Same Same But Different

Investors sometimes become concerned when they observe discrepancies in the performance of seemingly identical strategies with identical expected long-term performance.

In this article, which is a summary of a more comprehensive whitepaper (download here), we hope to alleviate these concerns by showing that short-term discrepancies will almost always arise when the same strategy is executed on different channels, like SMAs, UMAs, or mutual funds. Moreover, these discrepancies can be quite large in the short term without compromising the long-term expectations of the strategy.

For example, we offer AAA mandates using both futures and ETFs for a given volatility target. While they provide very similar underlying market exposures in the long term, over the short-term small differences in the underlying constituents of the ETFs versus futures, will produce short-term deviations.

Differences in trading costs and turnover preferences for each delivery channel also prompt us to execute AAA at different rebalance frequencies, and on different days of the week. Again, while the long-term returns for these mandates are statistically indistinguishable, performance over shorter horizons like a few months or years can be quite distinct due simply to how often and when these portfolios are rebalanced.

Consider two strategies that have precisely the same methodology, executed on the exact same investment universe. However they are executed with different rebalance frequencies between 1 and 20 days, and on different days of the month.

The strategies have returns that are statistically indistinguishable from one another over 25 years. How different could short-term performance really be if all that stood between them was the portfolio’s rebalancing frequency?

Perhaps surprisingly, the average difference between the best and worst strategy simulation was 7.2% over any given year. The difference was larger than 10.9% five percent of the time. Even when the strategies were tracking closely, we still observed a 4.2% dispersion between the best and worst performer. Figure 1 shows a few of the years where merely changing the rebalancing frequency led to large dispersions.

Figure 1: Performance of best and worst performing strategy permutations in years with the largest dispersion. Simulated results.

Source: ReSolve Asset Management. Each chart represents the growth of $1 for the worst and best performing strategy permutation each the calendar year. Simulated and hypothetical data. Past performance is no guarantee of future results.

The moral of the story is that investors have to either buy into the underlying process or not. Short-term performance is just noise. Investors need to trust (or not) that the fundamental drivers of the methodology (momentum/trend factors and diversification) are likely to prevail in the long-term, even in the face of random dispersion in the short-term.

Of course, this doesn’t just apply to AAA. It is axiomatic across any investment approach. The performance of the S&P500 would have been materially different from year-to-year if it added or removed companies at different times. How different would the index have been if the index committee had added Apple, Microsoft, or Amazon just 6-months earlier or later?

The ability to ignore short-term noise and focus on long-term evidence is what separates the willing losers from the alpha harvesters.

Disclaimer

Confidential and proprietary information. The contents hereof may not be reproduced or disseminated without the express written permission of ReSolve Asset Management Inc. (“ReSolve”). ReSolve is registered as an investment fund manager in Ontario and Newfoundland and Labrador, and as a portfolio manager and exempt market dealer in Ontario, Alberta, British Columbia and Newfoundland and Labrador.
These materials do not purport to be exhaustive and although the particulars contained herein were obtained from sources ReSolve believes are reliable, ReSolve does not guarantee their accuracy or completeness. The contents hereof does not constitute an offer to sell or a solicitation of interest to purchase any securities or investment advisory services in any jurisdiction in which such offer or solicitation is not authorized.

Forward-Looking Information. The contents hereof may contain “forward-looking information” within the meaning of the Securities Act (Ontario) and equivalent legislation in other provinces and territories. Because such forward-looking information involves risks and uncertainties, actual performance results may differ materially from any expectations, projections or predictions made or implicated in such forward-looking information. Prospective investors are therefore cautioned not to place undue reliance on such forward-looking statements. In addition, in considering any prior performance information contained herein, prospective investors should bear in mind that past results are not necessarily indicative of future results, and there can be no assurance that results comparable to those discussed herein will be achieved. The contents hereof speaks as of the date hereof and neither ReSolve nor any affiliate or representative thereof assumes any obligation to provide subsequent revisions or updates to any historical or forward-looking information contained herein to reflect the occurrence of events and/or changes in circumstances after the date hereof.

General information regarding returns. Performance data prior to August, 2015 reflects the performance of accounts managed by Dundee Securities Ltd., which used the same investment decision makers, processes, objectives and strategies as ReSolve has used since it became registered and commenced operations in August, 2015. Records that document and support this past performance are available upon request. Performance is expressed in CAD, net of applicable management fees. Indicated returns of one year or more are annualized. Past performance is not indicative of future performance.

General information regarding the use of benchmarks. The indices listed have been selected for purposes of comparing performance with widely-known, broad-based benchmarks. Performance may or may not correlate to any of these indices and should not be considered as a proxy for any of these indices. The S&P/TSX Composite Index (Net TR) (“S&P TSX TR”) is the headline index and the principal broad market measure for the Canadian equity markets. The Standard & Poor’s 500 Composite Stock Price Index (“S&P 500”) is a capitalization-weighted index of 500 stocks intended to be a representative sample of leading companies in leading industries within the U.S. economy.

General information regarding hypothetical performance and simulated results. These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account or fund managed by ReSolve will or is likely to achieve profits or losses similar to those being shown. The results do not include other costs of managing a portfolio (such as custodial fees, legal, auditing, administrative or other professional fees). The contents hereof has not been reviewed or audited by an independent accountant or other independent testing firm. More detailed information regarding the manner in which the charts were calculated is available on request. Any actual fund or account that ReSolve manages will invest in different economic conditions, during periods with different volatility and in different securities than those incorporated in the hypothetical performance charts shown. There is no representation that any fund or account will perform as the hypothetical or other performance charts indicate.

General information regarding the simulation process. The systematic model used historical price data from Exchange Traded Funds (“ETFs”) representing the underlying asset classes in which it trades. Where ETF data was not available in earlier years, direct market data was used to create the trading signals. The hypothetical results shown are based on extensive models and calculations that are available for any potential investor to review before making a decision to invest.