E-resources
Peer reviewed
-
Ghotbi, Mahdieh; Zahedi, Morteza
Expert systems with applications, 06/2024, Volume: 244Journal Article
Investing in the stock market and Forex can be lucrative, but it is important to approach it with caution and a clear understanding of the risks involved. Predicting the direction of prices in financial markets is a complex task, and there is no guaranteed way to do it. One innovative approach that has been proposed involves using a combination of the kinetic energy formula and indicator signals to predict prices, besides another predictions using deep reinforcement learning (DRL). This approach has led to the development of the Trading Deep Q-Network algorithm (TDQN), which incorporates the kinetic energy of stocks/currencies as a condition rule. The proposed approach, TKDQN method, has shown promising results in terms of accuracy and profitability, outperforming previous versions based on several metrics.
Shelf entry
Permalink
- URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year | Impact factor | Edition | Category | Classification | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Select the library membership card:
If the library membership card is not in the list,
add a new one.
DRS, in which the journal is indexed
Database name | Field | Year |
---|
Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
---|
Source: Personal bibliographies
and: SICRIS
The material is available in full text. If you wish to order the material anyway, click the Continue button.