Performance Disclosure - Consilience AI

We are very proud of the results seen from using our unique system of capturing and quantifying relative risks across companies. We are also committed to the concept of transparency and so endeavor to provide as clear an explanation as possible for our proof statements, without giving away any of our proprietary processes or calculations. Questions or comments can be forwarded to contact@alphaiq.ai

MODEL PORTFOLIOS	2023	2022	2021	CUMULATIVE
SPINDEX RISK UP (BAD)	13.5%	-48.2%	1.7%	-40.2%
SP500	23.0%	-19.6%	24.8%	23.4%
R3000	22.7%	-20.7%	22.4%	19.1%

METHODOLOGY

SPINDEX RISK UP (BAD) portfolio reflects the returns of a hypothetical portfolio consisting of equal weighted stocks that met the following requirements:

Had an increase of 30 points in terms of SPINDEX Total Overall Risk Score over the prior year.
This considered all companies in the Syntax Universe
The portfolios were reviewed and rebalanced quarterly.

EXPLANATION

The purpose of this data is to provide evidentiary statements that historically, over the time frames shown, our SPINDEX RISK SCORING SYSTEM has shown an ability to help identify poor performing companies. By selecting companies with an increasing SPINDEX OVERALL RISK SCORE, an investor would have had a greater probability of underperforming the S&P500 and the Russell 3000 over 3 years. By selecting companies with a decreasing SPINDEX OVERALL RISK SCORE, an investor would have had a greater probability of outperforming the S&P500 and the Russell 3000 over 3 years.
*PAST PERFORMANCE MAY NOT BE INDICATIVE OF FUTURE RESULTS.

Quarterly Rebalancing

For each stock that had an annual increase/decrease of 30 points in terms of the SPINDEX OVERALL RISK SCORE, the total return during the quarter was calculated as the % change in the price of the stock from the closing price of the stock 13 weeks prior to the closing price of the current period, excluding any dividends received during the month. The performance of those stocks was then averaged to get to annual returns and averaged again to determine cumulative results over 3 years.

These returns are not achievable with actual portfolios.

These returns are higher than the returns an investor could achieve investing real money in a portfolio of because the returns exclude a number of costs, including commissions incurred for trading, the average bid ask spread, and the price impact of the trading, as well as costs associated with accessing this portfolio data.

Universe of Companies

The universe remained consistent across the period of review and includes all companies within the SYNTAX Universe of companies, and scored using our SPINDEX Scoring System Enterprise Version. However, the underlying companies may have changed across the time period.

Comparable Returns

The S&P 500 (SP500) & Russell 3000 (R3000) is an unmanaged index and returns are available publicly. The Syntax Universe is unmanaged but not available publicly. It is based on the top 3000 publicly traded companies filtered based on size and liquidity.

Stock trading/investing involves risks and you can lose some or all of your investment. Hypothetical or back-tested results may not always be duplicated in the real world. Back-testing can at times produce an unintended look-ahead bias. Results can also at times be over or understated due to the exclusion of inactive companies. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading, not the least of which is the ability to withstand losses or to adhere to a particular trading strategy in spite of trading losses. These are material points which can also adversely affect actual trading results.

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Consilience.Ai embraces complexity, intersecting math, AI, and language for revolutionary insights in Science, Finance and Technology. Connect with us today to learn what Consilience.Ai can do for you!