Andreas F. Clenow – Stocks on the Move – Review

When I see a trading book that should be good I do research on the author as well as the writing before I decide to get it. I had heard about this book from different sources, listened to the author speak on some podcasts, and seen references in the intro to other traders I’ve been following who had helped with the book. Andreas Clenow is a quantitative hedge fund manager and the book is about momentum trading in the US stock market. When I start to read another trading book I don’t expect to learn a bunch of new things, but to understand the thought process and mindset behind the author’s approach to trading the markets in order to generate ideas myself. The book was published in 2015.

Being realistic is a good start

The book starts with explaining the mutual fund business and why most managers underperform the index. The author gives a brief introduction to ETFs with a word of caution about derivatives bundled into many exchange traded funds. Andreas brings readers down to earth by explaining why thinking that you can successfully pick stocks on logic and judgement is an illusion, but it’s not to promote technical analysis as he sees a great deal of luck and randomness there, too. He also writes about quantitative strategy simulations and survivorship bias that creeps in if you leave delisted stocks out of the testing universe.

Stocks that have gone up can go even more

It’s funny to read that at the time of writing in early 2015, Apple’s market cap was around $500 billion and the author asked the question, how likely it was for such a large cap stock to double in price compared to small caps. Looking at it today 7 years later, AAPL is worth almost $3T (trillion!). That is 5x return. Though the author has a point that small caps are more likely to double in price than mega caps, it pays to notice that stocks can go up more than it seems logical.

Why classical trend-following doesn’t work on stocks

I like the chapter about classical trend-following and the author saying it doesn’t work on stocks. Not so fast. After ditching the short side that is going short with the trend, the overall performance in his examples improves a lot. This is something I have found out myself after backtesting on decades of data. Simply riding stocks down by holding shorts for the long-term doesn’t work. It may work for a single random example in hindsight, but I mean it doesn’t work statistically on a large sample size. Another point in the book is that trend-following all the stocks in an index long only, doesn’t add any value to just holding the index. Which means we need a way to narrow down the universe of buying candidates and here comes momentum to the game. It may sound too stupid simple to be true, but trading momentum basically means buying stocks that are going up the most, anticipating the move to continue for some time.

Real trading differs from good-looking backtests and simulations

There’s much more in this book about measuring momentum, market filters, position sizing, position rebalancing etc. However, the second part of this piece of writing is rather different but very interesting. The author walks us through the momentum strategy in action that he presented earlier, describing year by year performance since 1999 all the way to 2014 with all the ups and downs and other nuances regarding trading the markets. It’s a fun and eye-opening way of getting explained the daily hustle, randomness and emotions when dealing with the markets in real life. I don’t want to compare the dotcom bubble too much to the most recent euphoria, but I must admit that reading 1999-2000 in action felt so 2020-2021. My main takeaway here was a reminder that as long as one has the discipline to manage risk and follow a tested plan, then feeling stressed about a market move today will look ridiculously unimportant in a 10-year equity curve in hindsight.

The Stocks on the Move strategy in brief

If you came here for the rules, here they are in short. Several people have rebuilt the strategy in code since the book came out, so the details are well documented:

1. The universe is the stocks in the S&P 500.
2. Rank them by momentum: the annualized slope of an exponential regression over the last 90 days, multiplied by the R² of that regression. A smooth rise ranks higher than a jumpy one with the same gain.
3. Skip stocks below their 100-day moving average and stocks with a gap of 15% or more in the last 90 days.
4. Only open new positions while the S&P 500 is above its 200-day moving average.
5. Size each position by volatility: 0.1% of the account divided by the stock’s 20-day Average True Range gives the number of shares.
6. Trade once a week (he uses Wednesday): sell stocks that dropped out of the top 20% of the ranking or fell below their 100-day average, and buy from the top of the list with the cash. Every other week, rebalance the position sizes.

Here is the sizing with made-up round numbers. On a $100,000 account, 0.1% is $100. A stock with a 20-day ATR of $2 gets 50 shares, and one with an ATR of $5 gets 20. The jumpier stock gets the smaller position, so on a normal day each holding moves the account by about the same amount. It is the same idea as sizing from the stop in my stop loss post, with volatility in place of the distance to the stop.

The index filter is the rule I find most interesting. It doesn’t sell anything when the S&P 500 drops below its 200-day average. It only stops new buying, so the portfolio shrinks on its own as the other rules sell the weak stocks.

Who is Andreas Clenow?

Andreas Clenow is a Swedish-born asset manager based in Zurich and the chief investment officer of ACIES Asset Management. He has an MSc in economics from the University of Gothenburg, worked at Reuters, where he became Global Head of Institutional Charting and Technical Analysis, and has been a partner in hedge funds. He has been a guest on several trading podcasts, including Better System Trader (episode 13), which I cover in my Better System Trader review.

Andreas Clenow’s books

Stocks on the Move (2015) is his second book. The first, Following the Trend (2013), applies the same systematic thinking to diversified trend following in futures, and I reviewed it too: Following the Trend review. His third, Trading Evolved, shows how to build and backtest strategies like these in Python.

Andreas Clenow summarizes his book with just one statement “buy stocks that move up”, but I actually enjoyed reading it even though it covered the topic I have studied a lot before, it still made me think critically about my own strategies and their robustness going forward. If you want to study systematic momentum trading in stocks, then it’s definitely an educative read.