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Last week we posted the 2009 year end performance for the Bloodhound model funds and showed:
• that none of them returned less than 50% and
• that the average return was 71.9% for the year.
This week the results for the US equity mutual funds were published in the NY Times:
• 11 general stock funds and 10 specialized stock funds did better than our average
• only one beat our best performer at 119.9%!
Congratulations to the 21 that did so well; of course, that left 5,750 funds that didn’t do as well.
Another fluke return for Bloodhound? Look at the 5 year returns (it’s not so easy for any of us to produce good returns with 2008 in the mix!):
• Of the 21 funds the 5 year return averaged 2.98% (range from -4.82% to 13.49%)
• Bloodhound’s model funds averaged 15.0% (range from 2.7% to 35.5%)
If, for example, you had invested $100,000 for 5 years:
• 2.98% would have earned you $15,815
• With 15% you would have earned $101,136!
With Bloodhound you can see 23 years of history for each of our model funds. We don’t think the performance is a fluke!
Build your own fund, or use one of ours, no fees other than your subscription, at http://www.bloodhoundsystem.com.
Bloodhound’s systematic investment model removes the need for market timing; there is a reason; you can’t do it and win! With Bloodhound you set the rules and then relax and follow them; read the blog on our year end 2009 results to see how well that has worked for 23 years.
We aren’t the only people who balieve that. Read the following article on the Fidelity web site, reproduced from Money magazine.
https://news.fidelity.com/news/news.jhtml?articleid=201001060442CNN_____MONEYMAG_-2010-01-05-pf-funds-market_timing_moneymag-index_htm&IMG=N&cat=default
Bloodhound builds personalized funds based on consistent investment rules; when we started the company we showed how they would have performed using 23 years of point-in-time data. In the wake of 2008 we entered the market to meet a good deal of skepticism; potential users were concerned that results based on historical analysis would be unrepeatable in the new, uncertain future, and that safety would be found in market timing, and not the buy and hold, low intervention trading reflected in the model funds that we demonstrated.
With a year of operation behind us, the results show a different story; here is the investment performance since January 1 2009 for the eleven model funds that Bloodhound provides as user guides; they can be modified or used as they are. Some highlights:
• None of the funds had a return of less than 50% in 2009 (the SP500 total return index was up 26%).
• The average return of a 20 stock portfolio in each of the model funds was over 70%.
• The lowest of the eleven funds returned 50%, the highest 105%.
• Five out of eleven funds are above their 1/1/2008 levels (the SP500 index is still down 21%).
• In 23 years, the average fund has made money in 19.5 years compared to 16 for the SP index.
• Ten of the eleven strategies are buy and hold for 12 months at a time, no market timing, no stock picking, you pick the strategy and the strategy selects the stocks and tells you when to trade. The performance shown is based on stocks that were purchased January 1st.2009.
The table shows the fund name with its average investment performance over 23 years since our data began in 1987; the number of those years in which the fund had a positive return; the value today of a single $100,000 investment in 1987 inclusive of trading costs, but exclusive of the Bloodhound subscription and taxes; 2009 return year to date; the change in the last month and the performance since 1/1/2008.
From any model, a user can create their own, current fund portfolio based on the latest financial and technical information in less than a minute. The results shown are for an investment of $100,000 using a portfolio of 20 stocks; the numbers have been tested at investment levels down to $10,000 and the results do not change significantly; 10 stock portfolios tend to outperform larger portfolios. Our analysis shows that the results are substantially independent of the time of year when the fund is started.
Bloodhound’s results have weathered storms! The investment environment reflected in the last 23 years included Black Monday (the worst one-day Dow fall in history), two major wars, 9/11, and two bear markets in which the SP500 index fell 50%. We believe that if the future is no worse, the model funds provide an excellent opportunity to put a modest amount of money away for a substantial long term reward.
We provide the support that will help you get started, and our current users range from housewives to hedge fund managers. For the sophisticated investor, Bloodhound provides 23 years of financial data, charting, the ability to build and test investment strategies using Fundamental, Technical and Custom functions and to select strategies to examine and modify from the database of 170,000 that we have tested.
The blog “How can I try Bloodhound” shows you how, in just three steps, you can set up your own real or tracking portfolio based on any fund in the Bloodhound library in just 4 keystrokes.
Updated year to date return on investment of the Bloodhound model strategies as at December 1st.
Highlights:
……. a better month, three strategies down for the month, but the average up 0.9% to an average of 60% year to date.
……. every one has recorded a higher % gain than its loss in 2008; 4 have gained in value since Jan 1 2008 (remember that a 30% loss in one year requires a 43% gain to recover its value in the following year)
…… 3 have gained over 75% year to date
…… the minimum return on investment is 36.7% compared to the SP500 gain of 17.6% (the much higher gains often quoted for the SP are measured from March 9th, from January 1 it is 17.6%!)
…… 11 out of 12 are one year buy and hold strategies
The table shows the model strategy name with its average investment performance over 23 years since our data began in 1987; the number of those years in which the strategy had a positive return; the value today of a single $100,000 investment in 1987 inclusive of trading costs, but exclusive of the Bloodhound subscription and taxes; 2009 return year to date; and the change in the last month.
The figures are for portfolios of 20 stocks and were based on an investment of $100,000. Bloodhound lets you test changes in these parameters; for example a portfolio of 10 stocks invested in Lion has averaged 57% over the 23 years compared to 47%; a $10,000 investment in Lion with a portfolio of 10 stocks has averaged 55.5% compared to 57%.
All of the strategies shown, with the exception of “Website” are 12 month buy and hold. Users usually make a single investment each year until Bloodhound issues the annual portfolio revision. No market timing, no stock picking; you let the strategy run and Bloodhound tells you if and what to trade.
Bloodhound provides you with the ability to build, find and test strategies that have high gain, low volatility, or to pursue other goals. The model strategies, with consistent high gain, few years in which they lost, and a buy and hold investment model provide an opportunity to put a modest amount of money away for accumulation over a period with little maintenance.
The blog “How can I try Bloodhound” shows you how, in just three steps, you can set up a real or tracking portfolio based on these strategies in just 4 keystrokes.
Because Bloodhound runs its investment strategies starting on January 1st. we are often asked whether the performance of the strategy would be maintained if you started, or added to, a fund at another time of the year. We have recently been able to analyze this effect and illustrate it below with Lion, a high performing and therefore probably more volatile strategy. Here are the results.
This chart shows the average return one year after investment, as a function of the day of the year the investment was made; there are 252 days in the year, and since we have 23 years of data, there are 23 different results for each day. We also show the standard deviation of the returns.
The blue line shows the return, and you can see is that there appears to be a variation between a 41% and 59% return, with the end of March and the last three months of the year generally offering somewhat higher returns. BUT, if you look at the standard deviation line, it shows that there is higher variability at those periods, so it is not at all certain that the apparent trend is statistically significant!
The second chart also shows the return based on investment on different days of the year, but this time, the lines represent the average return after investments of different periods than the one year that we showed above. They cover 3 months to 5 years. Note that the returns for periods longer than 1 year, are annualized, where those for less than a year are not, which is why they are lower.
What you can see is that the longer the period after investment, the less it seems to depend on the day you invested. Our conclusion is that the day you invest in a strategy does not seem to be a signifcant factor in its performance.
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