ETF Momentum Signal
for June 2016 (Final)
Second Place ETF
Third Place ETF
|Gross Compound Annual Growth Rates
(Since August 2006)
|Top 1 ETF||Top 2 ETFs|
|Top 3 ETFs||SPY|
Last Updated: April 29, 2011 • Posted in Individual Gurus
Eddie Kwong of TradingMarkets.com requested a review of Larry Connors’ Daily Battle Plan (Battle Plan). TradingMarkets.com presents the Battle Plan service as “a reliable guide for short term traders looking to take advantage of the surge in interest in exchange-traded funds (ETFs) with “a record of more than 80% correct trades. …Larry and his research team developed this evidence-based trading to counter the spotty performance and glaring conflicts of interest that exist on Wall Street.” To enable a review, TradingMarkets.com made public a listing of all Battle Plan trades since mid-October 2008, which uses ETF closing prices on trade recommendation dates to calculate gross returns and gross win rate [since removed from public view]. Using the data for the 165 positions listed as of 4/21/11 for the period 10/14/08 through 4/20/11, we find that:
Note that this analysis treats each position in each ETF as a separate trade, whereas the list on TradingMarkets.com aggregates some positions described as (up to three) “units” of a single trade. The separate trade perspective is essential to assessment of portfolio-level performance below.
As a first step in evaluating Battle Plan, we estimate the round-trip trading friction for Battle Plan subscribers as 0.56% of trade value, derived from the following assumptions/data:
The following table presents some basic performance statistics for the available sample of trades based on these assumptions. Notable points are:
Note that including any costs of shorting would lower profitability for all categories except Long Trades. Sensitivity tests on trading frictions indicate that:
For another perspective on Battle Plan profitability trend, the following chart plots trade-by-trade gross profits over the available sample, along with a best-fit linear trend line. Results indicate a decline in profitability (but also volatility) over time, likely driven by market conditions. A possible interpretation is that the data set commences with market conditions that are favorable to the method of identifying trades.
What about portfolio-level returns?
Generally, portfolio-level analysis is important for capturing the interplay of trade-by-trade returns and return volatility, as well as the effect of allocation to cash while awaiting trade recommendations.
The following chart summarizes the number of open Battle Plan positions over the available sample period based on close-to-close trading, as presented (treating close-to-next close as one trading day). It appears that allocating one-third of capital to each position would catch most recommended trades (in large part because of the three-unit grouped trades), but would miss many trades during the first half of the sample. Assuming a limit of three positions and late entry to open recommendations as cash becomes available, a Battle Plan portfolio is:
Alternatively, a three-position portfolio that ignores all recommendations issued while fully invested can participate in 128 out of the 165 total recommendations. How would a Battle Plan portfolio based on this three-position limit perform?
The final chart summarizes the performance of a hypothetical Battle Plan portfolio with a three-position limit by plotting portfolio values at points when the portfolio is all in cash over the available sample period. Assumptions underlying portfolio performance are:
Under these assumptions, the combination of trading friction and return volatility generally more than offset average gross return per trade. The terminal value of the hypothetical Battle Plan portfolio at the close on 4/20/11 is $25,614. Setting trading friction to zero makes the terminal value $33,978.
Note that, while the return on cash is practically zero over the sample period, the portfolio owner cannot allocate capital elsewhere without the risk of missing new Battle Plan recommendations.
For reference, buying and holding SPDR S&P 500 (SPY) over the sample period provides a total (dividend-reinvested) return of about 40%.
In summary, evidence from several tests of available trade data does not support a belief that all investors can consistently generate good returns by implementing the recommendations of Larry Connors’ Daily Battle Plan.
Cautions regarding findings include:
Rough Net Worth Growth Benchmarks
June 17, 2016