Swing Trader: ETFs for Growing Industries (TA)

This type of robot is designed for traders who want to trade a wide range of high-tech stocks and would like to have protection during a downtrend. For these purposes, we have chosen the following ETFs:
1. TQQQ - is a leveraged ETF that seeks daily returns, before fees and expenses, that are three times those of the Nasdaq 100 Index.
2. SOXL - is a leveraged ETF that seeks daily returns, before fees and expenses, that are three times those of the ICE Semiconductor Index.
3. LABU - is a leveraged ETF that seeks daily returns, before fees and expenses, that are three times those of the S&P Biotechnology Select Industry Index.
For protection during a downtrend, we use a pool of inverse ETFs – SQQQ, SOXS and LABD.
Every day, our Machine Learning algorithms analyze the situation of the market and make a decision on which ETFs to open a trade for. All algorithms are based on a proprietary combination of technical indicators with individually selected parameters. The AI selects the most suitable algorithm for each ticker, each market situation (uptrend, downtrend or sideways) and open trades.
The average trade duration is 14 hours, which allows our users to use their capital effectively and not get stuck in a trade for a long time. After entering the trade, the AI Robot places a fixed order "Take profit", the distance to which depends on the current market volatility. To exit a position, the robot uses 2 options: a fixed stop loss of 2-4% of the position opening price and a flexible trailing stop that allows you to save most of the profit if the market reverses.
The robot's trading results are shown without using a margin. For full trading statistics and an equity chart, click on the "show more" button on the robot page. In the tab “Open Trades”, a user can see how the AI Robot selects equities, enters, and exits in paper trades in real-time. 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 09.07.2022.