I have been dabbling lately in some different modeling for my portfolio (just using the free websites like Portfolio Visualizer) by using different adaptive allocation models to improve CAGR and/or decrease volatility. These methods include different momentum trades like risk parity, inverse volatility, and minimum variance.
I was just seeing if anyone else trades like this to increase returns and/or decrease volatility in their own portfolios and, if so, what tools they use or what their portfolio looks like?
A very cookie cutter example (
link to Portfolio Visualizer) of what I am talking about for anyone interested running from 1997-present. (Note: Just an bland example)
This example contains just 4 funds which are rotated based on, in this example, risk-parity. (actually it doesn't matter if you use risk parity or minimum variance in this example because it is so simplified) The four funds are all Vanguard: VTSMX (total stock market index), VGTSX (total international stock index), VGSIX (real estate index), and VBMFX (total bond index). Only the top two funds are held each month in varying percentages based on risk-parity.
As you can see, the timing model increases returns while decreasing volatility. (CAGR increases from 7.51% to 9.95% and annualized volatility decreases from 11.48% to 10.26% which improves both Sharpe and Sortino ratios for the timing model vs. the equal-weight portfolio.)
I just have been looking at approaches (like this example) which require trading/rebalancing at the beginning of each month. I figure that is is easy to do and only takes a few minutes each month from my brokerage account login.
Anyone else have experience with this or approaches they have tried using risk-parity, minimum variance, etc.? Maybe with leveraged ETFs?
Edit: corrected link
Hustle Harder