in Indonesia before and after the implementation of Village Fund Transfer. This study suggests that the elasticity of income inequality is higher after the implementation of village fund transfer. Rural poverty tends to decline annually, however, the elasticity changes is lower after the implementation of village fund transfer. Furthermore, this study suggests that village fund transfer is insignificant in coping with the issue of income inequality, while education and the level of labor productivity of agricultural sector appears to be the determinant factor in tackling the issue of income inequality in the rural areas. This study further reveals the significance of village fund transfer in suppressing the rural poverty rate. This study also highlights the significance of human resources quality and agricultural sector in reducing poverty rate in rural areas.

• KDI Journal of Economic Policy
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• v.41 no.2
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• pp.1-39
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• 2019

This paper utilizes a life-cycle overlapping-generations model to quantify the welfare effects of plans to postpone the depletion of the National Pension Fund. In order for the model to incorporate the rapidly changing demographic structure of Korea fully, we build and calibrate a model in transition directly. The model is considered suitable for analyzing the effects of demographic changes on the Korean economy and the effects of plans to change the National Pension System. According to a simulation of the model, to postpone the depletion of the National Pension Fund for 30 years, the premium rate must be increased to 18.3% from the current rate of 9%. By postponing the depletion of the fund reserve, young and future generations gain significantly at the expense of the older generations. The simulation results should be, however, interpreted as meaning that the current system is unjustifiably partial to the older generations. Moreover, given the current premium rate, it is desirable to strengthen the income-redistribution function of the National Pension System.

• International Commerce and Information Review
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• v.6 no.2
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• pp.339-358
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• 2004

This article discusses the critical issues on obligations and responsibilities in electronic funds transfer(EFT) between Article 4A of the UCC and the Model Law on International Credit Transfers of UNCITRAL. The electronic fund transfers begin with the issue of the payment order by the originator to the receiving bank for the beneficiary. All obligations and responsibilities of parties concerned occur when the receiving bank accept the originator's payment order to executes. So far, some the most compelling studies have focused on the legal obligations and responsibilities of electronic fund transfer in Korea. Therefore, In this paper, we would like to examine some problems of obligations and responsibilities in electronic fund transfer from Article 4A of UCC and the Model Law on International Credit Transfers of UNCITRAL. And also we present some Implications to reform EFT Law for the efficient application.