## What does cdf stand for in finance

- What does CDF stand for?
- What does CDF stand for? - Acronym Finder
- Statistics - What is CDF - Cumulative distribution
- Contract for Differences (CFD) Definition
- Random Variables, PDFs, and CDFs

A real-life example comes from finance. One way of measuring the risk of a portfolio (of stocks, for example) is to calculate the 5% daily value-at-risk, or VAR. To say that the 5% daily VAR is $x$ means you expect your loss to be worse than $x$ dollars on only 5% of days. For example, you might report that the 5% daily VAR is \$65,555, meaning that you expect to lose more than \$65,555 on 5% of days, and on the other 95% your loss will be less than \$65,555 (ideally, you will be in profit!)

## What does CDF stand for?

CFDs allow investors to trade the price movement of assets including ETFs, stock indices, and commodity futures.

### What does CDF stand for? - Acronym Finder

The CDF in After the Flash: Deep Six had established the People's Republic of Tidewater as an official government to rival that of the United States of America after the Atlanta Crisis. The CDF act as Tidewater's main military power, known at the time as the PRTM. The PRTM in Deep Six was a unit stationed in Chatham County, Georgia as the 9th Georgia Guard Division stationed in Fort Wilmington, also known as the "Blue Shield" division, tasked with holding the frontier against the United States. The division in Deep Six consisted of two companies the veteran Brown Company with two platoons left and full fresh Easy Company along with a reinforcement Lance Company.

#### Statistics - What is CDF - Cumulative distribution

The reporting of daily VAR is a requirement in financial institutions worldwide, so this certainly satisfies your requirements of a 'real-life' application!

##### Contract for Differences (CFD) Definition

Will it land heads up? Tails? More than that, how long will it remain in the air? How many times will it bounce? How far from where it first hits the ground will it finally come to rest? For that matter, will it ever hit the ground? Ever come to rest?

###### Random Variables, PDFs, and CDFs

For example, if $X$ is the height of a person selected at random then $F(x)$ is the chance that the person will be shorter than $x$. If $$F(\textrm{685 cm}) = $$ then there is an 85% chance that a person selected at random will be shorter than 685 cm (equivalently, a 75% chance that they will be taller than 685cm).

The question, of course, arises as to how to best mathematically describe (and visually display) random variables. For those tasks we use probability density functions (PDF) and cumulative density functions (CDF). As CDFs are simpler to comprehend for both discrete and continuous random variables than PDFs, we will first explain CDFs.

Investors holding a losing position can get a margin call from their broker requiring the deposit of additional funds.

A PDF is simply the derivative of a CDF. Thus a PDF is also a function of a random variable, x , and its magnitude will be some indication of the relative likelihood of measuring a particular value. As it is the slope of a CDF, a PDF must always be positive there are no negative odds for any event. Furthermore and by definition, the area under the curve of a PDF( x ) between - 8789 and x equals its CDF( x ). As such, the area between two values x 6 and x 7 gives the probability of measuring a value within that range.

EDIT: For my sample dataset of a normal distribution with an average of , this is what the CDF and survival functions look like. As the peak of a normal distribution represents the average, one expects the CDF to level off after the peak (ie, increase at a slower rate after the peak).

Extreme price volatility or fluctuations can lead to wide spreads between the bid (buy) and ask (sell) prices from a broker.