Shannon buy the dip and sell the rally experiment

The Constant-Proportion Rebalanced S&P 500 ETF Portfolio Experiment

Or in normal folks language The Shannon buy the dip and sell the rally experiment..

Claude Shannon is one of the super investors most people have never heard of.

Shannon was a brilliant and creative thinker. He solved real-world problems.

Shannon’s work had an impact on information theory, mathematics, engineering and computer science.

Sadly when he had solved a problem he also lost interest (especially in his later life) and moved on to the next problem without often writing down or sharing how he had solved the problem.

Still his accomplishments are many.

Author William Poundstone wrote extensively about Claude Shannon in his brilliant book; Fortune’s Formula. Good book by the way.

Have you bought the book yet?

Claude Shannon was one of the efficient market mob’s worst nightmares. He never published something on his investment methods. Shannon’s ideas, though very profitable in practice, never met his standards of originality and precision. Also by the time he trusted his investment process Claude was of an age that he hardly published anything.

Shannon and his wife Betty made a lot of money in the stock market. They had been investing for about 35 years together when they got interviewed by Philip Hershberg in 1986.

The first few years they paid their stock market college fees. In this learning period they did considerable trading and made moderate profits.

After switching to long-term holdings of stocks with products they liked, the annual portfolio return became close to around 28% a year.

Warren Buffett (another super investor) made an annual return of around 27% in Berkshire Hathaway between 1965 and 1995.

In the sixties he began holding regular meetings at MIT on the subject of scientific investing. Shannon described a way to make money off a random walk in one of those meetings.

That method is the topic of this real money experiment and blog.

Standard finance theory makes the assumption that volatility in the stock market always equals risk. This is completely nuts of course. Sometimes volatility equals risk in the stock market and sometimes it equals opportunity. As always in the stock market it depends. People want golden rules and assumptions that work all the time. Sadly that is not how the stock market operates.

Shannon proposed a constant-proportion rebalanced experiment at MIT where you shift assets at every rebalance to maintain the original 50-50 proportions of stock and cash. The experiment is contrarian by default. The stock market goes down and the experiment puts more cash into the stock market. When the stock market goes up the method sells some stock market exposure and puts the proceeds into cash. The constant-proportion portfolio buys the dip and sells the rally.

Shannon got asked;

“Did you use this system?”

“Naw”, said Shannon. “The commissions would kill you”.

Remember this was in the sixties and the seventies.

Commission rates and taxes were way higher back then.

Stock market commissions in this century are on a race to zero and for some investors in the US stocks have already reached zero.

Nevertheless commissions and taxes cut into the benefits of this system.

Shannon’s stock scheme harvests volatility.

Obviously when a stock has a high enough mean return, the Kelly-optimal trader would commit all his assets to this stock. The rebalancing scheme is then moot.

In normal folks language if you would know in advance a stock would guaranteed go up twice as much as say the S&P 500 index you would fill your boots with this stock and never sell any.

Obviously there are no guarantees in the stock market and nobody can know anything for sure and up front.

All we can do is place our bets and buy and hope for the best.

So therefore Shannon buy the dip and sell the rally experiment could well work as a way to beat the S&P 500 index these days. That is what the experiment will try to find out.

This will be a real money experiment. Luckily some brokers now pay some kind of interest on cash. Dividends income and interest payments on cash will be taken out of the portfolio. The experimental portfolio needs to beat the S&P 500 ETF by at least 2% annually to confirm the hypothesis. Obviously the experimental portfolio will have less volatility than a 100% S&P 500 ETF portfolio since at the start 50% of the Shannon portfolio will be in cash.

In a way benchmarking the experiment versus the S&P 500 ETF doesn’t make a lot of sense. The target is first of all to make money. The bigger target is to make money after correcting the returns for inflation. The overall target is to make money adjusted for inflation and taxes. The S&P 500 ETF benchmark is merely nice to have as a comparison.

Above; first buy order for the experiment.

So the real money portfolio is £4992 in the iUSA ETF listed in London in £ now and the £5008 is in cash.

That makes a total of £10000 exactly.

The buy order had a commission of £5.99! The commission drag wasted 12 bps.

To benchmark the £10000 portfolio on the sigfig website the £10000 needs to be first theoretically converted into dollars.

Above; £10000 equals about $12718 at the moment.

Above: snapshot of the VOO ETF price.

As the VOO ETF trades around 409.76 the benchmark can make a paper trade of 31 shares of the VOO ETF.

That paper buy order had a dollar value of $12703.

That leaves 12718-12703 or $15 which is put into cash in the benchmarked portfolio.

Above; VOO ETF holding put in the benchmarking website sigfig.com.

The translation of £ into $ slightly complicates this experiment which is a shame.

The experiment invests in an S&P 500 ETF.

Therefore the portfolio is unlikely to go to zero.

If one would do this experiment with a single stock the risk would be that the stock would go all the way to zero and wipe out the portfolio.

Considering the S&P 500 is somewhat diversified the risk of the S&P 500 ETF going to zero is a lot smaller.

A useful way of thinking about this is that if the S&P 500 goes to zero we probably have a lot bigger problems (like a nuclear war).

Doing this experiment with a highly volatile asset or stock would probably spice up the returns but it also would dial up the risk involved.

It will take more than 3 years before skill will outpace luck so this needs to be a multiyear experiment. Rebalancing will be done once every quarter in order not to get killed by commissions and taxes.

May the force be with the Shannon buy the dip and sell the rally experiment!

This blog is not advice on what you should do with your money and was written for information and entertainment purposes only. When you invest in the stock markets it is possible to lose money. Please do your own research. If in any doubt what is best in your individual situation, please hire a licensed financial advisor. Good luck on your investment journey.

Holland Park Capital London hopes you enjoyed the information in the blog. Holland Park Capital London Ltd is not receiving any compensation from anyone to write this blog. Holland Park Capital London is long most of the stocks in the S&P 500 index and is also long the S&P 500 index ETF. Holland Park Capital London has no business relationship with any company whose stock is mentioned in this blog. Holland Park Capital London expressed its own opinions. This is not advice. Make your own decisions please. Please go and see an authorized financial advisor before making any investment decisions. What works for Holland Park Capital London may well not work for you and your personal situation is unknown to Holland Park Capital London. Stocks go up as well as down and you may get back less than you invest. Any information in this blog should be considered general information and not relied on as a formal investment recommendation. This blog is for information purposes only and helps Holland Park Capital London expand on the book “Beat the Stock Market Casino” (available on Amazon) and brings extra discipline in the investment process. Holland Park Capital London is not liable for any mistakes in this blog. This blog cannot be a substitute for comprehensive investment analysis. Any analysis presented in this blog is illustrative in nature, limited in scope, based on an incomplete set of information and has limitations to its accuracy. The information upon which this blog is based was obtained from sources believed to be reliable, but has not been independently verified. Therefore the accuracy cannot be guaranteed. Any opinions are as of the date of publication and are subject to change without notice.