Why Confidence Level 95% is -1.65? I'm learning about Value at Risk for Investing which got me into statistical questions.
Here it's said that
For a confidence level of 95%, # of Standard Deviations (σ) = -1.65 x σ
And for a confidence level of 99%, # of Standard Deviations (σ) = -2.33 x σ
My question is, where do we get the -1.65 from? I've googled and found that for investing, the 95% confidence level always uses -1.65 in here, here, and this youtube video.
However when from the answers on this post, you can see that people are sure that -1.65 belongs to a 90% confidence level. Also see this answer.
So which one is correct? And how does it get the number from anyway? (Sorry I did not learn about statistics, please share a source to learn if you have)

As a bit of an expansion to the answer by @Tim :
First, the sources are assuming that the observed values follow a normal distribution.
Second, the sources are using "confidence level" in a particular sense.  By "95% confidence", they are saying to report the 5th percentile of observed values. Which is essentially the highest value in the bottom 5% of the observed values.
Assuming a normal distribution, this is approximately mean - 1.65 * sd.
Practically speaking, if you have the actual observed values, looking at the 5th percentile has the advantage of not needing to assume a normal distribution of values.
As you might imagine, mean + 1.65 * sd (plus !) approximates the 95th percentile, if this were also of interest.
So, mean ± 1.65 * sd captures the middle 90% of the observations.
You can run the following R code at https://rdrr.io/snippets/ .  It will generate random numbers that are approximately normal, show you a histogram, and calculate the "95% confidence" value as suggested by your sources, by two methods.  You can change the values for NumberOfObs, Mean, and StdDev.
NumberOfObs = 100
Mean = 0
StdDev = 10

A = rnorm(NumberOfObs, Mean, StdDev)

SD = sd(A)

mean(A) - 1.645 * SD

quantile(A, 0.05)

hist(A)

