The notability issue has been addressed. More external sources are added and many sentences are rewritten. Furthermore the formula was featured on Bloomberg.com and a independently replicated study for the Indian market. Furthermore a 'critique' section is added to give a more balanced description of the subject. The result section has also been rewritten and split in US results and International results.
'''Conservative formula investing''' is an investment technique that uses the principles of [[low-volatility investing]] enhanced with [[Dividend yield|net payout yield]] and [[Momentum (finance)|momentum]].
'''Conservative formula investing''' is an investment technique that uses the principles of [[low-volatility investing]] enhanced with [[Dividend yield|net payout yield]] and [[Momentum (finance)|momentum]].
The investment formula selects and equally weights the best 100 stocks from 1,000 stocks on a quarterly basis. It is discussed and replicated in a Bloomberg webinar in August 2022.[1] It is included as a stock screener on Validea and ValueSignals.[2][3] The formula is based on 3 investment criteria: volatility, net payout yield and momentum. First, the 1,000 largest stocks are divided into two groups based on their historical 36-month stock return volatility. Second, each stock in the low volatility group is ranked on its 12-1 month price momentum and net payout yield. Third, the momentum and yield ranks (1-500) are averaged and the 100 best stocks are equally weighted in a final portfolio. Code to replicate the investment formula is shared on Reddit and Medium.[4][5]
Background
The Conservative formula is a way to screen stocks similar to the magic formula of Joel Greenblatt. Stock screeners are designed to help investors in a systematic way in their aim to achieve high risk adjusted returns. The conservative formula gives investors exposure to multiple investment factors utilizing easy to obtain data. The formula is outlined by Pim van Vliet in the investment book 'High Returns from Low Risk' in 2016.[6] This book co-authored by Jan de Koning is translated into Chinese, German, French, Spanish and Dutch.[7][8][9][10][11] The formula has been scientifically tested by David Blitz and a public version is available on SSRN.[12][13] In 2019 and 2022 the formula is independently replicated and applied on the China A-share and Indian stock markets..[14][15] The formula has been discussed by Alpha Architect on GuruFocus.com, La Vanguardia Financial Investigator, ETF guru and reviewed on JD.com.[16][17][18][19][7]
Results US
The average annualized return is 15.1% over the period 1929-2016 significantly outperforming the US market index by 5.8% per year. The return is achieved with lower volatility resulting in a Sharpe ratio of 0.94 over the full sample period. It also gives a positive return over every decade. Return series are publicly available going back to 1929 and are updated every year.[20] The image shows the cumulative dollar performance the Conservative Formula. It also includes more recent out-of-sample results.
International results
The average annualized returns for Europe is 15.4% versus 7.4% for the market. The average annualized return for Japan is 9.6% versus 0.3% for the market. The average annualized return for Emerging Markets is 19.3% versus 6.3% for the market. The sample periods are 1986-2016 for Europe and Japan and 1993-2016 for Emerging Markets. In all cases the higher returns are achieved with lower volatility. [12]
The formula is independently tested on the Chinese A-share market for the period August 2008 to August 2018. Return is 10.9% versus 1.4% for the CSI-300 index, achieved with lower volatility.[14] In another replication study for the Indian market the conservative formula significantly outperforms the S&P BSE 100 by 12.6% per annum also with lower volatility. The Indian sample period ranges from September 2006 to June 2022.[15]
Critique
During 2020 low-volatility stocks did not offer risk much reduction during the pandemic sell-off lagging the market during the strong and quick rebound that followed. Several investors lost faith in a low-volatility approach.[21][22]
The returns are gross of transaction costs. The estimated annual transaction costs are between 0.3% and 0.8% for developed international markets lowering the net returns.[13]
The critique points need to be weighted against the out-of-sample evidence. Positive is that replication for independent markets such as China-A shares and India show strong results. For the US, pre-sample evidence shows strong results for the sample 1866-1928 as shown in the figure. Finally the post-publication returns are positive despite 2020, but no strong and final conclusions can be drawn from this relatively short period.
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