July 11, 2019

In a Quantopian forum, someone cited a Will Rogers quote as a putdown to the fact I was suggesting people buy stocks that are going up and drop those that are going down. This old Will Rogers quote goes like this:

Don't gamble; take all your savings and buy some good stock and hold it till it goes up, then sell it. If it don't go up, don't buy it.

To which I replied.

Will Rogers was right. It was and still is excellent advice. I used that same quote on my website years ago, but I read it differently. And I think Mr. Buffett also adheres closely to that same pun.

We should indeed buy stocks that are going up and not that are going down. Better yet, we should buy stocks that have shown they have been going up and continue to have some future and positive prospects.

It is our business to find and isolate the stocks that will tend to go in the same direction as our bets, whether these be long or short.

Berkshire Hathaway went from about $10 to about $320,000 over the past 50+ years while following in step with the vagaries of the market.

How long should it have taken to notice it was on the rise at some point along the way?

From 2002 to today, it went from 74k to 320k. That is an increase of $246,000 per share.

Yet, I have never seen it traded in any of the published simulations on Quantopian. Already, prior to 2002, it had gone up from $10 to $74,000, all the time making high after high over some 30 years. This gave anyone over 10,000 days to figure out that, well, “maybe”, somehow, it was going up. It has been going up now for over 18,000 days. I hope no one kept a mean-reversal thing on this one or held long-term shorts.

The general market has been going up too, on average, for over 88,000days. Should we wait another 88,000 days because we have doubts about where the market will go over the next 10 to 20 years?

We need somehow to observe that we should buy good stuff that is going up and wait for its price appreciation. IF the price of a stock does not generally go up, we get rid of that stock.

Over the past 50 years, the world population has grown from 3.6 billion to 7.5 billion. And over the next 30 years, we will add another 2.0 billion. The world will continue to prosper; companies will have to supply what people need and/or want. A lot of companies will prosper in doing so, and others won't. But, it has always been like that; it is the nature of modern business. So account for it, even in your trading strategies.

We are all doing backtests over past data in order to figure out what has a higher probability of helping us going forward, where it will count or not, in real money, that is, and not simulation money. But it will all depend on us and our trading programs.

It is not the market that is throwing you a curveball (it has been going up on average over the long term, and it is most highly probable it will continue to do so); it is your strategy design that might be ill-suited, misfitted, or poorly designed for its future job.

I kept the following in even if it was addressed to an individual:

What I am waiting for is that you simply challenge the math I presented. I can take it. There are equal signs all over the place. You will need to demonstrate a not equal sign and provide the grounds on which it is based. Surprisingly, in the process, you will be helping me design even better systems. But I think that is too much to ask. Anyway, consider it an open invitation. Mostly, I consider my math stuff to be more like 2+2 = 4, or is it 4 = 2+2?

My first post in that thread showed that the original trading strategy over the same time interval did NOT outperform even a simple Buy & Hold scenario using the same stocks.

The initial trading strategy had nothing special. It lived in a simple and basic long-term Markowitz 54-week rebalancing act. The type commonly found in so many Quantopian strategies using its scheduled rebalancing function.

Whatever the stock selection, the bar was set, and therefore, my early simulations clearly demonstrated that it was preferable to adhere to a Buy & Hold scenario than to execute the initial strategy since Σ(H(spy)∙ΔP) > Σ(Ha∙ΔP).

The objective became to reengineer this code, resulting in this new strategy Hb, so that the following could prevail:

Σ(Hb∙ΔP) > Σ(H(spy)∙ΔP) > Σ(Ha∙ΔP)

and thereby, not only outperform the original trading script but also the Buy & Hold scenario, which implicitly became the strategy's own benchmark.

The mathematical artistry came from generating alpha over and above this benchmark based on whatever trading methods I could use, even if I needed to revamp almost the whole strategy over its initial Quantopian-like strategy template.

Just more stuff to think about.

Created. July 11, 2019, © Guy R. Fleury. All rights reserved.