Speaking of tensions, when both the policy rate and quantity of money ease, valuations tend to rise. However, how do you typically handle the nuances of conflicting forces in valuation when:
1. The policy rate is hiking, but the quantity of money is increasing, or
2. The policy rate is hiking, Fed liquidity is increasing, but due to various reasons, the increased Fed liquidity is not effectively creating credit?
"While these datapoints are important to monitor, fundamentally, they have a lower quality compared to the economic datapoints noted above. This is inherent in their own process for collection. These types of data points are meant to show changes on the margin or diffusion as opposed to the absolute LEVEL. "
The idea is that not all data has the same quality.
What you would need to do is go through every single data release and ascertain the quality of each release and the range of implications you can make from them.
For example, very few of us would ever use the Michigan data or conference board data. its honestly just trash.
also you have to identify which data points are simply redundent.
Finally, rememeber, there is a quality spectrum of data based on its frequency. For example, GDP data is higher quality than PCE data even though they show functionally the same thing for the PCE line item. but the higher frequency can have more noise
Thanks for the answer. That aspect is clear, I’m more puzzled about the last part “These types of data points are meant to show changes on the margin or diffusion as opposed to the absolute LEVEL”
Do you mean it’s better to ignore >50 or <50 readings, focusing on rate of change?
It’s all spx
Does the debt-to-asset/equity charts include financials? Would be interested to see one without financials.
Great work. I have a question though.
Speaking of tensions, when both the policy rate and quantity of money ease, valuations tend to rise. However, how do you typically handle the nuances of conflicting forces in valuation when:
1. The policy rate is hiking, but the quantity of money is increasing, or
2. The policy rate is hiking, Fed liquidity is increasing, but due to various reasons, the increased Fed liquidity is not effectively creating credit?
Thats the secret sauce sir :)
dm me on discord and ill share a few thoughts
lol got it🤣
awsome report
"While these datapoints are important to monitor, fundamentally, they have a lower quality compared to the economic datapoints noted above. This is inherent in their own process for collection. These types of data points are meant to show changes on the margin or diffusion as opposed to the absolute LEVEL. "
Could you elaborate please?
The idea is that not all data has the same quality.
What you would need to do is go through every single data release and ascertain the quality of each release and the range of implications you can make from them.
For example, very few of us would ever use the Michigan data or conference board data. its honestly just trash.
also you have to identify which data points are simply redundent.
Finally, rememeber, there is a quality spectrum of data based on its frequency. For example, GDP data is higher quality than PCE data even though they show functionally the same thing for the PCE line item. but the higher frequency can have more noise
Thanks for the answer. That aspect is clear, I’m more puzzled about the last part “These types of data points are meant to show changes on the margin or diffusion as opposed to the absolute LEVEL”
Do you mean it’s better to ignore >50 or <50 readings, focusing on rate of change?
Ah wait, maybe you mean those datapoints are not useful to forecast the exact final reading (es cpi) but the components diffusion?