Q-Rank Performance
The Facts – Independent and Profitable
The Quantitative Stock Research rating system is the only research system
on the Internet that we know of today with a track-record published continuous
for nearly 2 decades. Rabbitt Analytics’ performance has been continuously
published every month since June 1992. Rabbitt Analytics analyzes approximately
the largest 2,500 stocks in the US every day.
Fifteen Years
Since its inception the Rabbitt Analytics Q-Stock Research System annual
published returns are as follows: Strong Buys (Q-rated 90-99) 18.5 percent,
Out-Performers (Q-rated 70-79) 10.7 percent, Underperformers (Q-rated
10-29) 2.7 percent, and Strong Sells (Q-rated 0-9)-2.1 percent. The S&P
500 returned 4.9 percent per year during this period (monthly rebalancing,
commissions and slippage excluded).
Five Years
In the last five-years the average strong buy returned 7.8 percent while
the S&P500 returned -3.8 percent per year (see table below – read
the row called “Five Year Trailing-Annualized”). The following
charts show the cumulative performance of the Q-Stock Rank system.
Three Years
The Q-Stock Research Rating System has done a superb job of identifying
high-risk stocks during the difficult market of the past three years.
During the recent three years the Q-Stock Research Rating Strong Buys
returned -2.5 percent, the S&P500 returned -9.8 percent annually,
and the Q-Stock Research Strong Sells returned -19.2 percent (see table
below – read the row called “Three Year Trailing-Annualized”).
One Year
There's an old saying, “all ships go out with the tide”. During
the past one-year, there have been no safe havens in US stocks. While
the queue stock research system failed to deliver out-performance, the
Rabbitt analytics newsletter consistently warned our clients. Not
to use the system, and rather to keep the strong stop-loss discipline,
high cash levels, and positions and bear ETF’s.
.
What Can We Learn
The Rabbitt Analytics "Strong Buy" Group's performance
(90-99 Q-Rank) has far exceeded the other groups' performances
(see the bar on the far-right side of the graph above).
The performance "edge" of the Q-Rank system is
best for the top group (Q-Stock Research Rating rated 90-99)
and does equally well identifying the stocks that will
do "worst" in the future. Stocks rated 0-9 are
the stocks that should either be avoided or possibly shorted.
Therefore, extreme ranks make it easier to draw conclusions.
For our complimentary report on selling short email us
at info@rabbittanalytics.com and request our article on
short selling.
The following chart gives the annual performance of the
Strong Buys (Q-Stock Research Rating 90-99), the S&P
500, and the Strong Sells (Q-Stock Research Rating 0-9)
in each calendar year for the past decade (since 1992):
The Rabbitt Analytics record is based on the average performance
of a portfolio basket of the stocks grouped according to
its Quantitative Stock Research rating and divided into
ten Q-Research rating deciles.
Past performance is no guarantee of future results.
Since July 1992, a hypothetical $1 dollar invested in
the top decile (Q-Stock Research Rating 90-99) became $167
(see above). The same $1 dollar invested in S&P 500
became $12.50 and a $1 dollar invested in the Q-Stock Research
strong sells became $.30.
How the Performance is Calculated
he entire 2500 stock universe is divided into ten groups
(deciles) based on their Q-Stock Research rating. The performance
of each Q-Research group is the average performance of
all stocks in the group regardless of market capitalization.
Dividends are not included in performance. The performance
of each Q-Research group could have been achieved only
if equal-dollar investments were made in all stocks in
that group on the day the stocks were rated, held for one
month, then sold off and that amount reinvested in the
subsequent month's stock recommendations for that group.
The monthly rebalancing assumed in the performance calculation
is used to calculate the performance of a large body of
stocks and may be impractical in real life, given transaction
costs.
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