- Dow Jones Newswires
- March 10, 2011
Pimco founder and co-chief investment officer Bill Gross. Source: Bloomberg
BOND king Bill Gross has unloaded all US government-related holdings, which include Treasuries, in the world's biggest bond fund.
The move reinforced Mr Gross's stance as a major Treasury bond bear.
He has fretted about the US fiscal deficits in recent months, saying that a 30-year bull run in the Treasury market was over.
Mr Gross, founder and co-chief investment officer of Pacific Investment Management Co, slashed such holdings to zero by the end of February from 12 per cent in January in the $US236.93 billion ($235bn) Total Return Fund (PTTRX), said a person on the company's fund-statistics information line today.
Cash was the new flavour for Mr Gross as he boosted holdings of cash and its equivalent to 23 per cent from 5 per cent in January in the fund. The holdings of mortgage-backed securities -- the biggest sector in the fund -- were reduced to 34 per cent from 42 per cent.
The Federal Reserve's $US600bn bond-buying program, which is expected to phase out later this year, has kept yields "artificially low" in the Fed's effort to drive money into riskier assets, like stocks, Mr Gross said earlier this month in a March investment outlook on Pimco's website.
US-government-related holdings in the Total Return Fund included nominal Treasuries, Treasury Inflation-Protected Securities, agency bonds and Treasury futures and options.
But yields may be too low, perhaps by 150 basis points, to attract new buyers of US government debt when the Fed's bond purchases end, Mr Gross wrote.
A successful transition from public- to private-sector credit creation has yet to be accomplished, he wrote, adding that current low yields could hinder that handoff.
A successful transition from public- to private-sector credit creation has yet to be accomplished, he wrote, adding that current low yields could hinder that handoff.
Pimco --a unit of Allianz -- is one of the world's biggest asset-management firms with more than $US1 trillion of assets under management.
Mr Gross and other fund managers at Pimco have said in recent months that a recovering economy dents demand for safe-haven assets. Over the longer term, the US's fiscal problems would also weigh on Treasuries and even exert downward pressure on the value of the US dollar as the country relies heavily on foreign money to fund its trade and budget shortfalls, they said.
The Total Return Fund has handed investors a return of 0.8 per cent this year through Tuesday, outperforming the benchmark index -- the Barclays Capital US Aggregate Bond Index which broke even, according to data from fund tracker Morningstar.
Over the past three years, the fund has handed investors a return of 8.61 per cent, beating the return of 5.64 per cent from the benchmark.
Here is a chart showing GDX is still on an ATR buy signal....
Thank you to Shaza for the research
The 2-ATR stop level is somehow an arbitrary choice and I wanted to check whether this bore an impact on the test results.
Note how the diversification and rebalancing over several ATR-multiple stop levels have a substantial impact on the Max Drawdown and volatility.
Here is a chart showing GDX is still on an ATR buy signal....
Trend Following, “Monkey Style”
A while ago, I used a quote from Winton manager and trend Follower David Harding (found in this interview) saying:
If you put in stops and run your profits and trade randomly you make money; and if you put in targets and no stops, and you trade randomly you lose money. So the old saw about cutting losses and running profits has some truth to it.
The quote was used to illustrate a post stating that a large driver of Trend Following returns is based on the mechanics of those systems (“cut your losses short, let your winners run“) which therefore benefit from the right tail of market return distributions – which are “fatter” than the usually assumed normal distribution – and avoid the left tail.
“Trade randomly”? Like the proverbial dart-throwing monkey? It seems so…
In effect, Harding is saying that entry points do not matter so much: a random entry coupled with a smart exit strategy would make money.
In effect, Harding is saying that entry points do not matter so much: a random entry coupled with a smart exit strategy would make money.
RANDOM TRADING TO THE TEST
I once met with a fund manager, who described his strategy as very similar to that random system in the Harding quote. What was really important to them was the position sizing for each new signal, as well as the exit strategy. The entry signal direction was “irrelevant”.
I found this puzzling at the time and have been wanting to test this idea since then, to verify whether a “random trading” system could indeed be profitable.
The system tested here is composed of random entries with additional “classic” components: a volatility-based fixed fractional money management and volatility-based trailing stop exits.
- The system first “tosses a coin” to decide whether to go long or short the market.
- An initial stop is set below/above the entry price at a distance equal to a fixed multiple of the volatility measure.
- That entry-stop distance is used to calculate the position size, so that the risk per trade (amount lost if trade gets stopped out) is equal to the fixed percentage of account equity.
- Every day, the trailing stop is adjused so that it is never further than the fixed multiple of the volatility measure. The stop always gets closer to the market and never gets adjusted further away from the market (i.e. if the market turns back toward the stop, the stop level does not change).
- When the position hits the trailing stop level, it gets closed and a new position is open. The direction of that new position is again determined by a new coin-toss.
TEST PARAMETERS AND RESULTS
For this test, I used fairly standard parameter values:
- Volatility Measure: 39-day (exponential) ATR
- Stop Distance: 2 ATR
- Risk per Trade: 1% of Account Equity
The portfolio used for this test is a subset of the one used in the State of Trend Following report, basically all those instruments that I have data for going back to the start of the test: in January 1990 (click for the exact list).
Since this is a random experiment, I generated multiple test outputs (200), all based on the same parameters, and averaged their monthly returns to create a composite equity curve, which performance summary statistics can be seen below:
| Performance Stats | |
|---|---|
| CAGR | 18.11% |
| Max DD | 33.57% |
| MAR | 0.54 |
| Monthly Std Dev | 6.34% |
| Average Monthly Rtn | 1.59% |
The 2-ATR stop level is somehow an arbitrary choice and I wanted to check whether this bore an impact on the test results.
I ran a further test, stepping the ATR-multiple for stop calculation from 2 to 10. Each ATR-multiple set was run 200 times again and averaged to give a composite equity curve.
Normalizing these 9 composite equity curves (for equal monthly standard deviation) and averaging them produced a “super-composite” equity curve composed of 2000 random tests (equally split between ATR-multiples ranging from 2 to 10).
Normalizing these 9 composite equity curves (for equal monthly standard deviation) and averaging them produced a “super-composite” equity curve composed of 2000 random tests (equally split between ATR-multiples ranging from 2 to 10).
The performance summary statistics of this “super-random-composite” equity curve are below:
| Performance Stats | |
|---|---|
| CAGR | 16.46% |
| Max DD | 21.87% |
| MAR | 0.75 |
| Monthly Std Dev | 5.67% |
| Average Monthly Rtn | 1.44% |
Note how the diversification and rebalancing over several ATR-multiple stop levels have a substantial impact on the Max Drawdown and volatility.
Both equity curves are charted below:
All in all, not too bad for “monkey-style” trading! It goes to show that signal entries, which most beginning traders/system developers focus so much on, are not so important after all…
Credits/Additional Reading: The concept of random entries with trailing stops has actually been discussed before. It seems like it was introduced by Van Tharp in his Trade your Way to Financial Freedom book, and mentioned on this article by Chuck Le Beau, where he expands on the concept of “Chandelier Exit” (name for volatility-based trailing stops).
Thanks and credits also to user “sluggo” on the Trading Blox forum, who published a similar study four years ago, and some code which I reused most of for this study. Note that his study found an opposite result, showing a turn in profitability (downwards) of random systems after 1997 (portfolio and parameter values are different though), so you might want to run your own test to verify this concept for yourself…
Credits/Additional Reading: The concept of random entries with trailing stops has actually been discussed before. It seems like it was introduced by Van Tharp in his Trade your Way to Financial Freedom book, and mentioned on this article by Chuck Le Beau, where he expands on the concept of “Chandelier Exit” (name for volatility-based trailing stops).
Thanks and credits also to user “sluggo” on the Trading Blox forum, who published a similar study four years ago, and some code which I reused most of for this study. Note that his study found an opposite result, showing a turn in profitability (downwards) of random systems after 1997 (portfolio and parameter values are different though), so you might want to run your own test to verify this concept for yourself…