Quantitative investment Based on Artificial Neural Network Algorithm
نویسنده
چکیده
Abstract: Financial investment has become an important issue, there are many trading strategies and parameters based on quantitative models, this paper use neural network algorithm to optimization strategy parameters, various combinations of optimization strategies, as well as the evolution of new strategies to generate better returns. The empirical results show that this method has a stable and substantial return on investment, neural network can be used as an aid for decision making investments in securities. Financial investment has become an important issue, there are many trading strategies and parameters based on quantitative models, this paper use neural network algorithm to optimization strategy parameters, various combinations of optimization strategies, as well as the evolution of new strategies to generate better returns. The empirical results show that this method has a stable and substantial return on investment, neural network can be used as an aid for decision making investments in securities.
منابع مشابه
Appraisal of the evolutionary-based methodologies in generation of artificial earthquake time histories
Through the last three decades different seismological and engineering approaches for the generation of artificial earthquakes have been proposed. Selection of an appropriate method for the generation of applicable artificial earthquake accelerograms (AEAs) has been a challenging subject in the time history analysis of the structures in the case of the absence of sufficient recorded accelerogra...
متن کاملStructural Reliability: An Assessment Using a New and Efficient Two-Phase Method Based on Artificial Neural Network and a Harmony Search Algorithm
In this research, a two-phase algorithm based on the artificial neural network (ANN) and a harmony search (HS) algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. The proposed method involves the generation of datasets to be used specifically for training by Finite Element analysis, to establish an ANN model using a proven AN...
متن کاملDiagnosis of hyperlipidemia in patients based on an artificial neural network with pso algorithm
One of the most common and most dangerous diseases of blood fats are such as heart disease, diabetes and stroke, heart and brain. It can control the timely diagnosis, treatment and then prevention of complications is become very effective even without using medicine. Heart disease and diabetes file if patients has useful information that can be used to estimate blood fat timely diagnosis. In th...
متن کاملOptimization of Plastic Injection Molding Process by Combination of Artificial Neural Network and Genetic Algorithm
Injection molding is one of the most important and common plastic formation methods. Combination of modeling tools and optimization algorithms can be used in order to determine optimum process conditions for the injection molding of a special part. Because of the complication of the injection molding process and multiplicity of parameters and their interactive effects on one another, analytical...
متن کاملPredicting air pollution in Tehran: Genetic algorithm and back propagation neural network
Suspended particles have deleterious effects on human health and one of the reasons why Tehran is effected is its geographically location of air pollution. One of the most important ways to reduce air pollution is to predict the concentration of pollutants. This paper proposed a hybrid method to predict the air pollution in Tehran based on particulate matter less than 10 microns (PM10), and the...
متن کامل