An introduction for S2Pro algo [focused on SOXL]

While I am not promoting my strategy, I am excited to share my in-depth research on decay loss for leveraged ETFs such as TQQQ, SQQQ, SOXL, SOXS, and others. In my manuscript, I cover all the key points of my study and understanding of these ETFs, with a particular focus on SOXL. The manuscript is available for free download on Google Drive, and I encourage you to take a look and use it as a resource.

As I can not include the download link here, I attached the abstract part in the following. Just email me if you need the .pdf document.

Abstract

Predicting whether the stock market will rise or fall is very difficult, but predicting market fluctuations is relatively easy. However, the ability to forecast volatility does not mean returns are guaranteed, because there isn’t a fixed relationship between them. In this paper, we propose a disruptive trading strategy, and design an algorithm using the basic model of severe decay loss of leveraged ETF in the volatile market, which makes the investment become more easily predictable. We will start with the basic theory of the significant decay loss problem of leveraged ETFs, and then explain the entire trading system and logic clearly according to the development and optimization timeline of the S2Pro series products. We will use data graphs instead of mathematical formulas to show the progression of S2Pro’s products in the past few decades including drawdown range, position control, stop loss, take profit points, annual earnings, and other related parameters. S2Pro series products are based on a strategy that abandons both the unilateral bullish and bearish market and instead focuses on the continuous accumulation of profits in the volatility market. In the past 20 years, the maximum annual return of S2Pro3, the most basic product of the S2Pro series, reached 300% (2008), and the minimum annual return was 1.2% (2016). Theoretically, the greater the volatility of the stock, the greater the return of the S2Pro series products, which has little correlation with the overall market’s return in the current year. The current cutting-edge version of the S2Pro series, S2Pro7, corresponds to a cumulative return of more than 200,000 times the principal amount when projected to market data from the past 22 years. Thanks to the powerful API trading algorithm provided by IBKR, the S2Pro series products have realized fully automatic quantitative trading, and the trading strategy is adjusted according to the closing price every day. This automatic trading strategy will liberate investors from the troublesome and tedious work of trading. Therefore, from the perspective of the investor, purchasing S2Pro products will be similar to investing in other ETFs. Furthermore, the mathematical formula behind the current S2Pro series (SOXX) can also be directly applied to ETFS such as SPY and QQQ, each yielding returns up to hundreds or thousands of times the principal amount. The investor can buy in at any time, at any position. After 2-3 weeks of fluctuation, the positions will converge to the real data of the S2Pro trading system. Lastly, we made a prediction: in view of our judgment that the volatility of the U.S. stock market in 2023 will still be significant, our trading strategy S2Pro7 can bring at least a 40% return in such a market regardless of general market fluctuations.

Looking forward to discuss with you guys about it.

Thanks,
S2Pro

Sounds very interesting. I sent you a message with my email address.

Sorry for that I forget to attached my email. jinwei6499@gmail.com
Please feel free to email me if you would like to read this manuscript. At least you will find a new probably profitable quant trading idea.

Thanks

Interesting - Please send a copy of your pdf to my e-mail address listed below:

rvjnuke@yahoo.com

FYI - I am looking at how markets evolve in response to shocks (i.e., GFC, 1987 Crash).
I suspect that changes in volatility regimes result from these shocks reflecting the market participants risk profiles.

Nuke