The decomposition-based vector autoregressive model (DVAR) provides a new framework for scrutinizing the efficiency of technical analysis in forecasting stock returns. However, its relationships with other technical indicators still remain unknown. This paper investigates the relationships of DVAR model with the Japanese Candlestick indicators using simulations, theoretical explanations and emp...

This paper is devoted to research the validity of options strategies with a particular emphasis on weekly options. The author proves that options, when traded successfully, could be better substitute than buying or selling underlying and good given volatility strategy well capitalised stocks give superb results. analysed simple using moving average bollinger bands US market. Then new capital al...

This paper describes recent development and test implementation of a continuous time recurrent neural network that has been configured to predict rates of change in securities. It presents outcomes in the context of popular technical analysis indicators and highlights the potential impact of continuous predictive capability on securities market trading operations.

We point out the need for CSCL community to reach large scale validation for its results by addressing the lack of sharing of interaction indicators and data. The main goal of the Mulce project is a definition for teaching and learning corpora (especially for interaction tracks), a technical format to organize data and a platform for corpus sharing, providing analysis and visualization tools.

The Internet of things (IoT) has had an enormous impact on the financial industry. With IoT, people can obtain real-time information; moreover, investment and management have become more flexible diverse. Because their high returns strong liquidity, stocks essential commodities through which invest manage money. However, are often associated with risks. Therefore, it is important for investors ...