I borrowed the idea of putting all the technical terms here from an excellent book[^1] on making decisions under uncertainty. The author points out that some concepts are "cloaked in Steam Era anachronisms."
And since the reader may be exposed to financial jargon elsewhere, it's helpful to unpack some of the definitions in plain language. As the reader will (hopefully) see later, on closer investigation, these concepts are not as complicated as they seem.
<span class="jargon-term">CORRELATION</span> - shows how closely the points in a scatter plot lie along a **straight line**. It can be any value in the range from -1.0 to +1.0 inclusively. As stressed in every Statistics 101 class, correlation doesn't imply that $x$ causes $y$ or $y$ causes $x$. ^correlation
For example, there's a strong positive interrelation between returns of the S&P 500 and the Nasdaq 100 indices, which is logical given that they both represent baskets of stocks and have a sufficient overlap. So when the S&P increases in one period, the Nasdaq will typically also go up, and vice versa.
![[glossary_corr_spx_ndx.svg]]
As can be seen from the chart, a straight line is not a bad fit for this situation, as the points are clustered pretty tightly around it.
Next comes an example of a negative interrelationship. Good market performance is associated with things running smoothly and having less uncertainty about the future. So when VIX goes down, typically, S&P goes up. Similarly, when prices jump up and down (VIX goes up), it is usually bad for the performance of the stocks (S&P goes down). The points are scattered more around the fitted line than in the previous example, but one can still argue that the association is pretty strong.
![[glossary_corr_spx_vix.svg]]
Here's an example of a correlation that is close to 0. Even though we can draw a straight line to the scatter plot, it's obviously a poor fit. There's no link between changes in one variable and changes in another.
![[glossary_corr_spx_bonds.svg]]
<span class="jargon-term">VOLATILITY</span> - the degree of up and down price movements from period to period. In finance, this term is often used interchangeably with another Red Phrase, <span class="jargon-term">STANDARD DEVIATION</span>, because it's the default method for calculating it. So, if someone says price volatility or standard deviation, they talk about the same thing. As always, a picture will be helpful. Consider daily price changes of different assets for the period of 1998-2024:
![[glossary_assets_volatility.svg]]
Compared with stocks, real estate, or gold, bond prices barely move.
Here's a table with some descriptive statistics:
| | Average | Standard Deviation | Max Down Move | Max Up Move |
| :---------- | ------: | -----------------: | ------------: | ----------: |
| Bonds | 0.01 | 0.26 | -1.67 | 1.8 |
| Gold | 0.04 | 1.06 | -9.09 | 10.95 |
| Stocks | 0.04 | 1.23 | -11.98 | 10.99 |
| Real Estate | 0.05 | 1.69 | -19.33 | 18.31 |
Thinking about volatility as a typical price change won't be an oversimplification. The table shows that a 1% daily move (up or down) in U.S. stocks shouldn't be making headlines, as it's pretty common. However, such a move would be a more significant event for bonds, given it's 4 times their typical price fluctuation.
[^1]: Savage, S. (2012) [The Flaw of Averages](https://www.amazon.com/Flaw-Averages-Underestimate-Risk-Uncertainty-ebook/dp/B0096CT4VY?ref_=ast_author_mpb). John Wiley & Sons