> If something coincides with something else nearly 100% of the time, I think its safe to say there's some relation between the two. And printing money is always prior to inflation.
Not really no, which is why we have the whole correlation != causation thing. The number of people who drowned in a swimming pool perfectly correlates with power generated by US nuclear plants over 10 years. [1] There's obviously no causative relationship. The same is true here - you need a model to adequately explain otherwise you're just intuiting, and intuition is frequently wrong.
> Are you talking about monthly? Maybe... The other thing about those times is we didn't have an unprecedented decline in commercial activity. How could businesses shut down indefinitely and a global pandemic looming over the world and the natural market response be "bullish for business!". Come on...
Again, much of the market performance is in big tech which has done extremely well over the last two years. Google is just one example. Look at the top NASDAQ and S&P holdings and you'll see the same thing. The market isn't the economy.
> Yes, they're invested in fixed income who yield < 2% and will likely drop a lot in dollar terms once rates ramp up.
Doesn't when they entered the market, and their allocation, mean a whole lot more?
> Not really no, which is why we have the whole correlation != causation thing. The number of people who drowned in a swimming pool perfectly correlates with power generated by US nuclear plants over 10 years
Not every encounter with a body of water results in drowning. But nearly every drowning involves a body of water. It's not about correlation. It's bayesian probability.
P(drowning|water) >> P(drowning)
P(lung cancer|smoking) >> P(lung cancer)
P(inflation|money printing) >> P(inflation)
Do you get it yet?
> The same is true here - you need a model to adequately explain otherwise you're just intuiting, and intuition is frequently wrong.
Pretty much any econ 101 book. Search basic economics in Amazon for sources
Every example you listed is an intuitive correlation. You can address the causative relationship between these, but not with the data you provided. All you've done is list a bunch of correlations, and asserted a causative relationship based on shared implicit context. There may be one, but you have not demonstrated it.
Let's work an example without implicit context. I tell you:
P(A|B) >> P(A)
What have you learned about B->A? Literally nothing because the relationship between A and B could be any of:
- A causes B (direct causation);
- B causes A (reverse causation);
- A and B are both caused by C (common causation);
- A causes B and B causes A (bidirectional or cyclic causation);
- There is no connection between A and B; the correlation is a coincidence.
Not really no, which is why we have the whole correlation != causation thing. The number of people who drowned in a swimming pool perfectly correlates with power generated by US nuclear plants over 10 years. [1] There's obviously no causative relationship. The same is true here - you need a model to adequately explain otherwise you're just intuiting, and intuition is frequently wrong.
> Are you talking about monthly? Maybe... The other thing about those times is we didn't have an unprecedented decline in commercial activity. How could businesses shut down indefinitely and a global pandemic looming over the world and the natural market response be "bullish for business!". Come on...
Again, much of the market performance is in big tech which has done extremely well over the last two years. Google is just one example. Look at the top NASDAQ and S&P holdings and you'll see the same thing. The market isn't the economy.
> Yes, they're invested in fixed income who yield < 2% and will likely drop a lot in dollar terms once rates ramp up.
Doesn't when they entered the market, and their allocation, mean a whole lot more?
[1] https://www.tylervigen.com/spurious-correlations