• Journal of applied mathematics & informatics
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• v.5 no.3
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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.

• Korean Security Journal
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• no.34
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• pp.313-336
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• 2013

The purpose of this study is to derive an optimal regression model for occurrences of major crimes on a security company's stock price through identifying precedence of the occurrences of major crimes on the security company's stock price, relationship between the occurrences of major crimes and the security company's stock price. Followings are the results of this study. First, the occurrences of murder crime, robbery crime, rape crime, theft crime move along the security company's monthly stock price simultaneously, and the occurrence of violence crime precedes 6 months to the security company's monthly stock price depending on the results of cross-correlation analysis of precedence of occurrences of major crimes, such as murder crime, robbery crime, rape crime, theft crime, violence crime on the security company's monthly stock price. Second, the explanation of the occurrences of robbery crime, rape crime, theft crime on the security company's monthly stock price is 61.7%($R^2$ = .617) excluding murder crime, violence crime depending on the results of multiple regression analysis(stepwise method) by putting the occurrences of major crimes, such as murder crime, robbery crime, rape crime, theft crime, violence crime into the security company's monthly stock price.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.275-283
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• 2016

Currently Internet and IT infrastructure of Korea has maintained the world's highest levels. But in another aspect, security incident, especially personal information breaches occur frequently. As personal information leakage happened, the companies will be negatively affected. And to prevent this, they have implemented to use a variety of security solutions from information security vendors. Therefore we set up hypotheses that the companies experienced personal information leakage as well as information security companies providing security solutions will be affected by the leakages. So this paper verify hypotheses about the impact of the value of information security companies, through analysing stock price fluctuation of the companies. We found that the stock price of information security companies has increased as personal information leakage happened. And differences according to leakage volumes and types of business are not statistically significant. But there are significant differences according to business classification of information security companies.

• Convergence Security Journal
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• v.15 no.3_2
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• pp.83-93
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• 2015

In this research, we used KOSPI, KOSDAQ and a stock price of Information Security related Company - S1, Ahnlab, Suprema, Raonscure and Igloosecurity. From August 2010 to July 2014, that is during 208 weeks(4 years), we had grasped index and stock price trend. Also we had attempted various Empirical analysis - Basic statistics of Security related Stock, Analysis of variance, Correlation analysis and Weekly Rate of Rise trends. The first purpose of this research is to see correlation between Security related Company and KOSPI, KOSDAQ. The second purpose of this research is to analyze whether stock items have investment value or not while watching features of flow of stock price per item. We expect possibility and merit of investment when we suppose Security industry's high potential to grow. It seems that Security related Company deserves to be invested. We expect investment for Security related Company that has high possibility of growing will create high yields compared to Market yields.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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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%.

• Proceedings of the KIEE Conference
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• 2006.07a
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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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• v.22 no.2
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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.

• Asia-Pacific Journal of Business
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• v.11 no.3
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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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• v.21 no.4
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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).