The Trend Asset Allocation Model is an asset allocation model that applies trend-following principles based on the inputs of global stock and commodity prices. This model has a shorter time horizon and tends to turn over about 4-6 times a year. The performance and full details of a model portfolio based on the out-of-sample signals of the Trend Model can be found here.
My inner trader uses a trading model, which is a blend of price momentum (is the Trend Model becoming more bullish, or bearish?) and overbought/oversold extremes (don't buy if the trend is overbought, and vice versa). Subscribers receive real-time alerts of model changes, and a hypothetical trading record of the email alerts is updated weekly here. The hypothetical trading record of the trading model of the real-time alerts that began in March 2016 is shown below.
The latest signals of each model are as follows:
- Ultimate market timing model: Buy equities (Last changed from “sell” on 28-Jul-2023)*
- Trend Model signal: Bullish (Last changed from “neutral” on 28-Jul-2023)*
- Trading model: Bullish (Last changed from “neutral” on 16-Apr-2024)*
Update schedule: I generally update model readings on my site on weekends. I am also on X/Twitter at @humblestudent. Subscribers receive real-time alerts of trading model changes, and a hypothetical trading record of those email alerts is shown here.
Subscribers can access the latest signal in real time here. Washed out Big Tech?
In discussions with investors, I have been asked if Are Big Tech has formed a bottom. Big Tech had been the leadership in the U.S. equity market. It’s an important group as it forms roughly 40% of the weight of the S&P 500. The NYSE FANG Plus Index staged an upside breakout out of a cup and handle pattern with long-term bullish implications. The index then pulled back and it’s bouncing off a relative support zone (bottom panel).
Is it time to tiptoe back into these stocks? What are the implications for the overall market in light of the outsized weight of Big Tech in the S&P 500?
The full post can be found here.
