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The era of free money may be coming to an end.

As we approach a point where deficits must decrease or even be eliminated, strategic investing will face challenges from headwinds. The risk of investing in strategic allocations has increased.

We do not know when the next bear market will arrive. What we know is that investors who are not prepared will face unexpected losses.

Market timing has the potential to minimize risks. With that in mind, we have developed a dual approach to market timing: hybrid asset allocation.

Hybrid asset allocation (HAA) employs two strategies: asset cross-sectional momentum and strategic allocation. Both strategies use ETFs to generate signals.

The asset cross-sectional momentum strategy (CSMOM) and the strategic allocation strategy (MOMMF) generate signals in the monthly timeframe. The rebalancing of MOMMF occurs annually and includes both tactical and passive components.

On top of that, we have also developed a dynamic momentum strategy. The Dynamic Momentum Strategy (DYNMOM) is a proprietary timing algorithm that trades the SPY ETF. Its objective is to maximize the Sharpe ratio and avoid market corrections. It generates signals on a monthly basis.

The signals of both HAA and DYNMOM are available with a monthly subscription. After the last trading day of each month, subscribers receive an email when the updates are available. Then, subscribers can log in and view the updates and whether there are new entry or exit signals.

We provide precise entry and exit signals every month.

No ambiguity, no buzzwords, no fundamental analysis, no obscurantism: well-defined entry and exit signals for major and liquid ETFs.

Relative performance of HAA, DYNMOM, and SPY ETF, January 2, 2020 to May 31, 2024

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Disclaimer: No part of the analysis in this blog constitutes a trade recommendation. The past performance of any trading system or methodology is not necessarily indicative of future results. Read the full disclaimer here.

Charting and backtesting program: Amibroker. Data provider: Norgate Data

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