Swing Trader, Long Only: Valuation & Efficiency Model for Energy Sector (FA)

This AI Robot is for traders who prefer to open long only positions and trade stocks of undervalued companies from energy sector with good efficiency ratios. The maximum number of simultaneously open positions is limited to 30 and the average trading duration is 17 days, which makes following the signals of this robot simple and affordable for beginner traders.

The algorithm of the robot is based on the classic method of assessing the fair value of a company using a deep analysis of its book value and improved with the help of a business efficiency model developed by our team of analysts. In addition, the robot uses a pool of technical analysis methods to find optimal exit points to limit losses in a timely manner and maximize profits.

Every day, our mathematical power analyzes thousands of stocks traded on the US market and looks for undervalued stocks of companies from energy sector with high business quality. As soon as a suitable stock is found, the robot generates a buy signal. The robot opens only long positions, as our backtests have shown that stocks correctly selected using fundamental analysis demonstrate high stability even during a downtrend. After opening a trade, the robot places a fixed stop of 15% of the entry price of the position to prevent large losses in the event of a sharp change in market conditions. Also, the robot sets an additional trailing stop based on a unique combination of technical indicators that allow time for a trend reversal and exit the trade.

The robot's trading results are shown without using a margin. For a full trading statistics and equity chart, click on the "show more" button on the robot page. In the tab “Open Trades”, a user can see live how the AI Robot selects equities, enters, and exits in paper trades. In the tab “Closed trades”, a user can review all previous trades made by the AI Robot.

Disclaimer. The presented paper traded results (annualized returns, % wins/loss, and other statistics) are achieved by the application of the backtested and forward tested models. The past backtested and forward tested performance should not be taken as an indication or guarantee of future performance, and no representation or warranty, expressed or implied is made regarding future performance. Forward testing started on 02.16.2023.