Ivy league Portfolio

Ivy league Portfolio| In my previous post I wrote that learning how to program your own automated trading system has substantial benefits. Once you get accustomed to coding your trading strategy you will start to notice how easy it is to pick up other programming languages. By learning how to code my own trading system, I have learned the programming language V.B.A,-Visual Basic for Applications, which definitely has been a plus for me. My love for Excel knows no bounds! It is an excellent program that can do anything you think of.

My only qualm is the graphics. Oh, the graphics!

 

So I decided to fire up excel and to do a comparison of the hedge fund strategies using a portfolio model that resembles the Ivy League endowments. The portfolio that I constructed is based on Mebane T. Faber and Eric W. Richardson book called “The Ivy Portfolio.” The Ivy Portfolio model which I used is somewhat similar to what is described in this excellent book. I used the major non correlated asset classes to replicate an Ivy League endowment:

  1. S&P 500
  2. FTSE-REIT
  3. MSCI-EAFE
  4. GSCI
  5. Ten Year Treasury T-Bonds

 

A simple buy and hold strategy was used for the simulation.  The portfolio was readjusted on a yearly basis to equally allocate funds to the proper asset classes. For the minimum acceptable return – which indicates the minimum rate of return that a project manager considers acceptable before initiating a project, I used an average return on the three month T-Bill from 1997 to 2011.


The total equity was readjusted from nominal returns- an unadjusted rate value, or change in value to an Inflation Adjusted Return – a measure of return that accounts for the return period’s inflation rate. I used the average CPI rate from 1997 to 2011 for the inflation adjusted total equity. It’s labeled as “real.” The simulation was back tested from 1997 to 2011 using $250,000 as starting equity.

 

Next, I took the position as if I were an institutional investor allocating 15% of an endowment to a hedge fund strategy. The other 85% is allocated equally to the major asset classes.  The results are in the table.  The hedge fund strategies data were all taken from Barclay hedge expect the systematic index which was taken from IASG.

Conclusion:

Just by looking at the table one can see that the systematic hedge fund strategy offers a higher return on capital with a lower standard deviation, which would indicate a tighter probability distribution, and a lower level of risk.

Glossary:

Downside Deviation – A measure of downside risk that focuses on returns that fall below a minimum threshold or minimum acceptable return (MAR).

Upside Deviation – This measures only deviations above a a minimum threshold or minimum acceptable return (MAR).

Sharpe Ratio – The Sharpe ratio tells us whether a portfolio’s returns are due to smart investment decisions or a result of excess risk.

Sortino Ratio – The Sortino ratio is similar to the Sharpe ratio, except it uses downside deviation for the denominator instead of standard deviation, the use of which doesn’t discriminate between up and down volatility.

 

Chad Grant

Author: admin

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