Predicting Stock Prices Using Polynomial Classifiers: The Case of Dubai Financial Market

Assaleh, Khaled; El-Baz, Hazim; Al-Salkhadi, Saeed Mohammed

doi:10.4236/jilsa.2011.32010

Cited by 5 publications

(5 citation statements)

References 23 publications

(23 reference statements)

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“…PC is the recommended learning algorithm for recognition with classification, regression and generalization capabilities. PCs require less calculation and have been used successfully for several applications of pattern recognition and signal detection problems, including speech and speaker recognition 124 …”

Section: Soft Computing Methodsmentioning

confidence: 99%

“…PCs require less calculation and have been used successfully for several applications of pattern recognition and signal detection problems, including speech and speaker recognition. 124 Since ANN needs to be tuned to determine parameters that require running the process several times, Al-Assaf and El Kadi 53 developed a new concept of PC to estimate the fatigue life of composite materials. They have compared the results of the proposed concept with feedforward and recurrent NNs.…”

Section: Polynomial Classifiersmentioning

confidence: 99%

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Soft computing methods for fatigue life estimation: A review of the current state and future trends

Kalaycı

Karagöz

Karakaş

2020

Fatigue Fract Eng Mat Struct

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Fatigue causes cracking or breakage in a material due to repeated loads; it causes the material to become unusable. Therefore, knowing the fatigue life of materials is crucial for the implementation of designs, economy and human life. Soft computing methodologies, a subset of artificial intelligence emerging to simulate human intelligence, deal with approximate models and seek solutions to complex real-life problems relying on both computational power of machines and the high accuracy of the algorithms. In this study, soft computing methods adapted for estimating/predicting the fatigue life of engineering structures and materials are investigated. For this purpose, 95 articles published between 1995 and 2020 have been examined in detail. With this review, it is aimed to reveal the efficiency of soft computing methods and contribute to their development. Recommendations have been made to draw attention to these methodologies which are expected to be used in many areas in the future.

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Section: Soft Computing Methodsmentioning

confidence: 99%

Section: Polynomial Classifiersmentioning

confidence: 99%

Soft computing methods for fatigue life estimation: A review of the current state and future trends

Kalaycı

Karagöz

Karakaş

2020

Fatigue Fract Eng Mat Struct

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“…China has experienced rapid development on stock index and commodity futures market in recent years, and various studies concerning on high frequency data to achieve profits are springing out, discussions of which range from arbitrage opportunity [1] to wave theory [2]. Accurate predictions of price movements in futures market will bring large profits in trading, which has become a challenging task for investors and a focus for academicians.…”

Section: Introductionmentioning

confidence: 99%

“…Quantitative methods and techniques have been widely applied to forecast price trend. The Polynomial Classifiers and back propagation feed forward neural networks models were conducted on Dubai Financial Market to forecast securities' prices movements [3]. Regression and Neural Network models are used for predicting Shanghai Composite Index returns and price volatility [4].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Intraday Trading Strategy Based on ACD Rules and Pivot Point System in Chinese Market

Tian¹,

Quan²,

Zhang³

et al. 2012

JILSA

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Various trading strategies are applied in intraday high-frequency market to provide investors with reference signals to be on the right side of market at the right time. In this paper, we apply a trading strategy based on the combination of ACD rules and pivot points system, which is first proposed by Mark B. Fisher, into Chinese market. This strategy has been used by millions of traders to achieve substantial profits in the last two decades, however, discussions concerning on the methods of calculating specific entry point in this trading strategy are rare, which is crucial to this strategy. We suggest an improvement to this popular strategy, providing the calculating and optimizing methods in detail to verify its effectiveness in recent Chinese futures market. Because of the high liquidity and low commissions in stock index futures market, this trading strategy achieves substantial profits .However, given the less liquidity in commodity futures market, profits decrease and even be neutralized by the relatively high commissions

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“…The results provided us with a good basis of assessing merits of stocks. Assaleh et al [4] predict stock price in the Dubai Financial Market from historical price data using the Polynomial Classifiers (PC) and Artificial Neural Networks (ANN). Qin Qin et al [5] use two different types of prediction models and multiple technical indicators to predict the Shanghai Composite Index returns and price volatility.…”

Section: Introductionmentioning

confidence: 99%

Clustering Analysis of Stocks of CSI 300 Index Based on Manifold Learning

Liu¹,

Cai²,

Luo³

2012

JILSA

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As an effective way in finding the underlying parameters of a high-dimension space, manifold learning is popular in nonlinear dimensionality reduction which makes high-dimensional data easily to be observed and analyzed. In this paper, Isomap, one of the most famous manifold learning algorithms, is applied to process closing prices of stocks of CSI 300 index from September 2009 to October 2011. Results indicate that Isomap algorithm not only reduces dimensionality of stock data successfully, but also classifies most stocks according to their trends efficiently

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Predicting Stock Prices Using Polynomial Classifiers: The Case of Dubai Financial Market

Abstract: ABSTRACT

Cited by 5 publications

References 23 publications

Soft computing methods for fatigue life estimation: A review of the current state and future trends

Soft computing methods for fatigue life estimation: A review of the current state and future trends

Optimization of Intraday Trading Strategy Based on ACD Rules and Pivot Point System in Chinese Market

Clustering Analysis of Stocks of CSI 300 Index Based on Manifold Learning

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