A review of stock market prediction with Artificial neural network (ANN)
Stock market is a promising financial investment that can generate great wealth. However,
the volatile nature of the stock market makes it a very high risk investment. Thus, a lot of …
the volatile nature of the stock market makes it a very high risk investment. Thus, a lot of …
[HTML][HTML] Utilizing artificial neural networks and genetic algorithms to build an algo-trading model for intra-day foreign exchange speculation
Abstract The Foreign Exchange Market is the biggest and one of the most liquid markets in
the world. This market has always been one of the most challenging markets as far as short …
the world. This market has always been one of the most challenging markets as far as short …
[HTML][HTML] Optimization of Traditional Stock Market Strategies Using the LSTM Hybrid Approach
Investment decision-makers increasingly rely on modern digital technologies to enhance
their strategies in today's rapidly changing and complex market environment. This paper …
their strategies in today's rapidly changing and complex market environment. This paper …
A new method for predicting stock market crashes using classification and artificial neural networks
The stock market prediction is an interesting topic, especially for traders and investors. One
important aspect of predicting the stock market is identifying price patterns which may result …
important aspect of predicting the stock market is identifying price patterns which may result …
[HTML][HTML] Hybrid models combining technical and fractal analysis with ANN for short-term prediction of close values on the warsaw stock exchange
M Paluch, L Jackowska-Strumiłło - Applied Sciences, 2018 - mdpi.com
This paper presents new methods and models for forecasting stock prices and computing
hybrid models, combining analytical and neural approaches. First, technical and fractal …
hybrid models, combining analytical and neural approaches. First, technical and fractal …
[HTML][HTML] An improved probabilistic neural network model for directional prediction of a stock market index
Financial market prediction attracts immense interest among researchers nowadays due to
rapid increase in the investments of financial markets in the last few decades. The stock …
rapid increase in the investments of financial markets in the last few decades. The stock …
Discovery of trading points based on Bayesian modeling of trading rules
Mining hidden patterns with different technical indicators from the historical financial data
has been regarded as an efficient way to determine the trading decisions in the financial …
has been regarded as an efficient way to determine the trading decisions in the financial …
Modified neural network algorithms for predicting trading signals of stock market indices
The aim of this paper is to present modified neural network algorithms to predict whether it is
best to buy, hold, or sell shares (trading signals) of stock market indices. Most commonly …
best to buy, hold, or sell shares (trading signals) of stock market indices. Most commonly …
The influence of using fractal analysis in hybrid MLP model for short-term forecast of close prices on Warsaw Stock Exchange
M Paluch, L Jackowska-Strumiłło - 2014 Federated Conference …, 2014 - ieeexplore.ieee.org
The paper describes a new method of combining Artificial Neural Networks (ANN), technical
analysis and fractal analysis for predicting share prices on the Warsaw Stock Exchange. The …
analysis and fractal analysis for predicting share prices on the Warsaw Stock Exchange. The …
Determination of temporal stock investment styles via biclustering trading patterns
Due to the effects of many deterministic and stochastic factors, it has always been a
challenging goal to gain good profits from the stock market. Many methods based on …
challenging goal to gain good profits from the stock market. Many methods based on …