*Named after the investment pro who coined the term “risk parity,” the Qian portfolio is my version of the mathematically precise Risk Parity asset mix Edward Qian proposes in his book. It belongs in the moderate portfolio grouping, along with the 80/20 and the Levered Butterfly.*

I wanted at least one portfolio to track the mathematically optimal version of Risk Parity, and thus have the Qian (pronounced “Chen”) portfolio. It is named after Edward Qian, Chief Investment Officer and Head of Research, Multi Asset at PanAgora Asset Management. Qian coined the term “risk parity” in 2005, has published a number of commentaries and white papers on the concept, and is the author, Risk Parity Fundamentals. In chapter five of that book, Qian proposes a benchmark risk parity portfolio, or rather, the macro-allocations for such a portfolio. On page 199, Qian writes:

*The volatility estimate we choose is 20%, 15%, and 3.5% for GSCI (Commodities), MSCI (Equities), and WGBI (Bonds), respectively. The weights are inversely proportional to the volatilities and they are scaled to 25%, 33%, and 142% correspondingly so that the resulting leverage is 200%.*

Qian proposes this as the allocation between the broad asset classes but does not propose individual funds to put that portfolio into practice. Additionally, Qian’s audience seems to be other professional investment managers with greater abilities to use futures, options, and other more advanced financial techniques to achieve the sought-after amount of leverage. I then took these allocations and using the leveraged ETFs available to the average investor, created the Qian portfolio. It uses small amounts of leveraged equity ETFs, with heavy allocations toward leveraged bond ETFs to create the portfolio. I also chose to divide the 25% Commodities allocation to 15% PDBC and 10% Gold, in keeping with other risk parity portfolios. I selected ETFs from the same common palette of ETFs for the other portfolios to minimize the chance that it was specific asset choice that explains the portfolio’s performance, for good or for ill. Instead, the shared assets will hopefully provide insight on the particular choices for macro-allocation.

To be quite honest, the Qian portfolio does not seem that attractive based on backtesting. I group it with the Bogleheads 80/20 and the Levered Butterfly, since it has around the same figures for standard deviation (the mid-13% range). It does suggest a slightly higher annual return compared to the 80/20, but unlike many other risk parity portfolios, does not seem poised for shorter or less severe downturns. Moreover, its withdrawal rates are even lower than the 80/20. When compared to the Levered Butterfly, meanwhile, it appears even less favorably, with return numbers, volatility and drawdown statistics, and withdrawal rates meaningfully lower. On the plus side, the correlation matrix does show a number of negatively-correlated and non-correlated relationships between assets, but ideally, this would also show up in higher withdrawal rates and shallow drawdowns.

I did consider scrapping this portfolio, but thought that, even if it does underperform the others in the tracking process, that could be valuable data to consider. The fixed-income allocation seems high for sure. It may also be that the macro-allocation is sound, but the choices for the assets to implement it are not. Perhaps I have chosen the wrong type of bonds for the portfolio, namely the 10% to short-term treasuries. That could have been extended-duration, investment-grade corporates, or less than investment-grade corporates, instead. We’ll just have to test to find out.

Here is the **Correlation Matrix** (*Data from 2015, so take with a grain of salt; credit to **Portfolio Visualizer**):*

And, the **Backtest Analysis*** **(Data from 1970; credit to **Portfolio Charts**):*