High Returns from Low Risk - Van Vliet - a book review and recommendation

Wednesday, Jun 07 2017 by
43
High Returns from Low Risk  Van Vliet  a book review and recommendation

One of Europe’s most influential fund managers has just written a fabulous little book titled “High Returns from Low Risk - a remarkable stock market paradox”. I don’t recommend many books, but I think there are a lot of investors that could learn from this. It’s barely 140 pages long, and in spite of a dose of marketing towards the end, it’s a great addition to any stock market investor’s library.

The book is written by academic turned fund manager Pim Van Vliet and his colleague Jan de Koning. Both work at the Dutch fund management group Robeco, which has become well known for its factor investing funds. While Van Vliet will take the plaudits for the book, it’s clear that De Koning has had a huge hand in making his ideas accessible and should take a lot of credit. It’s no mean feat to make tricky financial concepts easily understandable, and I think they’ve nailed it.

Cursor_and_pim_van_vliet_-_Google_Search

I’ve been reading Van Vliet’s academic research on Low Risk investing for years. In fact, his work was one of the biggest influences on our design of the RiskRatings recently launched on the Stockopedia website for more than 40,000 stocks worldwide. For those that know nothing about Low Risk investing and want a quick primer do read my previous blog on the topic.

The Tortoise & The Hare

In a nutshell, most investors believe that to achieve higher returns you need to take on higher risk. In fact, this is now so taken for granted that you’ll find risk vs return ‘sliders’ on practically all robo-advisory websites. Here’s what you’ll find on Nutmeg:


5937e184142e6QdmRG96JUo.gif


The message from the industry is… no risk / no return !

Van Vliet illustrates clearly with more than 86 year’s of stock market data that this is nonsense. Within the stock market universe, low risk stocks outperform high risk stocks dramatically over the long term.

They don’t do it every year. In fact high risk shares do outperform in bull markets. But low risk shares outperform to such an extent in bear markets and sideways markets that their overall ‘full cycle’ performance smashes that of high risk shares.

Van Vliet shows that from a universe of the 1000 largest US stocks, buying the…

Unlock this article instantly by logging into your account

Don’t have an account? Register for free and we’ll get out your way

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. 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.


Do you like this Post?
Yes
No
43 thumbs up
0 thumbs down
Share this post with friends




31 Comments on this Article show/hide all

Edward Croft 8th Jun 12 of 31
3

In reply to Joy Woodstock, post #8

Joy - what a lovely post. I agree it's best to avoid automatic stop losses... I learnt the hard way too. We're developing some tools that will help set more appropriate (volatility adjusted) stop losses. I want them for myself but they'll always be a guide to me rather than absolute.

Regarding making it less of a part time job. I am of course biased but I will always adamantly bang the table for DIY investing. What drives me mad about most institutional funds is that they are increasingly designed for scale. Scale benefits the fund provider, not the private investor and scale reduces the opportunity set. As private investors we're much more nimble and can buy small positions easily in the market and benefit from opportunities that larger funds just can't access.

Blog: Follow @edcroft on Twitter
| Link | Share
Edward Croft 8th Jun 13 of 31

In reply to pka, post #11

Pka - personally I think just focusing on Conservative / Balanced may leave some return on the table.
There's evidence that it's ok to reach for a bit more risk in higher ranking shares. Conservative + Balanced is only 25% of the market after all. Van Vliet actually reduced his large cap universe to the least risky 50% before adding momentum + income filters.

If you review the recent webinar I did, the best performing Risk+Style segment to date has been Speculative High Flyers. It's been mostly an upwards trending market since 2013, so this may not persist through a downturn, but it will certainly be interesting to watch.

Blog: Follow @edcroft on Twitter
| Link | Share | 1 reply
pka 8th Jun 14 of 31
1

In reply to Edward Croft, post #13

Ed, you wrote:
"Pka - personally I think just focusing on Conservative / Balanced may leave some return on the table.
There's evidence that it's ok to reach for a bit more risk in higher ranking shares. Conservative + Balanced is only 25% of the market after all. Van Vliet actually reduced his large cap universe to the least risky 50% before adding momentum + income filters."

If Conservative + Balanced are only 25% of the market, perhaps you should add 'Adventurous' stocks to your Van Vliet screen, otherwise you are not reproducing his original criteria closely enough.

| Link | Share | 1 reply
Edward Croft 8th Jun 15 of 31

In reply to pka, post #14

True, but I'm also mindful that he restricted his universe to the biggest 1000 stocks in the USA.  I don't have the exact cutoff, but I reckon his universe of stocks includes half our 'mid caps'.   Balanced + Conservative (from the chart below) aren't too far off 50% of this universe.

593938124105friskrating.png

Blog: Follow @edcroft on Twitter
| Link | Share | 1 reply
pka 8th Jun 16 of 31

Ed, you wrote:

"True, but I'm also mindful that he restricted his universe to the biggest 1000 stocks in the USA. I don't have the exact cutoff, but I reckon his universe of stocks includes half our 'mid caps'. Balanced + Conservative (from the chart below) aren't too far off 50% of this universe."

OK, that makes sense to me.

| Link | Share
Julianh 9th Jun 17 of 31
2

Ed thanks for this fascinating article.
Reading your review has left me thinking about
1. The short to medium term application of different investment approaches
2. Whether there will come a time when the development of such rules (based on the best ideas of investors and academics) will be replaced by machine learning
1. Timing the use of different investment approaches
When I started investing I tried to follow a Buffett "buy good shares and hold for life" approach. However the current bull run in growth stocks has seduced me into changing my approach. BOO, ACSO, BVXP, BUR, FEVR, PURP et al. have all been doing so well over the last few months that I am up 19% year to date. But the problem with following the current fad is the need to switch out of it when the mood changes. I have been top slicing to minimise the risks of a sharp correction and coping with my disappointment at all the missed profits as the top sliced shares keep powering on up. But at some point this bull market will stall or crash. And when that happens the Van Vleet approach sounds like an ideal approach into which to switch.
Will you be adding Pim van Vleet to your list of gurus, so that it is easy to find this screen?
2. Guru based investement approaches vs. machine learning
A much more long term concern of mine is the increasing prevalence of machine learning systems. A good introduction to this is the FT interview with Demis Hassabis (21 April 2017). The key difference between traditional AI and machine learning systems is that:
* AI systems apply rules based on the best human understanding of what works - e.g. the Stockopedia screens and ranks
* machine learning feels all the data and all the results into the computer and let's the computed identify patterns and rules and then keep improving on those rules as more data are collected
If machine learning can create a computer that can beat the best Go Player in the world (where traditional AI had failed), how long will it be before it will also start to produce systems that can read the stock market, pick stocks and maybe even time the market better than any of the gurus and therefore any of our guru derived systems. The risk of course is that these systems (requiring high levels of computing power and large quantities of data) will be available only to the rich. The hedge funds and high worth individuals who can afford access to these systems will again have an advantage. And that would be a real shame given how well Stockopedia has democratised investing, making it possible for the ordinary private investor to compete on equal terms with the well funded hedge funds.
Have you thought about incorporating a machine learning approach to investing in a future upgrade to Stockopedia?
With lots of appreciation for all the great things Stockopedia has done

| Link | Share
gus 1065 10th Jun 18 of 31
1

In reply to Edward Croft, post #15

Hi Ed.

Hopefully by the time you read this you're safe and sound and reasonably well recovered from your journey down to Paris. Thanks for the article and introduction to Van Vliet's book that was succinct and well written to the extent I sat and read it in one two hour sitting. Ironic that it takes two Dutchmen writing in a foreign language to communicate potentially complex ideas in such a clear manner. A few thoughts and comments on the book and your own clear follow up.

From your article, I got the sense that the VV's thesis is that there is a paradox in investing that there is a higher return to be made from a given portfolio of lower risk/volatility shares. I'd interpreted this as suggesting a "top left to bottom right" linear relationship (with return on the y axis and risk on the x axis) whereby lowest risk gives highest returns. However, if you look at the key empirical chart of the relationship on page 32, this shows it to be more of an "n" shape with best returns coming from the second lower quartile of risk at about the 20-22% volatility range before a sharp drop off when you get to the 9th and particularly 10th decile. Further it also suggests (to the naked eye) that there is not a huge difference between say the 20-80% range in the sample. I don't think this undermines his hypothesis but maybe suggests avoiding the volatility extremes (most Conservative and Highly Speculative) is the way to go.

The approach is to screen the whole stock universe for a less risky subset and then apply a second filter that combines V and M rankings to get a second filter to identify the best of the less risky safe stock subset. It may be that I missed him addressing the point on the first read through, but I wondered if there might be a different (better result) from picking the best V and M universe of stocks and then applying the risk/volatility filter to that, i.e. pick the most fertile looking stocks and then weed out those which don't clear the low volatility hurdle.

Although there is some discussion in the later chapters about the risk:reward paradox in other asset classes (e.g. fixed income, commodities etc.) and his view that the paradox of risk:return does seem to apply elsewhere, so far as I can tell the analysis is always done intra rather than inter asset class. He doesn't seem to address here whether, for example, the "best" low risk fixed income portfolios have historically out performed the best low risk equity portfolios. Possibly too broad a scope for someone only interested in shares but it would be of interest to someone looking at a wealth portfolio as a whole trying to determine if there is a sweet spot for asset allocation between different asset classes.

I note and agree with some of the comments made earlier in the thread about the use of "income" i.e. dividend per share as a measure of value. I think current dividend is perhaps not the best measure of current and future earnings potential and that some measure based on income/free cash flow per share or maybe PEG etc., might be a better filter to apply. Likewise, some element of Q screening such as adding an Altman Z2 or Beneish score might improve the gene pool too. Tying this back in to my second point above, I will probably try and apply VV's principles by optimising my target pool using my existing various QV and M based filters and then looking to pick out as a second order filter those in the two or three least risky categories.

Thanks again. All in all an excellent read and a useful addition to any investor's library.

Gus.

| Link | Share | 1 reply
ratioinvestor 12th Jun 19 of 31

Ed and all, There really is no paradox that low risk outperforms. It is only due to our psychological biases we think there is a paradox. For stocks to grow value over the long-term it is a necessary condition that they can retain value over the long-term. Low risk stocks are not exposed to risk factors that can stop them from retaining value. They are therefore able to compound value whereas stocks exposed to meaningful risk factors are not.

We have a psychological belief that high risk stocks should outperform to compensate for the risk.  But if you think it through this makes no sense.  We also see some high risk stocks perform fantastically well.  This generates a survivorship bias in terms of how we think of high risk stocks i.e. we tend to ignore or forget the myriad of high risk stocks that have failed.  When we observe the fantastic returns from a high risk stock that has succeeded we assume that to get fantastic returns we need to look towards high risk stocks.

Thanks for the book recommendation I'll have a look. Not sure it says anything new but it could be good.  It certainly looks like it is written in plain English which is unusual.

I assume the book uses volatility as a risk proxy which can work to some extent.  However, the real drivers of risk are fundamental risk factors which change over time and need to be assessed.  The banking sector, for example, may not have been volatile leading up to 2007.

A final point is that almost everyone is into factor investing these days.  The reality is that it is generally not a good way to invest.  What determines a company's worth in the long-term is the fundamental compounding power of the business.  Whether it is small cap, low volatility and other factors only offer statistical insights.

As an aside once I saw John Ruffer present once and he dismissed the idea that fund managers should avoid risk.  He stated that he was risk seeking and would try to find offsetting risk.  I.e. a Japanese stock and a UK stock with different risk profiles.  I think he got this wrong as fund managers should avoid risk given that it will hurt long-term returns and the compounding ability of individual holdings.

| Link | Share
Edward Croft 12th Jun 20 of 31
3

In reply to gus 1065, post #18

Gus - there are a variety of studies and a variety of results. Most find a fairly flat (or humped) relationship between risk and return, but with a severe drop off in the highest risk segment of the market.

What is almost universal across low volatility studies, is a sharp (and almost linear) decrease in risk-adjusted return from the lowest risk to the highest risk deciles.  That's the key takeaway from the low volatility anomaly.   A rational investor, rather than buying the higher risk decile, would borrow money to invest in the low risk decile and keep borrowing until the volatility of the holdings was the same as the higher risk/higher return decile.  At the identical level of volatility, the low risk portfolio would significantly outperform. 

Of course most investors are leverage-averse or have constraints, so they don't do this... but it is the rational thing to do if you are chasing return. 

Blog: Follow @edcroft on Twitter
| Link | Share | 1 reply
Nick Ray 12th Jun 21 of 31

It is a lot like favourite-longshot bias. In theory if horses were priced accurately it would not matter whether you bet on favourites or longshots. They would all approximately return your stake back minus the bookies profit over the long term.

But in practice, favourites win slightly more often than they should given their price and longshots win slightly less often than they should. So not only are the favourites a lower volatility bet, but they have a better return as well.
Humans seem to prefer taking a higher risk of a bigger return and will pay for the privilege of the excitement that it gives them.

I think it is similar with stocks. In theory the return/volatility ratio should stay the same and you can use leverage to decide where you want to be on the line. But in practice higher volatility stocks do not return as much as they should according to theory. Those who seek the excitement of volatility are apparently prepared to pay for it (not necessarily intentionally!)

| Link | Share
ed_miller 12th Jun 22 of 31
1

In reply to Edward Croft, post #20

Ed - Interesting point regarding price volatility vs risk-adjusted return and leveraging a low price-volatility portfolio for best return. However, this doesn't consider the effect of leverage on tolerance of price volatility, due either to psychology or pragmatic considerations (e.g. margin calls, or the threat of them). That my portfolio is unleveraged, and I take a long-term view, is key to my tolerance to higher price volatility, especially for high-quality stocks. Under such circumstances, Buffett doesn't accept price volatility as a valid measure of risk.


Thanks for another useful and interesting article.

Regards,

Ed Miller

| Link | Share | 1 reply
Edward Croft 13th Jun 23 of 31
3

In reply to ed_miller, post #22

Of course the great irony about Warren Buffett is that he runs a highly leveraged low-beta (low vol) strategy. Most value investors are so disdainful of the use of volatility as 'risk'... but the reality is many of them align their investment processes with low volatility principles.

Read up on Buffett's low-vol + quality strategy here... http://www.econ.yale.edu/~af227/pdf/Buffett%27s%20Alpha%20-%20Frazzini,%20Kabiller%20and%20Pedersen.pdf

Blog: Follow @edcroft on Twitter
| Link | Share | 2 replies
fazm 13th Jun 24 of 31

In reply to Edward Croft, post #23

greater irony is the same research people kills the dividend part. Subsumed in Value (p/bv) & quality (growing dividends) and offering a fraction of the premium of said "value" & "quality".

| Link | Share
ed_miller 13th Jun 25 of 31
1

In reply to Edward Croft, post #23

Good to see the paper you attached - 'Buffett's Alpha' again. I wondered what you meant initially when you referred to Buffett as highly leveraged, but of course you were referring to his use of insurance float - good point.

I think Buffett would point out that low volatility was a by-product of investing in companies that are both very large (by necessity given the scale of funds invested) and high-quality (to achieve superior long-term returns), as well as avoiding paying too much, rather than actually setting out to achieve low volatility to reduce portfolio risk. As you will be aware, Buffett put it this way: "The estimate of risk has nothing to do with volatility. It is based on the certainty that the individual stocks will, over time, produce a profit." [See 'The Essays of Warren Buffett by Lawrence A. Cunningham] Maike Currie, Personal Finance Specialist at Fidelity Worldwide Investment added: "Don't confuse risk and volatility. Volatility, while painful, is not risk. If you're investing for the long term, fluctuating market sentiment along the way does not matter." [Thisismoney.co.uk, 17th Jan 2015]. I think this distinction between short- and long-term is crucial. I can understand the attraction to Quants of using price volatility to measure risk, and for short-term risk I think it is valid; but not a QV buy-and-hold portfolio over many years. I wonder whether a liabilities-to-profit ratio, perhaps in combination with net gearing and an earnings-stability measure (such as that used by Bill O'Neil) might provide a more successful measure of portfolio risk over long holding periods. The strategies of many successful small-cap growth investors suggests it might.

Regards,
Ed

| Link | Share | 1 reply
Edward Croft 13th Jun 26 of 31
2

In reply to ed_miller, post #25

Ed, of course you do hear these arguments a lot and Howard Marks has written dozens of pages about what risk is or is not.  But there's no doubting that on average less risky companies are less volatile.  It may be individual companies that matter to value investors, but it's averages that matter to quants.   

Ican't perceive of a scenario where the lowest volatility set of companies in the market are the most risky.  I can imagine individual assets that are low volatility being risky (e.g. Bernie Madoff's fund)... but averages will tend to iron extreme point examples out.  

I do go into some more thought in the RiskRatings ebook, and there are some scatter plots showing the relationship of Volatility with Bankruptcy risk.  It's funny, but nearly all modern models of bankruptcy risk include volatility as a measure of perceived market risk.  So there's certainly something in it.  

Blog: Follow @edcroft on Twitter
| Link | Share | 1 reply
ed_miller 13th Jun 27 of 31

In reply to Edward Croft, post #26

All good points, Ed. I'll take a look at the info behind your latest links - thanks. Howard Marks is never terse!

| Link | Share
Philip Winkworth 5th Jul 28 of 31

Thanks for a good review of an excellent book. One observation I would like to make is that the book did not place quite enough focus on the fact that the screening process is a multi stage one and can't really be done by simply entering all the criteria into a screener and pressing go.

Van Vliet advises to rank the stocks then buy the first 100. Please correct me if I am wrong, but isn't he saying to rank them on the sum of their scores in the income and momentum fields after first discarding those with the highest volatility?

To do this we first need to identify our low volatility universe then rank all candidates on each of the two criteria then add the two rankings together to give another score. Once we have this combined score we can sort the stocks from best to worst using Excel or something and then buy the top 100 to top 20 or whatever.

If there is a way to have Stockopedia or Google do this for me, to avoid a tiresome export to a spreadsheet, then I would appreciate some instruction on how to make it happen.

PGW

| Link | Share
JohnEustace 9th Jul 29 of 31
1

Now that I have read the book I wasn't so impressed. It seems to me he is advocating a QMV approach where volatility is used as the only real quality filter.
I get the attraction of low volatility and I much prefer a nice steady line upwards on the price chart to one that jerks around but it's not sufficient for me. I think there is much more rich and useful data embedded in the Stockopedia rankings system.

| Link | Share
Dougalash 24th Jul 30 of 31

brilliant book its a must read.

| Link | Share
Redrichmond 17th Oct 31 of 31
1

Ed , more recomendations on books please.Cant get enough of them
I have worked my through 8 of the guru screeen books and just ordered the Van Vliet book. (+ another screen , william o neil book from the states coming) Amazing , by reading I am definately improving at investing. Wonderful. My Favourite so far is the contrarian David Dreman book... I will need to build a library soon

| Link | Share

What's your view on this article? Log In to Comment Now

You can track all @StockoChat comments via Twitter


About Edward Croft

Edward Croft

CEO at Stockopedia where I weave code, prose and investing strategies to help investors beat the stock markets. I've a background in the City and asset management but now am more interested in building great stock selection tools for the use of investors online.   Traditionally investors online have had very poor access to the best statistics, analytics and strategies for the stock market and our aim is to set that straight.  High Quality fundamental information has been prohibitively expensive in the past and often annoyingly dull. People these days don't just want to know the PE Ratio and look at a balance sheet. They expect a layer of interpretation over data, signal from noise and the ability to know at a glance whether a stock is worth investigating or not. All this is possible using great design and the insights gleaned from quantitative research.  Stockopedia is where we try to make it happen ! more »

Follow


Stock Picking Tutorial Centre



Let’s get you setup so you get the most out of our service
Done, Let's add some stocks
Brilliant - You've created a folio! Now let's add some stocks to it.

  • Apple (AAPL)

  • Shell (RDSA)

  • Twitter (TWTR)

  • Volkswagon AG (VOK)

  • McDonalds (MCD)

  • Vodafone (VOD)

  • Barratt Homes (BDEV)

  • Microsoft (MSFT)

  • Tesco (TSCO)
Save and show me my analysis