Video Explanation
Overview
We have designed a scoring system for each risk asset under our coverage, including SPY, QQQ, BTC, AAPL, AMZN, GOOGL, META, MSFT, NVDA, TSLA, and PLTR.
The total score is 10. We assign:
4 points to our ML model outputs
3 points to the price technicals
2 points to valuations
1 point to seasonality
We update the 4-3-2-1 scores every Monday to set the tone for the week.
ML Model Scores
Every day, we run a set of macro-driven, machine-learning algorithms ahead of the market open to deduce the risk-on versus risk-off regime for the specific risk asset. The machine produces a binary result of 1 (risk on) versus 0 (risk off).
For our 4-3-2-1 method:
One point is awarded for each day the asset remains in a “risk-on” state, with a maximum of 4 points.
One point is deducted for each day the asset remains in a “risk-off” state, with a minimum of 0 points.
Price Technicals
We analyse the price chart using both Elliott Wave theory and traditional technical analysis methods.
We award:
1 point to the medium-term technical uptrend (months)
1 point to the short-term technical uptrend (days)
1 point if the asset is en route to our target but yet to reach key resistance
Valuation
We follow each asset’s valuation in the form of P/S (or EV/S) and P/E ratios, both in a historical context and relative to their growth rates.
We award:
1 point if the growth-adjusted valuation is more attractive to peers
1 point if the absolute valuation is below the asset’s historical 5-year mean.
Seasonality (SPY, BTC, TLT)
Using the past 10-year seasonality data (where available), we assess the likelihood of a seasonal correction to SPY, BTC, and TLT. The SPY seasonality is used for SPY, QQQ, and Mag-7 stocks due to their high positive correlations.
We award 1 point if the forward 10-calendar-day returns of the asset have been historically positive.
