The Darwin Portfolio is one of my portfolios that I don’t normally adjust too often. It holds 5 ETFs that represent 5 of the major asset classes and allocations are based on Risk Parity such that risk (as measured by volatility) is limited to 3% per

The Darwin Portfolio is an “all-weather” portfolio that requires few adjustments, based on risk parity, only when allocations get significantly out-of-line. The portfolio holds only 5 assets that may be adjusted for risk parity with an allocation to “Volatility”

The Darwin Portfolio is an “All-Weather” portfolio with a dash of volatility. Performance to date (since lowering volatility target levels last November) looks like this: The large “jumps” correspond to periodic allocation adjustments to risk parity – but maybe the stacked chart is easier

Adjustments to the Darwin Portfolio are not rigorously scheduled since they are designed to maintain Risk Parity, are usually minor, and I prefer to keep trading costs to a minimum. Here’s how the Portfolio has performed since I changed to a

The Darwin Portfolio is a “Buy-And-Hold” portfolio of assets that is only adjusted when allocations fall out-of-line with recommendations based on risk parity (i.e. equal risk on all holdings). Performance to date (~4 months from inception)

The Darwin Portfolio is a risk-adjusted allocation model with volatility targeting used to determine how many shares of each asset to hold. The portfolio holds only 5 conventional, but diversified, asset classes plus a 10% holding in a volatility product (depending on whether volatility is expected to

The Darwin Portfolio is a relatively inert portfolio in that all assets in the portfolio quiver are held continuously (Buy-and-Hold) in allocations designed to keep the risk from each asset at defined levels as calculated from volatility measurements over time. Throughout most of 2022 I

Last week I took an early look at the Darwin Portfolio and, while I don’t like to change too many parameters for these reviews (so as to provide a reasonable example of performance that might be expected from use of the various models used), I decided that the