My colleagues Saurabh Mukherjea and Rakshit Ranjan co-authored a book titled Coffee Can Investing with a subtitle – “The Low Risk Road to Stupendous Wealth”. In this blog, Justin Carbonneau of Validea brings out a similar  essence from the book High Returns from Low Risk: A Remarkable Stock Market Paradox, authored by Robeco fund managers Pim van Vliet and Jan de Koning, whose research with long term data support highlights this paradox in the stock market. Popular belief is that investors seek an appropriate reward for the risk they are willing to take and hence to generate higher returns one needs to take higher risk. The authors demonstrate that indeed it is possible to generate higher returns with low volatility. Van Vliet’s multi-factor model overlays a momentum and quality factor over the original low volatility universe.
In this month’s newsletter, we explain why Marcellus’ Consistent Compounders Portfolio has been resilient through the recent bout of market weakness (the portfolio is up 5.8% in August vs Nifty’s -0.9% and is up 10.6% in the past six months vs Nifty’s 2.1%) – our portfolio’s weighted avg earnings grew 17% vs Nifty’s 1.8%. It also explains how our portfolio companies’ manage to sustain these earnings despite the macro slowdown – because these companies produce goods and services which are essential to the common man. That in effect is one of three parts to our investment philosophy of reducing volatility: First, look for companies with clean accounting and governance – hence avoid fraud risk. Second, prefer companies which make essential products, thereby reducing demand risk. Finally, look for deep competitive moats, which alleviate risks to profitability.
“Van Vliet developed a factor-based model that combines three relatively simple investment criteria – volatility, momentum and net buyback yield. This is what he calls a “conservative formula” for stock selection.
Volatility: The investable universe (the 1,000 largest companies by market cap) is separated into two groups. The 500 least volatile stocks are eligible for inclusion in the model, while the 500 most volatile are ineligible. Volatility is define by the 3 year standard deviation of returns for each security in the universe.
Momentum: Stocks with higher momentum are rewarded in the model. Academic studies have shown momentum tends to persist in the intermediate term, but mean revert in the short-term and long-term. As a result, stocks are ranked based on their one year momentum, excluding the most recent month.
Net Payout Yield: Net payout yield, which is the sum of the dividend yield and the share buyback yield, partly capture the value and quality premium in stocks. The higher the net payout yield the better.
The stocks that passed the initial volatility test are ranked by the other two factors, and then a combined rank is calculated. The stocks with the best combination of momentum and net payout yield get the highest scores.
…From 1929 to 2016, the top 100 conservative stocks selected using the factors mentioned above produced an annualized return of 15.1% compared to 9.3% for the overall market and 2.1% for the most speculative stock cohort. The conservative and speculative portfolios were made up of the 100 top ranked stocks, rebalanced quarterly. The outperformance is not just limited to the US market, as the conservative formula also produced alpha generating results in different markets, including Europe, Japan and Emerging markets.”

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Note: The above material is neither investment research, nor financial advice. Marcellus does not seek payment for or business from this publication in any shape or form. The information provided is intended for educational purposes only. Marcellus Investment Managers is regulated by the Securities and Exchange Board of India (SEBI) and is also an FME (Non-Retail) with the International Financial Services Centres Authority (IFSCA) as a provider of Portfolio Management Services. Additionally, Marcellus is also registered with US Securities and Exchange Commission (“US SEC”) as an Investment Advisor.



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