A PCA-Based Multi-Asset Class ETF Portfolio for these Uncertain Times

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 In this post we asked a Statistics-trained AI to construct a portfolio consisting of ETFS representing Asset Classes viz: DXY=Currency [USD]; DCB=Commodities; IEF=10-year Treasury; SPDR=Equities [SP500]; GLD=Gold.

Data as of 4 June 2025

The initial PCA (Principal Components Analysis out is presented in the chart below:


The Correlation matrix Heatmap is shown below:

The Investor’s instructions to the AI was:

“The uploaded .xlsx contains the prices of the most common and most liquid ETFs representing the different asset classes viz: SPDR, DXY, IEF, GLD, DBC. Due to the unpredictability of the current situation in the financial markets caused by the US-China trade war and the unpredictable behavior of the current U.S. President, use the most recent PCA loadings.  Assume I am a retiree with no regular income and live on the monthly payout from my Social Security and the interest rate payment from my bank savings account. The current bank savings account interest rate is 2.5 % a year. Taking into account my circumstances, devise a PCA-based portfolio strategy using the ETFs above, that would give me an annualized return of not less than 3.5%. Tell me the risk of this portfolio using the Treynor Ratio and not the Sharpe Ratio.  Take $100,000 as my allocation for this investment. Thus, show the allocation for each ETF as a dollar amount, and the total as $100,000. Rounding the numbers is allowed. Plot all this on a chart that I can easily visualize.”

The proposed portfolio allocation is depicted in the chart below. The portfolio has a Beta of 0.04, and a Treynor Ratio of 1.73 with a projected annual return of 10.2%.








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