• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.1-10
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• 2022

This research proposes a novel trading method based on sample entropy for the FTSE China A50 Index. The approach is used to determine the points at which the index should be bought and sold for various holding durations. The findings are then compared to three other trading strategies: buying and holding the index for the entire time period, using the Relative Strength Index (RSI), and using the Moving Average Convergence Divergence (MACD) as buying/selling signaling tools. The unique entropy trading method, which used 90-day holding periods and was called StEn(90), produced the highest cumulative return: 25.66 percent. Regular buy and hold, RSI, and MACD were all outperformed by this strategy. In fact, when applied to the same time periods, RSI and MACD had negative returns for the FTSE China A50 Index. Regular purchase and hold yielded a 6% positive return, whereas RSI yielded a 28.56 percent negative return and MACD yielded a 33.33 percent negative return.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1441-1461
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• 2017

Nowadays, Dynamic Adaptive Streaming over HTTP (DASH) has become very popular in streaming multimedia contents. In DASH, a client estimates current network bandwidth and then determines an appropriate video quality with bitrate matching the estimated bandwidth. Thus, estimating accurately the available bandwidth is a significant premise in the quality of video streaming, especially when network traffic fluctuates substantially. To cope with this challenge, researchers have presented various filters to estimate network bandwidth adaptively. However, experiment results show that current schemes either adapt slowly to network changes or adapt fast but are very sensitive to delay jitter and produce sharply changed estimation. This paper presents a novel bandwidth estimation scheme based on Moving Average Convergence Divergence (MACD). We applied an MACD indicator and its two thresholds to classifying network states into stable state and agile state, based on the network state different filters are applied to estimate network bandwidth. In the paper, we studied the performance of various MACD indicators and the threshold values on bandwidth estimation. Then we used a DASH proxy-based environment to compare the performance of the presented scheme with current well-known schemes. The simulation results illustrate that the MACD-based bandwidth estimation scheme performs superior to existing schemes both in the speed of adaptively to network changes and in stability in bandwidth estimation.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.113-123
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• 2003

Many researches on the application of neural networks for making financial index prediction have proven their advantages over statistical and other methods. In this paper, a neural network model is proposed for the Buying, Holding or Selling timing prediction in stocks by the price index of stocks by inputting the closing price and volume of dealing in stocks and the technical indexes(MACD, Psychological Line). This model has an equalized multi-layer arithmetic function as well as the time series prediction function of backpropagation neural network algorithm. In the case that the numbers of learning data are unbalanced among the three categories (Buying, Holding or Selling), the neural network with conventional method has the problem that it tries to improve only the prediction accuracy of the most dominant category. Therefore, this paper, after describing the structure, working and learning algorithm of the neural network, shows the equalized multi-layer arithmetic method controlling the numbers of learning data by using information about the importance of each category for improving prediction accuracy of other category. Experimental results show that the financial index prediction using the equalized multi-layer arithmetic neural network has much higher correctness rate than the other conventional models.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.94-103
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• 2021

This study aims to propose technical trading rules for Bitcoin futures and empirically analyze investment performance. Investment strategies include standard trading rules such as VMA, TRB, FR, MACD, RSI, BB, using Bitcoin futures daily data from December 18, 2017 to March 31, 2021. The trend-following rules showed higher investment performance than the comparative strategy B&H. Compared to KOSPI200 index futures, Bitcoin futures investment performance was higher. In particular, the investment performance has increased significantly in Sortino Ratio, which reflects downside risk. This study can find academic significance in that it is the first attempt to systematically analyze the investment performance of standard technical trading rules of Bitcoin futures. In future research, it is necessary to improve investment performance through the use of deep learning models or machine learning models to predict the price of Bitcoin futures.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.127-130
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• 2009

We propose a method for detecting DDoS (Distributed Denial of Service) traffic in real-time inside the backbone network. For this purpose, we borrow the concepts of MACD (Moving Average Convergence Divergence) and RoC (Rate of Change), which are used for technical analysis in the stock market Due to the fact that the method is based on a quantitative, rather than a heuristic, detection level, DDoS traffic can be detected with greater accuracy (by reducing the false alarm ratio). Through simulation results, we show how the detection level is determined and demonstrate how much the accuracy of detection is enhanced.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1536-1543
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• 2000

In this paper, we propose a multiple access scheme for efficient transmission of realtime and non-realtime data in IMT-2000 through cdma2000's CDMA MACD. On the contrast to the conventional circuit-based service, this framework is packet-oriented service. maximum number of simultaneous subscribers increases due to the statistical multiplexing based on variable transmission rate of realtime data. System performance is evaluated and compared with conventional circuit-based scheme considering transmission delay and channel utilization by computer simulation.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.107-109
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• 2013

주식 시장에서 거래되고 있는 증권은 MACD(Moving Average Convergence Divergence), Stochastic 등의 보조 지표를 이용하는 기술적 분석을 통하여 매수/매도 시점을 결정한다. 주식 시장의 객관적인 자료를 통하여 분석하는 기술적 분석 방법은 주식 시장 외적인 요소를 반영하는데 있어 한계점이 존재한다. 본 논문에서는 기술적 분석 방법에 기사를 종목별로 분류하고 기사의 긍정 및 부정을 판별하는 문서 분류 기법을 적용하여 주식 외적인 요소를 반영하는 시스템을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.335-338
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• 2012

유전 알고리즘 (Genetic Algorithm)은 기존의 알고리즘 개발방법을 통하여 해결하기 어려운 최적화 등의 문제를 해결하기 위한 자연계의 진화과정을 모방한 방법이다. 본 연구에서는 유전 알고리즘을 이용하여 KOSPI 200에서 거래되고 있는 증권의 매수/매도 종목을 추천하는 방법을 제시한다. 이를 위하여 기술적 분석 (Technical Analysis) 방법 중에서 Slow Stochastic 지표와 MACD 지표를 이용하여, 매일매일 두 지표가 나타내는 매매 신호를 기반으로 해당하는 각각의 종목에 대해 최근 가장 좋은 수익률을 나타내는 매수/매도 종목을 추천하는 방법을 구현한다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.207-217
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• 2010

It is taken a violent fall of the international stocks market that was an American Subprime Mortgage Situation. The loss rate of individual investor judged than foreigner and institution by bigger thing. Therefore, further scientific and mechanical investment is needed at the stock investment using Internet HTS. This dissertation is stocks profit rate analysis which uses individual engine foreigner Knowledge Base HTS at the Bear Period the Bear Wave Period the Bull Period the Bull Wave Period. Knowledge Based e-friend HTS was Installed. HTS does composite stock exchange index in actuality stock trading and engine's fund earning rate, yield that is abroad comparative analysis using trend line that is HTS tool, MACD, Bollinger Bands, Stochastic slow's function. Usually, each subjects suppose that deal 5 stocks, and comparative study of the profit(loss)rate of the down to earth falling rate and rising rate, by comparing the earning rate of 5 Small capital stocks with 5 medium capital stocks and 5 Large capital stocks during the bear period, the bear wave period, the bull period, the bull wave period has meaning at the making research of the financial IT field.

• The Journal of Information Systems
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• v.12 no.2
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• pp.1-20
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• 2003

This paper deals with the application of the genetic algorithm to the technical trading rule of the stock market. MACD(Moving Average Convergence & Divergence) and the Stochastic techniques are widely used technical trading rules in the financial markets. But, it is necessary to determine the parameters of these trading rules in order to use the trading rules. We use the genetic algorithm to obtain the appropriate values of the parameters. We use the daily KOSPI data of eight years during January 1995 and October 2002 as the experimental data. We divide the total experimental period into learning period and testing period. The genetic algorithm determines the values of parameters for the trading rules during the teaming period and we test the performance of the algorithm during the testing period with the determined parameters. Also, we compare the return of the genetic algorithm with the returns of buy-hold strategy and risk-free asset. From the experiment, we can see that the genetic algorithm outperforms the other strategies. Thus, we can conclude that genetic algorithm can be used successfully to the technical trading rule.