James O'Shaughnessy's seven traits of the successful active investor

Monday, Oct 07 2019 by
19
James OShaughnessys seven traits of the successful active investor

We owe a debt of gratitude to James O’Shaughnessy not just for his groundbreaking multi-decade studies into various stock market factors but because of his championing of a rational, systematic, and emotionally-detached approach to investing. 

He values process over outcome - and his systems are typically supported by vast amounts of quantitative research. Building a framework of consistent, data-driven processes into your investment routine is one of the surest ways to improve returns over time. We’ve referred to it as 'managing the monkey' before - applying rules-based processes to avoid self-defeating mistakes. 

When it comes to managing that monkey, few rival O’Shaughnessy. So, when he discusses the traits he deems most conducive to successful investing, it pays to listen. Here’s a quick review...

1. Successful active investors have a long-term perspective

How many of us are truly long-term investors in this fibre optic age? The data certainly suggests that we are trading more than ever and holding for shorter time periods

O’Shaughnessy himself says: ‘Successful active investing runs contrary to human nature. It’s encoded in our genes to overweight short-term events, to let emotions dictate decisions and to approach investing with no underlying cohesiveness or consistency.  Successful active investors do not comply with nature; they defy it.

Simply thinking long-term can give you a sizable advantage over other investors. AQR co-founder Cliff Asness calls it the closest you can get to having ‘an investing superpower’.

2. Successful active investors value process over outcome

If an investment goes wrong, that does not automatically invalidate the thought process that compelled you to buy. 

Humans crave certainty but the inconvenient truth is we deal in probability distributions. Ed illustrates this point in his most recent SNAPS post. From that article, I’ve taken the image below - you might have seen it before. Every blue dot in each of the 5 graphics below represents a randomly generated portfolio of 90+ StockRank shares held for the first half of 2019.

The important point here is the dispersion. Each blue dot is more or less identical in terms of Value, Quality, and Momentum characteristics, but even the 50 Stock Folios have a c10% performance range. Regardless of the outcome, though, the process underlying each portfolio was sound and is backed up by years of our own research.

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Disclaimer:  

As per our Terms of Use, Stockopedia is a financial news & data site, discussion forum and content aggregator. Our site should be used for educational & informational purposes only. We do not provide investment advice, recommendations or views as to whether an investment or strategy is suited to the investment needs of a specific individual. You should make your own decisions and seek independent professional advice before doing so. The author may own shares in any companies discussed, all opinions are his/her own & are general/impersonal. Remember: Shares can go down as well as up. Past performance is not a guide to future performance & investors may not get back the amount invested.


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5 Comments on this Article show/hide all

Nick Ray 7th Oct 1 of 5
20
‘Knowing the past odds of how often and by what magnitude a strategy either outperforms or underperforms its benchmark gives you an incredible edge that many people ignore. Successful active investors know this and pay close attention to this information, thereby putting the probabilities on their side.’

I agree 100%. So can we have a  button to calculate past odds for a strategy (or even for a given metric) please?

More generally, you have an absolute goldmine of data collected now, but hardly any of it seems to be easy to do anything with.

We can create screens but we can't find out how they would have performed in the past.

We can use "rank in market" in a screen, but we can't directly find out where those percentile points are for a metric.

There is so much that is almost within in reach....

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EssexBoy 7th Oct 2 of 5
1

In reply to post #519466

Nick: during the recent Stockopedia webcast, I recall Ed Croft mentioning in passing that they will be introducing a ‘back testing’ facility in the near future, for use with standard screens and tailor made screens; and perhaps with Portfolios.

Perhaps someone from Stockopedia can comment here on this.

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HumourMe 7th Oct 3 of 5
1

In reply to post #519466

I'm eagerly awaiting the day I can investigate Z-Score like measures using modern tools such as logistic regression and being able to investigate other factors using tools such as random forests and xgboost to really dig into F-Scores etc. A summary of winners vs losers at the end of the year with common start of year factors, if any, would be nice ...

We might not have enough back data to be able to definitively test long term outcomes but we would be able to eliminate what hasn't worked recently.

I'm (re) reading What Works on Wall Street at the moment (4th edition is much better than the 1998 revised edition although plot is a little dry) and it is stressed that in the longer term styles go in and out of fashion as part of a process of mean reversion. A useful Stocko addition would be a summary of Guru historical drawdowns and how close we are - if mean reversion also applies to these, then todays 'losers' might be tomorrows future performers. A single page summarising the old stats available on the old site would also be nice to have, especially if expanded to include Sharpe and Sortino ratio etc.. .

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Jack Brumby Tue 10:27am 4 of 5
4

In reply to post #519466

Hi Nick,

Backtesting capabilities are high on the agenda and we're hoping to bring out a simple version in the near future. I'm not personally too familiar with how it's progressing but I know it's in the works. It's part of a big data project we are working on that will be a real upgrade behind the scenes and will allow you to do much more of the type of analysis that you want to do.

As you say, almost within reach.

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Magicmerve Wed 2:34pm 5 of 5
1

Really interesting read and I've taken away some key messages that I was personally questioning.

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