I've written a book describing how my system works, so I hope you don't mind if I use my "canned" explanation. It will be almost the same pat answer I've written elsewhere in these forums.
What I call sentiment (or bias) is based primarily on two factors: (1) painstakingly selected moving averages, and (2) typical price ranges.
The notion that there are no "best" moving averages is one with which I wholeheartedly disagree. However, I do not consider them to be the ones commonly used by many traders, such as the 10-, 20-, 50-, 100- or 200-period moving averages. In fact, I don't base the moving averages I use on ANY periods at all. One of the differences that makes my system unique is that all my moving averages are based on TIME, which is something I have not seen used by any other trading methodology.
I would also dispute the belief that, though a moving average will show a consistent change in the price of a security over time, there are no uniform rules that can be applied across all markets (due to the fact that every asset class has unique price histories and levels of volatility).
This is because in designing my system, part of my goal was to come up with something that was reflective of flight dynamics, which uses the laws of physics to explain how forces act on vessels to govern their performance, stability and control to ultimately determine their velocity and attitude with respect to time.
So, in the same way pilots are aware that a Boeing 747 will lift off the ground by angling upward at two to three degrees per second with a maximum angle of 10 to 15 degrees; I as a retail trader know the parameters dictating whether an asset is rising or falling from the perspective of a day, swing, or position trader. This does not change from one asset class to the next.
In other words, market sentiment or bias is strictly dependent on statistical analysis. What do the numbers say? It's as simple as that.
I also think of my system as relying on a methodology similar to that used by meteorologist to predict the weather—one based as much as possible on mathematical probability. The idea is to gather and evaluate precise, up-to-date, quantitative data and use it to calculate the odds of price reaching designated values within a given time period by patterning the system's elements after the equations, wave functions, and computer models used in weather forecasting.
But, instead of monitoring wind velocity and direction, cloud formations, humidity, temperature, and barometric pressure; I evaluate the synergy between such factors as typical price ranges, reoccurring chart patterns, horizontal support and resistance levels, trend lines, and market structure, all in multiple time frames—with the result being a graphical depiction of current market conditions I can then use to help me make precise, well-timed trades.
USDJPY has been heading higher at least since January 27, 2021. There's no two ways about it. This makes its overall sentiment or bias bullish. For me, it is completely technical. However, the key (longer-term) measures I use are one-month, 12-days, 6-days, 1-week, 4-days, 2-days, 24-hours and eight-hours, and these perspectives are out of alignment with one another at the moment.
From my point of view, what I would LOVE to see happen is for the rate to drop back down to the lower regions of the associated price ranges (somewhere in the neighborhood of 129.37 to 132.33) where I could enter a long position with almost 100% certainty (conviction) that the rate would ultimately (eventually) rise once again.
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