|as of October 31, 2016||Manager (net of fees )||S&P 500|
|as of October 31, 2016||Manager (net of fees )||S&P 500|
|Value-at-risk (95%, 1 week)||-6.7%||-7.2%|
|vs. S&P 500|
Limitations of hypothetical back-tested results
You have opted to view hypothetical back-tested results for this portfolio. These hypothetical back-tested returns are NOT actual results based on actual trading of real client funds for any time periods before November 01, 2016. These hypothetical back-tested results are not based on nor bear any relation to the actual performance of any Covestor client portfolio. Covestor does not make any representation that any client will or is likely to achieve results similar to the hypothetical results presented here. No Covestor client actually attained these hypothetical results. These hypothetical back-tested results are not an indicator of the future returns a client will realize by investing in this portfolio. Actual results in a Covestor client account employing this strategy could differ significantly from these back-tested hypothetical results depending on factors such as: broad stock market performance, factor returns, available liquidity, interest rates, economic growth, transaction costs, and other market factors.
HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS, SOME OF WHICH ARE DESCRIBED BELOW. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS SUBSEQUENTLY ACHIEVED BY ANY PARTICULAR TRADING PROGRAM. ONE OF THE LIMITATIONS OF HYPOTHETICAL PERFORMANCE RESULTS IS THAT THEY ARE GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. 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. 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 PERFORMANCE RESULTS ALL OF WHICH CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS.
Covestor has provided back-tested hypothetical results for this portfolio for informational and educational purposes only.
This portfolio was launched on Covestor on November 01, 2016. Any return information about this portfolio pertaining to any time periods before November 01, 2016 is based on hypothetical back-tested results. Hypothetical back-tested results and related risk metrics are calculated and presented separately from performance and risk metrics based on trading of actual funds.
There is an important distinction between the method used to calculate hypothetical and actual returns for this portfolio. Hypothetical back-tested returns before November 01, 2016 are calculated on a month-end basis with this monthly series of hypothetical returns then used as basis for calculating the various risk and return metrics presented. (See detailed discussion of the calculation of hypothetical returns in the section below, Covestor's back-testing calculation methodology and assumptions). This is different from the returns based on actual trading of this portfolio starting on November 01, 2016 which are calculated daily, as for all the other portfolios on the Covestor platform. Consequently, the month-end calculation of hypothetical back-tested results for this portfolio may limit their comparability to the daily calculation of actual returns.
Limitations of back-testing generally
Back-testing uses historical data to test the viability of a particular investment strategy, and attempts to indicate how a product constructed with the benefit of hindsight would have performed during a certain period in the past if the product had been in existence during that time. Specifically, back-tested results are hypothetical and do not reflect actual trading or the effect of material economic and market factors on the investment process, and back-testing does not place any client money at risk.
Based on criteria applied retroactively with the benefit of hindsight and knowledge of factors that may have positively affected the results of the portfolio, back-tested results cannot account for all financial risk or other market factors that may affect the actual performance of this portfolio.
Since trades have not actually been executed, results may have under- or over-compensated for the impact, if any, of certain market factors, such as the effect of limited trading liquidity, and may not reflect the impact that certain economic or market factors may have had on the investment process. Further, back-testing carries the additional risk that the security selection and portfolio construction processes have been overfitted or adjusted to maximize past hypothetical returns in order to present the investment strategy in a favorable light. Actual performance in a client account could thus differ significantly from back-tested performance.
Covestor's back-testing calculation methodology and assumptions
These hypothetical back-tested results reflect the deduction of advisory fees, brokerage or other commissions and other expenses that a Covestor client would have to pay if he invested in this portfolio after the launch date.
Both for purposes of actual trading and for purposes of calculating these hypothetical back-tested results, this portfolio only invests in securities that trade on a US stock exchange. Options, futures, commodities, derivatives, leverage and shorting are not used in this portfolio.
Covestor calculated these hypothetical back-tested results by retroactively applying a model designed on the basis of historical data with the benefit of hindsight, and based on assumptions integral to the model, which may or may not be testable and are subject to losses. Covestor tested various fundamental factors with the goal of delivering systematic exposure to different risk premiums available. Covestor constructed this portfolio by selecting securities with attractive fundamental characteristics. Covestor's analysis involved creating and systematically rebalancing quarterly a hypothetical portfolio to test the quantitative validity of the factor-based strategy. This model used historical price and fundamental metric data going back to April 30, 1999. When data for a security became unavailable because, for instance, a stock stopped trading for any reason, e.g., bankruptcy, merger or acquisition, or the trading data for the stock was unavailable for an open position, Covestor assumed the security was closed at the last monthly price. Hypothetical trading activity took into account brokerage commissions, other transaction fees and an estimation of spread cost for each security.
To calculate these hypothetical returns, Covestor started with a hypothetical investment amount of $5,000. Using historical fundamental data supplied by Thomson Reuters WorldScope database (described here: https://www.rimes.com/data/thomson-reuters-worldscope/), Covestor then ran its investment process as if it had been investing in and trading the portfolio starting on April 30, 1999. Covestor then calculated the number of shares to hypothetically trade in each security selected, and the commissions and other associated transaction costs.
For purposes of this calculation, Covestor used a modified version of Interactive Brokers LLC’s standard tiered commission structure, which we believe facilitates efficient investing and is also applicable to actual trading in this portfolio. Under this structure, IB charges $0.0035 per share in commissions based on the whole “basket” of securities in a client’s Smart Beta investment rather than on each security. Generally, IB charges a minimum commission for the basket of all securities orders in a client account equal to the lower of $5 or 0.05% of trade value, if more than the standard tiered commissions charge of $0.0035 per aggregated shares in the client basket. Interactive Brokers commissions are capped at 0.5% of the value of the basket trade.
To provide a more conservative estimate of the price at which Covestor could have bought or sold a security in the past, during the time periods covered by the hypothetical back-tested returns, Covestor used recent data of the bid-ask spread for each security to calculate a more realistic trading price. This generally led to a higher price for purchases and a lower price for sales, thus providing a more conservative, realistic estimate of the trade price used to calculate hypothetical back-tested returns.
Covestor calculated these hypothetical returns on a monthly basis. At the end of each month, Covestor used the price of each position multiplied by the units of each position to calculate the value of the portfolio. Covestor rebalanced the portfolio quarterly by calculating its new target portfolio allocations and generating the trades required by calculating the difference between the new and old position. This process was then continued for each period until Covestor reached the end of the period covered by the hypothetical back-test.
Covestor calculated the return for each monthly period as the difference in portfolio value over the period. For example, if:
Covestor then used this time series of monthly returns to derive the hypothetical returns and risk metrics presented for the entire time period covered by the back-test. These hypothetical returns and risk metrics are static in nature, calculated once and will not change or update in the future unless the applicable advisory fees or brokerage commissions increase at which time Covestor will recalculate the hypothetical back-tested returns based on those revised advisory fees and/or commissions.
The model Covestor used to calculate these hypothetical back-tested returns assumes that the markets were sufficiently liquid to execute trades in the US equity market, subject to the above referenced recent bid-ask spread data for each security used to calculate a more realistic trading price that Covestor could have achieved. The model also assumes no external cash flows into the portfolio (i.e., investments into or withdrawals from the portfolio). These hypothetical back-tested results also reflect an estimate of dividends based on a weighted average of dividend yield for all positions held during each period. Namely, Covestor used an end-of-quarter dividend yield value for each stock in the portfolio and aggregated all those dividend yield values across the portfolio based on security weight. Covestor then divided the quarterly value by three to calculate a monthly value used in the return calculation.
Covestor makes no representations and warranties as to the reasonableness of any of these assumptions.
Covestor does not guarantee that there will be sufficient liquidity to implement this model or that the model will work and attain results similar to these hypothetical or positive results. Investing in this portfolio presents the potential for loss as well as for profit.
Covestor makes no guarantees as to accuracy of data underlying these back-tested results
While Covestor believes that the data used to calculate the hypothetical results on this page was obtained from reliable sources, in generating the hypothetical charts and results for this portfolio Covestor used historical market data which has not been audited and validated, and may contain errors in pricing or other conditions. Covestor exclusively relied on data compiled by a third-party (i.e., the Thomson Reuters Worldscope database) for market data and information as the basis for these hypothetical return calculations, and cannot be responsible for the accuracy of this data.
Month to date
Quarter to date
Year to date
Quarterly vs S&P500
|as of March 28, 2017||Manager (net of fees )||S&P 500|
|Last 365 Days||-||15.8%|
This portfolio is new to the Covestor platform and does not have 365 days worth of daily performance data required for us to calculate risk metrics.