1. Equity Risk Sciences’ hypothetical backtested examples are provided as illustrative examples only and do not represent the performance of actual client portfolios.
  2. Hypothetical backtested performance results have many inherent limitations, some of which are described below.
  3. No representation is being made that any account will or is likely to achieve profits or losses similar to those discussed. In fact, there are frequently sharp differences between hypothetical backtested performance results and the actual performance results subsequently achieved by any particular trading program.
  4. The hypothetical backtested performance of our Enduring Portfolios™ is based on the following assumptions:
    1. The investable universe for the backtest includes over 17,000 US securities from all sectors with market capitalization during the stated time period of at least $500 million.
    2. The backtest presented may not include all the constituents of the aforementioned investable universe.
    3. The performance shown is for the stated time period only – namely, from 12/31/1999 to 12/31/2021.
    4. The investment strategy used by the backtested portfolio in this presentation buys and sells stocks based on ERS’s proprietary Risk Ratings. The portfolio holds up to 30 stocks at a time. ERS’s backtester identifies the 30 best-rated stocks on each day, then buys and sells stocks based on the changes in their ratings.
    5. Due to market volatility, each account’s performance may be different.
    6. The returns shown assume the reinvestment of dividends and other income.
    7. The returns assume a starting account size of $100,000.
    8. The returns do not include the deduction of any kind of fees, including management fees, and other brokerage expenses that may be incurred in managing a $100,000 investment account. No management fees are charged on the accounts.
    9. The returns do not take into account slippage which may be incurred when actual investments are made.
  5. The results of hypothetical backtests may be affected by certain biases in their methodology. Below is a partial list of some of these biases, along with the measures Equity Risk Sciences has taken to mitigate them, if any:
    1. Survivorship bias: Many stock data providers only offer data on current publicly-traded companies, excluding those companies which failed and were subsequently delisted. While ERS has acquired data on several thousand delisted companies, there are other delisted companies for which we do not have such data which could have affected the outcome of our backtests.
    2. Insufficient sample bias: In order to draw statistically significant conclusions, the sample size must be sufficiently large. Our 22-year backtest performs a total of 2,179 total trades. In addition, we also have our “Benchmark” study, which examines over 300,000 date-rating data pairings and demonstrates that, in aggregate, stocks with lower-risk ratings have outperformed stocks with higher-risk ratings.
    3. Look-ahead bias: Look ahead bias is the process where one calculates a result which is biased by the fact that one already has some degree of knowledge of events that will later come to pass, whether minuscule or significant. This is a common problem in historical studies, rendering some of these more or less useless.
      In order to avoid look-ahead bias, the human element needs to disappear from the equation. ERS accomplishes this by using a computer-based backtesting program, which accepts user inputs to set the intended buy rules, sell rules and other backtesting conditions prior to each test, but then only makes trade decisions based on those pre-set conditions without any further human input.
    4. Data-release timing bias: Some companies take longer than others to release their quarterly financial statements. As such, any trading action taken during a backtest which takes into account financial data which investors could not have known on the date of that action suffers from look-ahead bias.
      Under current law, public companies are required to file their quarterly statements within 45 days of quarter-end, or within 90 days of year-end. Equity Risk Sciences attempts to minimize the effects of look-ahead bias on its risk ratings and its hypothetical backtested portfolios by assuming, as a stand-in for knowing the exact dates, that all companies file their quarterly financial dates exactly 45 days after the end of their financial quarter or year, and only including such data in its backtests after those 45 days has passed. Some companies file their financial statements late or file their annual statements between 45 and 90 days after the end of their corporate year, which would give us a look-ahead advantage in decision-making. However, others file earlier than 45 days, in which case our backtests will be disadvantaged due to gaining access to that new information later than the real market. While it is impossible to predict how much these biases may influence our backtest results, we have taken steps to minimize that effect on our results.
    5. Temporal bias: Most models used in the financial worlds today exhibit what we call temporal bias. We are here referring to the fact that most data or data points in the financial world do have some form of temporal element associated with them.
      Consider the following example of temporal bias: A correlation between a company’s Market Cap and its Revenues may exist. But it will be of a temporary nature only; for example, as time passes, investors may decide that they are willing to pay a greater price for each dollar of revenues than before. Eventually, models which rely on assumptions made during one time period may fail when those assumptions are no longer true.
      ERS believes that its risk ratings are based on sound economic principles which will continue to bear fruit into the future. For example, over a long enough time horizon, companies with more cash and less debt will always be worth more than companies with less cash and more debt.
    6. Data-mining bias: When developing backtests, it is possible that one could mold or sculpt a method to “fit” the actual occurrences of financial history, as we know it.
      The principal way to avoid data-mining bias is to not search for what works. Proper science forms a thesis, which would logically work, and then ONLY test whether the thesis can be proven to work or not.
      Using this approach limits the risk of data-mining bias, as no “mining” takes place. Rather, the scientific method is used. The only changes to the formulation of ERS’s ratings occur when additional logic is applied to reflect additional measures of financial practices that affect the risk of a company. ERS does not change the derivation of the ratings based on the success or failure of our risk ratings in predicting future price movements.
    7. Market-impact bias: The act of trading a stock has an effect on that stock’s price; the more shares you trade, the larger that effect. Equity Risk Sciences’ backtests currently do not make any attempt to adjust its hypothetical backtest portfolios to account for the effects of its portfolios’ own trades.
    8. Optimal-period bias: There may be periods of time in which ERS’s models work better than they do in other periods of time. However, the backtest shown in our business plan spans 22 years and includes several periods of both market growth and market decline. We expect this will be sufficient to mitigate the possibility of optimal-period bias affecting the results. In addition, ERS has conducted other studies not included in the business plan which use different time periods but produce results which are similarly supportive of our risk ratings’ additive value when used to guide investment decision-making.
    9. Liquidity bias: ERS’s hypothetical backtests assume that they are able to make all stated trades on the date the system chooses the stocks to buy or sell, which ignores the possibility that there may not be enough volume traded to satisfy the portfolio’s requirements on that day.
  6. 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. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results.
  7. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical backtested performance results and all of which can adversely affect actual trading results.
  8. Our expected returns and expected volatility measures have been based on Equity Risk Sciences’ backtesting analysis. For the reasons noted above, there is no guarantee that actual returns will match our initial expectations regarding the fund’s returns or volatility measures. Expected returns will be modified based on actual experience.
  9. The information may contain projections or other forward-looking statements regarding future events, targets or expectations, and is only current as of the date indicated. No assurance can be given that the investment objective or target return will be achieved or that an investor will receive a return of all or part of his or her initial investment.
  10. The opinions and predictions expressed in this presentation represent the current, good faith views of Equity Risk Sciences, Inc. and are provided for limited purposes; they are not definitive investment advice. Predictions, opinions, and other information in this presentation are subject to change continually and without notice of any kind and may no longer be true after the date indicated.
  11. All investing involves risk, including the possible loss of money you invest. Graphs, charts, tools, and graphics are used for illustrative purposes only, and may not reflect actual future performance. The contents of this presentation are for informational purposes, and unless we have recommended this portfolio to you, it is not investment advice tailored for you.
  12. DISCLAIMER: THERE ARE NO WARRANTIES, EXPRESSED OR IMPLIED, AS TO ACCURACY, COMPLETENESS, OR RESULTS OBTAINED FROM ANY INFORMATION PROVIDED HEREIN OR ON THE MATERIAL PROVIDED. This document and the information which it accompanies or to which it refers and relates does not constitute a complete description of ERS’s investment services and is for informational purposes only. It is in no way a solicitation or an offer to sell securities or investment advisory services. Any statements regarding market or other financial information is obtained from sources which ERS and its suppliers believe to be reliable, but ERS does not warrant or guarantee the timeliness or accuracy of this information. Neither ERS’s information providers nor ERS shall be liable for any errors or inaccuracies, regardless of cause, or the lack of timeliness of, or for any delay or interruption in the transmission thereof to the user. All investments involve risk, including foreign currency exchange rates, political risks, market risk, different methods of accounting and financial reporting, and foreign taxes. Your use of these and all materials provided by ERS, including the equityrisksciences.com website is your acknowledgement that you have read and understood the full disclaimer as stated above.