PURPOSE Minimal axial diameter (MIAD) in magnetic resonance imaging (MRI) was recognized as the most useful parameter in diagnosing lateral retropharyngeal lymph (LRPL) nodes in nasopharyngeal carcinoma (NPC). This study aims to explore the additional nodal parameters in MRI and positron emission tomography-computed tomography for increasing the prediction accuracy. MATERIALS AND METHODS A to...

The purpose of this empirical study is intended to investigate XCS (Extended Classifier System) based model with knowledge rules for dynamic TIPP (Time Invariant Portfolio Protection) policy. There are two XCS-based agents in the proposed model (MA-TIPP).One agent dynamically optimizes Multiple and Tolerance variables which are concerned as the important parameters of TIPP and recommend trading...

Moving averages and indicators derived from these are used to predict the future direction stocks will move. In manual algorithmic trading, moving play a decisive role in decision making. this study, new hybrid approach has been developed that can be as an alternative such SMA, WMA EMA literature. BIST30 Turkey, proposed method performs better than widely MACD, Stochastic RSI, commonly

This study empirically tested the feasibility of machine learning in trading strategies using technical indicators and news information as feature variables for learning. Six were adopted this study, including moving average (MA), convergence/divergence (MACD), relative strength index (RSI), stochastic oscillator (KD), on-balance volume (OBV), sentiment ratio (SR) developed via text mining. Sel...

The management of financial portfolios or funds constitutes a widely known problematic in financial markets which normally requires a rigorous analysis in order to select the most profitable assets. The presented paper proposes a new approach, based on Intelligent Computation, in particular genetic algorithms, which aims to manage a financial portfolio by using technical analysis indicators (EM...

The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) and Filter that gives buying and selling recommendations to investors. The algori...

The aim of this paper is to develop a trading system based on Support Vector Machines (SVM) in order to use it in the S&P500 index. The data covers the period between 03/01/2000 and 30/12/2011. The inputs of the SVM are different forecasting algorithms: Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Momentum, Bollinger Bands and the Chicago Board Options Exchange V...

The purpose of this paper is twofold. Firstly, to assess the merit of estimating probability density functions rather than level or classification estimations on a oneday-ahead forecasting task of the EUR/USD time series. This is implemented using a Gaussian mixture model neural network, benchmarking the results against standard forecasting models, namely a naïve model, a moving average converg...