Pattern matching trading system based on the dynamic time warping algorithm
The futures market plays a significant role in hedging and speculating by investors. Although
various models and instruments are developed for real-time trading, it is difficult to realize …
various models and instruments are developed for real-time trading, it is difficult to realize …
Adaptive stock trading with dynamic asset allocation using reinforcement learning
Stock trading is an important decision-making problem that involves both stock selection and
asset management. Though many promising results have been reported for predicting …
asset management. Though many promising results have been reported for predicting …
Day trading profit maximization with multi-task learning and technical analysis
Stock price movements are claimed to be chaotic and unpredictable, and mainstream
theories of finance refute the possibility of realizing risk-free profit through predictive …
theories of finance refute the possibility of realizing risk-free profit through predictive …
Analyzing sensory data using non-linear preference learning with feature subset selection
The quality of food can be assessed from different points of view. In this paper, we deal with
those aspects that can be appreciated through sensory impressions. When we are aiming to …
those aspects that can be appreciated through sensory impressions. When we are aiming to …
How many reference patterns can improve profitability for real-time trading in futures market?
SJ Lee, KJ Oh, TY Kim - Expert Systems with Applications, 2012 - Elsevier
Investors in futures market used to employ trading system which depends on reference
pattern (template) to detect real-time buy or sell signal from the market. Indeed they prepare …
pattern (template) to detect real-time buy or sell signal from the market. Indeed they prepare …
Finding the optimal frequency for trade and development of system trading strategies in futures market using dynamic time warping
SJ Lee, KJ Oh - Journal of the Korean Data and Information …, 2011 - koreascience.kr
The aim of this study is to utilize system trading for making investment decisions and use
technical analysis and Dynamic Time Warping (DTW) to determine similar patterns in the …
technical analysis and Dynamic Time Warping (DTW) to determine similar patterns in the …
Dynamic asset allocation exploiting predictors in reinforcement learning framework
JW Lee, J Lee, BT Zhang - European Conference on Machine Learning, 2004 - Springer
Given the pattern-based multi-predictors of the stock price, we study a method of dynamic
asset allocation to maximize the trading performance. To optimize the proportion of asset to …
asset allocation to maximize the trading performance. To optimize the proportion of asset to …
[HTML][HTML] Clustering-inverse: A generalized model for pattern-based time series segmentation
Patterned-based time series segmentation (PTSS) is an important task for many time series
data mining applications. In this paper, according to the characteristics of PTSS, a …
data mining applications. In this paper, according to the characteristics of PTSS, a …
Dynamic asset allocation for stock trading optimized by evolutionary computation
J LEE, JW LEE, BT ZHANG - IEICE transactions on information …, 2005 - search.ieice.org
Effective trading with given pattern-based multi-predictors of stock price needs an intelligent
asset allocation strategy. In this paper, we study a method of dynamic asset allocation …
asset allocation strategy. In this paper, we study a method of dynamic asset allocation …
[PDF][PDF] 2 단계하이브리드주가예측모델: 공적분검정과인공신경망
오유진， 김유섭 - 정보처리학회논문지B, 제14-B 권, 2007 - scholar.archive.org
요 약본 논문에서는 주가예측의 정확도를 향상시키기 위하여 공적분 검정 (Cointegration
Tests) 과 인공 신경망 (Artificial Neural Networks) 을 사용한 2 단계 하이브리드 예측 모델을 …
Tests) 과 인공 신경망 (Artificial Neural Networks) 을 사용한 2 단계 하이브리드 예측 모델을 …