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An article appeared recently in the UK magazine "Investors
Chronicle" entitled "Useless Tools".
The gist of the article was that UK fund managers were doing a
pathetically bad job using their tools (valuations, company
analysis, business models, knowledge of management etc.) and were
all (except 3) beaten over each of the last 5 years by the
author's "Low-Risk Portfolio". This portfolio returned 86.5% (total)
over the past 5 years.
This low-risk portfolio was quoted as "...based on simple mean-
variance optimisation, in which the only inputs are the volatilities
and Betas of the share's quarterly returns since 1992..."
I sent the author an email asking for further details and his reply
is below. The question is, does anyone use this sort of analysis and
does Amibroker lend itself to the required calculations?
Steve
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
Hello. Thanks for your interest and kind words. I attach a brief
description of what I do, taken from the website.
To take this further, I'd recommend Modern Portfolio Theory and
Investment Analysis, by Edwin Elton and Martin Gruber, who describe
the process in detail.
It's a very interesting idea to apply this to US stocks.
One thing you'll almost certainly find is that historic (in-sample)
efficient portfolios vastly out-perform fund managers. My portfolio
shows that this is true out-of-sample too - though of course I've no
idea whether this will remain the case.
Best wishes
Chris
How we form the portfolio
At the start of every calendar quarter since 1998 I've asked a
simple question: what set of stocks in the FTSE 100 has had the
lowest possible volatility of quarterly returns since 1992? This set
has been our low-risk portfolio.
To see how stocks get into this portfolio, consider the equation
that tells us the variance of a portfolio. It is:
Variance = 1/N x (Average variance) + (N-1)/N x Average covariance
The low-risk portfolio is the one that minimizes this variance; to
find this, I use some software called the Investment Portfolio,
available from John Wiley & Sons.
It's clear from this equation that there are only two ways a
stock
can get into our portfolio; either it has a low variance, or it has
a low covariance with other stocks*.
Note that low volatility on its own is not enough to get into our
portfolio. Smiths Group has a lower variance than BAT. But it
doesn't get into our portfolio whereas BAT is a major holding
because it has a high covariance with other stocks whereas BAT
doesn't.
Conversely, low covariances with other stocks are not enough. Rio
Tinto has these, but it's quite volatile, so it's excluded.
Note also that equity risk can't be removed entirely. Even the
lowest possible risk portfolio still has a standard deviation of
almost half that of the market. This means that you can only remove
half of equity risk by diversifying among equities. To reduce risk
by more than this, you need other assets.
* Actually, I use implied covariances, obtained by multiplying
stocks' betas by the variance of the All-share index. There's
a
simple reason for doing this. Some pairs of stocks might have a
negative covariance in the past simply because of luck – as one
had
bad news at the same time as the other had good.
It would be imprudent to assume that such chance events will
continue into the future, so we shouldn't use such covariances to
measure risk.
Instead, we ask: what fundamental reason do we have to expect that
two stocks will move together? If you believe the capital asset
pricing model – which says that market risk is the only
systematic
factor that determines stock returns – the answer can only be
that
the two stocks are sensitive to moves in the market. If this is so,
we can estimate an implied covariance by multiplying their betas by
the variance in the All-share index.
The paradox here is that although the CAPM is clearly wrong as a
guide to asset pricing, it produces a portfolio that delivers great
risk-adjusted returns.
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