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with Tal Davidson

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Quantitative Value & Momentum Performance 1999-2019

The following portfolio is a quantitative all-cap Value & Momentum portfolio. This systematic, algo-based portfolio consists of 50 long-only holdings: 30 Quantitative Value stocks (60% of the portfolio value) + 20 Quantitative Momentum stocks (40% of the portfolio value). The portfolio holds liquid Stocks with QV stocks in the 30th percentile of market or larger and QM stocks in the 40th percentile of the market or larger. It enjoys a low asset turnover of ~30%, achieved through sophisticated methods.

Attributes of the portfolio:

  • Diversified – minimizes risk and volatility through holding 50 stock holdings
  • High Return Potential over the long-term – utilized  Value and Momentum factors
  • Low Cost – holds stocks directly, so NO management fees
  • Low Maintenance – rebalance only twice per year
  • Low Asset Turnover – contributing to low transaction costs and low tax liability

I have rigorously tested my screener and strategy using the best-known methods to avoid curve-fitting and cognitive biases. Let’s see how it fared in the short-term (i.e., in 2019) and the long-term.

All Cap Value & Momentum (QV + QM) During 2019

The following chart presents the performance of a quantitatively-selected portfolio of 50 long-only holdings: 30 Quantitative Value stocks (60% of the portfolio value) + 20 Quantitative Momentum stocks (40% of the portfolio value). The portfolio holds liquid Stocks with QV stocks in the 30th percentile of market or larger and QM stocks in the 40th percentile of the market or larger.

QV+QM Performance 2019

The following chart presents the performance of my version of the portfolio over a 5-years period, June 30th, 2014, to June 30th, 2019. The reason I do all my long term backtests starting June 30th is two-fold: 1) to be consistent with academic research who uses such convention 2) to be consistent across all my publications, enable readers to compare all my backtests, apples to apples.

QV+QM Performance 2014-2019

We can see that the performance over a 5-years period was on par with the S&P 500’s performance. The model was ahead of the benchmark for the larger part of the 5-years period and stumbled below it just at the very end.

Testing the strategy over 20 years starting June 30th, 1999, and ending on June 30th, 2019, tells a totally different story.

QV+QM Performance 1999-2019

All-cap Quantitative Value & Momentum delivered astonishing average annual returns of 17.22% vs. 5.81% for the S&P 500. Over the long term, the model beats the benchmark (and any other strategy I am familiar with) heads over feet. Moreover, it has done so with lower volatility, as measured by the standard deviation of monthly returns. The standard deviation of the strategy came in 12.26% vs. 14.51% for the S&P 500, as can be seen in the following table. Sharpe ratio is at a super high level of 1.22x vs. 0.32x for the S&P 500. The correlation with the S&P 500 benchmark is a mere 72%. It means that only 72% of the months tested, the S&P 500 and the model both appreciated or both declined. In all other cases, when the market declined during a month, the model appreciated, and vice versa. Over the long term, Quantitative Value & Momentum develops a healthy margin over the market and runs much higher.

QV+QM Statistics

It is also interesting to see, in the tables above, the contrast between the wild overperformance in the long term (table on the right) vs. the mild underperformance during the last three years (table on the left).

Looking at the yearly performance in the following table, we see that in most of the years during the last 20 years, the model delivers positive excess returns over the market. It had underperformed the benchmark in only 5 of the last 20 years. Unfortunately, two of those years were 2017 and 2019, falsely leading some investors to believe that Quantitative Value & Momentum, or any Value Investing method in general, had lost its touch. Some even go as far as saying that Value Investing is dead.

QV+QM yearly performance

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Hi, I’m Tal Davidson. I develop quantitative investing strategies which are based on deep academic research. I’m not the ordinary finance guy. I’m more of a technology geek, working as a computer engineer in one of the largest tech companies in the world. I’ve been learning and experimenting with investment strategies for the last 15 years. In the last few years, I perfected several strategies and have made the transition to being 100% quant. My commitment is to guide you in creating your own quantitative portfolio with confidence, even if you’re not a programmer. You too can the master quant strategies that have the power to help grow your capital and achieve life-changing returns!

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