• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.59-71
• /
• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Journal of Mechanical Science and Technology
• /
• v.15 no.5
• /
• pp.639-645
• /
• 2001

Experimental investigations were conducted to study forced convection of fully developed turbulent flows in horizontal equilateral triangular ducts with different surface roughness pitch ratios (P/e) of 4, 8, and 16 on one side. The ducts bottom wall was heated uniformly and the other surfaces were thermally insulated. To understand heat transfer enhancement mechanism, heat transfer rates were measured. Smooth triangular ducts were also tested for benchmark purposes. The results were compared with previous results for similarly configured channels, at which they were roughened by regularly spaced transverse ribs in the rectangular and circular channels.

• East Asian Economic Review
• /
• v.21 no.2
• /
• pp.147-165
• /
• 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.

• ETRI Journal
• /
• v.33 no.1
• /
• pp.39-49
• /
• 2011

A new structure learning approach for Bayesian networks based on asexual reproduction optimization (ARO) is proposed in this paper. ARO can be considered an evolutionary-based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter, the parent and its bud compete to survive according to a performance index obtained from the underlying objective function of the optimization problem: This leads to the fitter individual. The convergence measure of ARO is analyzed. The proposed method is applied to real-world and benchmark applications, while its effectiveness is demonstrated through computer simulations. Results of simulations show that ARO outperforms genetic algorithm (GA) because ARO results in a good structure and fast convergence rate in comparison with GA.

• Journal of Computing Science and Engineering
• /
• v.4 no.4
• /
• pp.276-290
• /
• 2010

The join operator is fundamental in relational database systems. Evaluating join queries on large tables is challenging because records need to be efficiently matched based on a given key. In this work, we analyze join queries in SQL with large tables in which a foreign key may be null, invalid or valid, given a referential integrity constraint. We conduct an extensive join performance evaluation on three DBMSs. Specifically, we study join queries varying table sizes, row size and key probabilistic distribution, inserting null, invalid or valid foreign key values. We also benchmark three well-known query optimizations: view materialization, secondary index and join reordering. Our experiments show certain optimizations perform well across DBMSs, whereas other optimizations depend on the DBMS architecture.

• Structural Engineering and Mechanics
• /
• v.46 no.2
• /
• pp.231-244
• /
• 2013

An efficient method is proposed here to identify multiple damage cases in structural systems using the concepts of flexibility matrix and strain energy of a structure. The flexibility matrix of the structure is accurately estimated from the first few mode shapes and natural frequencies. Then, the change of strain energy of a structural element, due to damage, evaluated by the columnar coefficients of the flexibility matrix is used to construct a damage indicator. This new indicator is named here as flexibility strain energy based index (FSEBI). In order to assess the performance of the proposed method for structural damage detection, two benchmark structures having a number of damage scenarios are considered. Numerical results demonstrate that the method can accurately locate the structural damage induced. It is also revealed that the magnitudes of the FSEBI depend on the damage severity.

• International Journal of High-Rise Buildings
• /
• v.3 no.3
• /
• pp.191-198
• /
• 2014

The tall building and super tall building has been a common building type in China, with multiple functions and complex geometry. Composite construction is broadly used in tall building structures and constitutes the mixed structure together with concrete and steel constructions. The mixture of the constructions is purposely designed for specific area based on the analysis results to achieve the best cost-effectiveness. New types of composite construction are conceived of by engineers for columns and walls. Material distribution is more flexible and innovative in the structural level and member level. However the reliability of computer model analysis should be verified carefully. Further researches in the design and build of composite construction are necessary to ensure the success of its application. Composite or Mixture Index is suggested to be used as a performance benchmark.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.21 no.5
• /
• pp.113-120
• /
• 2013

This paper presents a mathematical model to determine the optimal length of static messages that can achieve more efficient use of a FlexRay network. In order to determine the optimal length of static message, the proposed model evaluates the given set of messages with respect to a network utilization index, which is defined in this work. The efficient use of a FlexRay network is achieved by reallocating any static message whose length is equal or greater than the resulting value to the dynamic segment. The effectiveness of the proposed method is investigated by applying to the SAE benchmark data.

• Journal of Information Processing Systems
• /
• v.13 no.4
• /
• pp.863-875
• /
• 2017

The traditional text similarity measurement methods based on word frequency vector ignore the semantic relationships between words, which has become the obstacle to text similarity calculation, together with the high-dimensionality and sparsity of document vector. To address the problems, the improved singular value decomposition is used to reduce dimensionality and remove noises of the text representation model. The optimal number of singular values is analyzed and the semantic relevance between words can be calculated in constructed semantic space. An inverted index construction algorithm and the similarity definitions between vectors are proposed to calculate the similarity between two documents on the semantic level. The experimental results on benchmark corpus demonstrate that the proposed method promotes the evaluation metrics of F-measure.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.1248-1250
• /
• 2015

MySQL 데이터베이스에서 사용하는 Non-clustered Secondary Index는 디스크 접근 시 Random한 입출력을 유발하여 디스크 장치의 성능을 저하시키는 문제점을 가지고 있다. 이를 해결하기 위해 MySQL의 Storage Engine은 Insert Buffer를 사용하여 Random한 디스크 접근을 방지한다. Benchmark를 통해 성능 평가를 진행한 결과 Insert Buffer를 사용하는 것만으로 성능이 개선되는 것을 확인하였다. 또한, 현재의 Insert Buffer를 수정하여 더 큰 성능 향상을 이끌어낼 수 있는 부분을 발견하여 이에 대한 아이디어를 제시, 간단한 구현을 통해 추가적인 성능 향상을 보였다.