Year-to-date: Low-volatility evidence dating back to 1873

Year-to-date: Low-volatility evidence dating back to 1873

15-08-2016 | インサイト

As new historical databases are opening up, there are great opportunities for out-of-sample tests of market anomalies. Research shows that the volatility effect also existed in the 19th century.

  • David Blitz
    David
    Blitz
    PhD, Executive Director, Head of Quant Selection Research.
  • Pim  van Vliet, PhD
    Pim
    van Vliet, PhD
    Managing Director, Head of Conservative Equities - Pim van Vliet

Speed read

  • New deep historical databases are opening up 
  • A great opportunity for out-of-sample tests of market anomalies 
  • The volatility effect exists in the 19th century as well

In our summer reading series, here’s a chance to catch up with some of our top picks so far in 2016. The following story was originally published earlier this year.

New databases

The large majority of all academic studies use the famous CRSP (Center for Research in Security Prices) database. This database is maintained by the University of Chicago. It contains all stock data for all US stocks listed on the New York Stock Exchange from 1926 onwards, followed by stocks listed on the American Stock Exchange (AMEX) and the technology-dominated NASDAQ exchange. This database is the longest and cleanest one can get at this moment. Still, it only covers a successful period for one country: the United States. 

Increasingly, other databases are opening up and described in the empirical financial literature. Additional evidence is very important when assessing the robustness of factor premiums. For example, Dimson, Nagel, and Quigley (2003) have tested the value premium for the UK market over the period 1955-2001. Recently, Goetzmann and Huang (2015) studied a completely new database with stock returns from the St. Petersburg stock market. They show that momentum also worked in pre-revolutionary Russia over the period 1865-1914. Geczy and Samonov (2015) use a database for the US stretching from 1801 to 2012. They also document a momentum premium in the 19th century. 

We welcome these new historical databases. They provide an additional opportunity to falsify an existing theory. A skeptical explanation for market anomalies is that they are just the result of luck or chance. Besides more recent out-of-sample evidence, a deep look into history could also be refreshing now and then and give insights into why an anomaly exists. 

In this short article, we briefly discuss the main results for the low-volatility effect in the 20th century. We supplement this with fresh out-of-sample results for the low-risk effect dating back to the 19th century.

クオンツに関する最新の「インサイト」を読む
クオンツに関する最新の「インサイト」を読む
配信登録

20th century: US low-risk stocks outperform high-risk stocks

Low-risk stocks outperform high-risk stocks in the long term. We have documented the effect for Europe and Japan (2007) and emerging markets (2012). A nice overview of international evidence is given by Haugen and Baker (2012). 

For this article, we have used the CRSP database and only included: (1) stocks with prices above USD 1 and (2) the largest 1,000 stocks. These strict criteria help to get to an investable database (only large caps) that is not affected by technical effects such as the bid-ask bounce. Stocks are sorted into ten portfolios based on historical 3-year volatility with a quarterly rebalancing frequency and portfolio returns are equal-weighted. 

The figure below shows the cumulative performance of the low-volatility and high-volatility portfolio. Both portfolios consist of 100 stocks. 

The puzzling result shown in Figure 1 is that low-volatility stocks outperform high-volatility stocks, while CAPM theory would predict the opposite. The annualized return difference is 4% and corrected for risk the CAPM alpha spread is 14%. 100 dollars invested in 1929 in low-volatility stocks would have grown to USD 400.000 in early 2015 while the investment in high-volatility stocks would be worth only USD 20.000. Low-volatility stocks would have made you 20 times richer than high-volatility stocks. Most striking is the very weak performance of high-volatility stocks. 

Figure 1 | Cumulative performance of low/high volatility stocks 1929-2014
Source: Robeco Quantitative Research, CRSP

19th century: Belgian low-risk stocks outperform high risk stocks

The CRSP database includes the 1929 stock market crash and the subsequent Great Depression. But stock markets already existed well before the CRSP start data of 1926, and these forgotten decades also contain interesting bull and bear markets. For example, the big stock market crashes of 1873 and 1907 are often lacking in academic empirical studies. 

To our knowledge, the only 19th century evidence for the low-risk anomaly is provided by Annaert and Mensah (2013). They show the existence of a low-beta effect in the Belgian stock market over the period 1873-1914. Today the Belgian stock market is relatively small (<1% of MSCI World), but at the end of the 19th century, it was one of the largest stock markets in the world. Belgium was the first country to take part in the Industrial Revolution on the European continent after Great Britain. 

In their analysis, the Belgian professors analyze on average 237 stocks that were listed on the Belgian stock market and had at least two years of price data. They find evidence for the existence of a significant low-risk effect. Figure 2 shows the results of five portfolios sorted on market beta. The dotted line shows the risk-return relation as predicted by the CAPM, while the curved line shows the actual empirical relation between return and market beta. The line is first upwards sloping, but then going down sharply for high-beta stocks. 

Figure 2 | Risk and return in the 1873-1914 period
Source: Annaert and Mensah, 2013, data are from Panel E and G in Table 2

Low-risk stocks outperform high-risk stocks, also in the period 1873-1914. We like such ‘archeological finance’ research for two reasons. 

First, the finding that low-volatility, momentum and value anomalies are also found to be present in this entirely new dataset makes it unlikely that these anomalies are merely a manifestation of data mining. That is good. One of the biggest risks for quantitative researchers is that they pick up spurious patterns, which are just a coincidence. That’s why we like long-term databases and rely on solidly proven factors. 

Second, this new data can provide a better understanding of stock market anomalies. For example, in the 19th century hardly any money was managed by professionals and benchmarks did not exist yet. One explanation for the low-volatility effect is the dubious role of benchmarks, which create agency problems between asset owners and asset managers. This new evidence tells us that benchmarks cannot be the only explanation why low-risk stocks earn high-risk adjusted returns. 

重要事項

当資料は情報提供を目的として、Robeco Institutional Asset Management B.V.が作成した英文資料、もしくはその英文資料をロベコ・ジャパン株式会社が翻訳したものです。資料中の個別の金融商品の売買の勧誘や推奨等を目的とするものではありません。記載された情報は十分信頼できるものであると考えておりますが、その正確性、完全性を保証するものではありません。意見や見通しはあくまで作成日における弊社の判断に基づくものであり、今後予告なしに変更されることがあります。運用状況、市場動向、意見等は、過去の一時点あるいは過去の一定期間についてのものであり、過去の実績は将来の運用成果を保証または示唆するものではありません。また、記載された投資方針・戦略等は全ての投資家の皆様に適合するとは限りません。当資料は法律、税務、会計面での助言の提供を意図するものではありません。

ご契約に際しては、必要に応じ専門家にご相談の上、最終的なご判断はお客様ご自身でなさるようお願い致します。

運用を行う資産の評価額は、組入有価証券等の価格、金融市場の相場や金利等の変動、及び組入有価証券の発行体の財務状況による信用力等の影響を受けて変動します。また、外貨建資産に投資する場合は為替変動の影響も受けます。運用によって生じた損益は、全て投資家の皆様に帰属します。したがって投資元本や一定の運用成果が保証されているものではなく、投資元本を上回る損失を被ることがあります。弊社が行う金融商品取引業に係る手数料または報酬は、締結される契約の種類や契約資産額により異なるため、当資料において記載せず別途ご提示させて頂く場合があります。具体的な手数料または報酬の金額・計算方法につきましては弊社担当者へお問合せください。

当資料及び記載されている情報、商品に関する権利は弊社に帰属します。したがって、弊社の書面による同意なくしてその全部もしくは一部を複製またはその他の方法で配布することはご遠慮ください。

商号等: ロベコ・ジャパン株式会社  金融商品取引業者 関東財務局長(金商)第2780号

加入協会: 一般社団法人 日本投資顧問業協会