• Journal of applied mathematics & informatics
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• 제5권3호
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• pp.805-810
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• 1998

In this paper we set the stock price model in security market when the price process is a continuous semartingale and find a unigue solution of price process model.

• 시큐리티연구
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• 제34호
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• pp.313-336
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• 2013

본 연구는 주요범죄 발생의 경비업체 주가에 대한 선행성, 주요범죄 발생과 경비업체 주가 간의 관계를 규명하여 주요범죄 발생의 경비업체 주가에 대한 최적 회귀모형을 도출하는데 그 목적이 있다. 이와 같은 연구의 목적에 따른 연구결과는 다음과 같다. 첫째, 주요범죄 발생 건수의 경비업체 월말 주가에 대한 선행성을 분석한 교차상관 결과, 살인범죄, 강도범죄, 강간범죄, 절도범죄 발생 건수는 경비업체 월말 주가와 동행(同行)하며, 폭력범죄 발생 건수는 경비업체 월말 주가에 대하여 6개월 선행(先行)한다. 주요범죄 발생 증감률의 경비업체 주가 증감률에 대한 선행성을 분석한 교차상관 결과, 살인범죄 발생 증감률은 경비업체 주가 증감률과 동행(同行)하며, 강도범죄, 강간범죄, 절도범죄, 폭력범죄 발생 증감률은 경비업체 주가 증감률에 대하여 유의하지 않은 것으로 나타났다. 둘째, 주요범죄 발생 건수의 경비업체 월말 주가에 대한 중다회귀모형(stepwise 방식)을 도출한 결과, 살인범죄, 폭력범죄 발생 건수가 제외되고 결정계수($R^2$)가 .617로 주요범죄 발생 건수가 경비업체 월말 주가에 미치는 영향을 61.7% 설명할 수 있는 것으로 나타났다. 주요범죄 발생 증감률의 경비업체 주가 증감률에 대한 중다회귀모형(stepwise 방식)을 도출한 결과, 강도범죄, 강간범죄, 절도범죄, 폭력범죄 발생 증감률이 제외되고 결정계수($R^2$)가 .040으로 주요범죄 발생 증감률이 경비업체 주가 증감률에 미치는 영향을 4.0% 설명할 수 있는 것으로 나타났다.

• 산업경영시스템학회지
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• 제37권4호
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• pp.202-211
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• 2014

Pairs trading is a type of arbitrage investment strategy that buys an underpriced security and simultaneously sells an overpriced security. Since the 1980s, investors have recognized pairs trading as a promising arbitrage strategy that pursues absolute returns rather than relative profits. Thus, individual and institutional traders, as well as hedge fund traders in the financial markets, have an interest in developing a pairs trading strategy. This study proposes pairs trading rules (PTRs) created from a price ratio between securities (i.e., stock index futures) using rough set analysis. The price ratio involves calculating the closing price of one security and dividing it by the closing price of another security and generating Buy or Sell signals according to whether the ratio is increasing or decreasing. In this empirical study, we generate PTRs through rough set analysis applied to various technical indicators derived from the price ratio between KOSPI 200 and S&P 500 index futures. The proposed trading rules for pairs trading indicate high profits in the futures market.

• 정보보호학회논문지
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• 제26권1호
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• pp.275-283
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• 2016

현재 우리나라의 인터넷과 IT 인프라는 세계 최고 수준을 유지하고 있다. 그러나 그 이면에는 보안사고, 특히 개인정보 유출 사고가 빈번히 발생하고 있다. 개인정보 유출 사고 발생 시 해당 기업은 부정적 영향을 받게 되며, 이를 방지하기 위해 정보보호 업체의 다양한 보안 솔루션을 사용하고 있다. 따라서 개인정보 유출 사고 발생 시 발생 기업은 물론 기업에 보안 솔루션을 제공하는 정보보호 업체에도 영향을 미칠 것으로 생각된다. 이에 본 논문에서는 개인정보 유출 사고 발생 시 정보보호 업체의 주가 변화를 통해 보안 이벤트가 정보보호 업체의 가치에 어떠한 영향을 주는지 가설을 세워 검증하였다. 그 결과 개인정보 유출 사고 발생 시 정보보호 업체의 주가는 상승하였으며, 사고 규모, 사고 발생 업종에 따른 차이는 통계적으로 유의하지 않았고, 정보보호 업체의 업태 구분에 따른 차이가 존재하였다.

• 융합보안논문지
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• 제15권3_2호
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• pp.83-93
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• 2015

본 연구에서는 종합주가지수와 코스닥지수 그리고 융합보안 관련기업인 에스원, 안랩, 슈프리마, 라온시큐어, 이글루시큐리티의 주가를 이용하였다. 지난 2010년 8월에서 2014년 7월까지 총 4년(208주) 동안 지수 및 주가 동향을 파악하였다. 또한 보안 관련주의 기초통계량과, 분산분석, 상관분석, 각 주별 상승률동향 등 다양한 실증 분석을 시도하였다. 본 연구의 목적은 보안관련 기업들과 종합주가지수, 코스닥지수와의 상관관계를 살펴보는데 있다. 또한 각 기업들 주가흐름의 특징들을 파악하면서 투자가치가 있는지 분석하는데 있다. 향후 지식융합보안 산업의 높은 성장 가능성을 보았을 때 보안 관련기업들의 투자 가능성과 투자 메리트에 기대를 걸어보았다. 향후 성장 가능성이 높은 보안 관련기업에 대한 투자는 시장수익률 대비 높은 수익률을 보일 것으로 기대가 된다.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.166-171
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• 2023

The Stock price analysis is an increasing concern in a financial time series. The purpose of the study is to analyze the price parameters of date, high, low, and news feed about the stock exchange price. Long short term memory (LSTM) is a cutting-edge technology used for predicting the data based on time series. LSTM performs well in executing large sequence of data. This paper presents the Long Short Term Memory Model has used to analyze the stock price ranges of 10 days and 20 days by exponential moving average. The proposed approach gives better performance using technical indicators of stock price with an accuracy of 82.6% and cross entropy of 71%.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.359-360
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• 2006

This paper introduces a variable of methodology and models of solving Security-Constrained Price-Based Unit Commitment(SPUC) Problems in the Deregulated Power Market. The objective of SPUC is coordination between GENCOs and the ISO. GENCOs apply Price-Based Unit Commitment(PBUC) without security constraints and submit capacity bids to the ISO for maximizing their revenues. Using generation data and transmission data obtained from TRANSCOs, the ISO applies Security-Constrained Unit Commitment(SCUC), executes congestion management and contingency analysis for minimizing line flow violations and the risk supplying loads. Considering analysis data, the ISO should adjust GENCOS' bid. In this paper, we presents the result of survey and analyze on the approach of the SPUC problem.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.185-192
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• 2022

Forecasting and time series modelling plays a vital role in the data analysis process. Time Series is widely used in analytics & data science. Forecasting stock prices is a popular and important topic in financial and academic studies. A stock market is an unregulated place for forecasting due to the absence of essential rules for estimating or predicting a stock price in the stock market. Therefore, predicting stock prices is a time-series problem and challenging. Machine learning has many methods and applications instrumental in implementing stock price forecasting, such as technical analysis, fundamental analysis, time series analysis, statistical analysis. This paper will discuss implementing the stock price, forecasting, and research using prophet and LSTM models. This process and task are very complex and involve uncertainty. Although the stock price never is predicted due to its ambiguous field, this paper aims to apply the concept of forecasting and data analysis to predict stocks.

• 아태비즈니스연구
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• 제11권3호
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• pp.243-260
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• 2020

Purpose - This paper aims to investigate the properties of crude oil based derivative security (DLS) focusing on step-down type for comprehensive understanding of its risk. Design/methodology/approach - Kernel estimation is conducted to figure out statistical feature of the process of oil price. We simulate oil price paths based on kernel estimation results and derive probabilities of hitting the barrier and early redemption. Findings - The amount of issuance for crude oil based DLS is relatively low when base prices are below $40 while it is high when base prices are around $60 or $100, which is not consistent with kernel estimation results showing that oil futures prices tend to revert toward $46.14 and the mean-reverting speed is faster as oil price is lower. The analysis based on simulated oil price paths reveals that probability of early redemption is below 50% for DLS with high base prices and the ratio of the probability of early redemption to the probability of hitting barrier is remarkably low compared to the case for DLS with low base prices, as the chance of early redemption is deferred. Research implications or Originality - Empirical results imply that the level of the base price is a crucial factor of the risk for DLS, thus introducing a time-varying knock-in barrier, which is similar to adjust the base price, merits consideration to enhance protection for DLS investors.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.65-74
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• 2021

The rapid change in gold price is an issue of concern in the global economy and financial markets. Gold has been used as a means for trading and transaction around the world for long period of time and it plays an integral role in monetary, business, commercial and financial activities. More importantly, it is used as economic measure for the global economy and will continue to play an important economic vital role - both locally and globally. There has been an explosive growth in demand for efficient and effective scheme to predict gold price due its volatility and fluctuation. Hence, there is need for the development of gold price prediction scheme to assist and support investors, marketers, and financial institutions in making effective economic and monetary decisions. This paper primarily proposed an intelligent based system for predicting and characterizing the gold market trend. The simulation result shows that the proposed intelligent gold price scheme has been able to predict the gold price with high accuracy and precision, and ultimately it has significantly reduced the prediction error when compared to baseline neural network (NN).