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The efficiency
and real-world success of a trading model is usually dependent on two
variables. The simplicity of the algorithm, the amount of trades
The efficiency
and real-world success of a trading model is usually dependent on two
variables. The simplicity of the algorithm, the amount of trades produced by
the algorithm and the amount of human adjustment. The aim is to generate the
highest IRR with the simplest method, the least amount of trades and without
the need to interfere and adjust for different trading environments. The simplicity is
a good predictor of future success because the more complicated an algorithm
the more likely that it is retrofitted to describe the past data and that it
will fail in future trials. The amount of trades generated is also important
due to the transaction costs. It is
probably possible to generate enormous theoretical returns with a complex
algorithm that executes 150 trades a day but after transaction costs are
factored in, the end result would be a disaster. Any backward testing of a
trading algorithm should also be without any human interference (such as
assertions that in reality an intelligent human would interfere in October
2008 and then give back the control to the algorithm in mid
2009) to test the long-term predictive power of the algorithm. Leveraged
Dividend Fund aims to execute one of three trading models developed by the
site owner. This model is based on exploiting the carry-trade between low
dollar borrowing costs and high dividend yielding stocks and closed end
funds. Also leverage and a hedging system is
implemented in the model to amplify returns and to avoid margin calls. The performance
of the model is presented in the graph to the left as well as the
performances of S&P100 Total Return, Bond Return and a
8% annualized return for comparison. The model has only two variables in the
algorithm therefore satisfies the simplicity
requirement. The algorithm is back-tested with no human interference or
adjustment and on that basis has produced an annual return of 32,6% with a
44,6% annual standard deviation compared to 2,0% annual return and a 19,1% annual standard deviation
for the S&P 100 Total Return Index. In executing the model for the Fund the model might be suppressed if there is an expected market movement that would interfere with the model. So while the back-testing results are completely without interference the performance of the Fund will be a combination of the algorithm’s success and the site administrator’s occasional choices to use the model or not. If the model is suppressed it will be noted in the comments section. |
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Since Inception Relative Performance Graph vs
DJIA and 7 -10 Year Bond Index Latest Trades
Comments Jan 18th' 12
15:28 The model is
still suppressed and I have not traded the Fund for a while. The market just
does not provide the correction that I expect that would make me comfortable
to accumulate shares according to the model. The long Treasury positions
remain. There will most likely be a comment here when the Fund starts
trading. However, I can't anticipate when we will get to levels more
accommodative to get into high yielder MREITS without taking too much risk. Dec 8th' 11
11:43 Just applied
the same long Treasury positions similar to other Funds to the Leveraged
Dividend Fund too. The Greek situation is not solved yet. I will not activate
the model until Greeks get their bailout. Dec 2nd' 11
11:04 The model
that underlies this Fund is usually independent of market conditions.
However, some high-yielding stocks are leveraged MREITs and these tend to be
sensitive to credit conditions. Any negative news from Greece and the
European situation might affect the US credit markets too and make some of
the components of this model crash. The model also gives much better results
when implied volatilities are low so I will suppress the model for a while
until Greek situation clears up. Then I should be able to initiate positions
when risks are much lower. Since
Inception Performance Chart vs Equity and Bond
Benchmarks
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Latest Trades
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