Normal distribution | Mathematical finance

Kurtosis risk

In statistics and decision theory, kurtosis risk is the risk that results when a statistical model assumes the normal distribution, but is applied to observations that have a tendency to occasionally be much farther (in terms of number of standard deviations) from the average than is expected for a normal distribution. (Wikipedia).

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From playlist BIOLOGY: Health

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What Causes a Heart Attack?

What is the leading cause of heart attacks worldwide? » Subscribe to Seeker! http://bit.ly/subscribeseeker » Watch more SICK | http://bit.ly/SICKplaylist Atherosclerosis. That’s athero, which talks about the vessels in our heart, plus sclerosis, which means fibrosis of those vessels.

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The immune system has a whole arsenal of ways to fight off an infection. But with pneumonia, the immune system’s response can be lethal. » Subscribe to Seeker! http://bit.ly/subscribeseeker » Watch more SICK | http://bit.ly/SeekerSICKplaylist When it comes to some diseases, like pneumonia

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From playlist Healthcare Patient Education Animations

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Kurtosis of a probability distribution (FRM T2-7)

[Here is my xls http://trtl.bz/121817-yt-kurtosis-xls] Kurtosis is the standardized fourth central moment and is a measure of tail density; e.g., heavy or fat-tails. Heavy-tailedness also tends to correspond to high peakedness. Excess kurtosis (aka, leptokurtosis) is given by (kurtosis-3).

From playlist Quantitative Analysis (FRM Topic 2)

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Level 1 Chartered Financial Analyst (CFA ®): Measures of dispersion including volatility

Session 2, Reading 8 (Part 2): A previous video in this CFA playlist looked at classic measures of central tendency. This is also called the first moment of the distribution or the distributions the location where is the distribution centered. When we say that I think most of us think of t

From playlist Level 1 Chartered Financial Analyst (CFA ®) Volume 1

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From playlist Space Science

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FRM: Distribution moments (mean, variance, skew, kurtosis)

Here is the spreadsheet I used @ http://db.tt/bziK312h. The four central moments of a distribution are mean (1st), variance, skew and kurtosis. They tell us quickly about the personality of the distribution. For more financial risk videos, visit our website! http://www.bionicturtle.com.

From playlist Operational Risk Analytics

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This is a sample of our 2012 FRM Quantitative Analysis T2.a video tutorials. View our products here: https://www.bionicturtle.com/products/financial-risk-management/ The Bionic Turtle program is the most effective and affordable preparation aid for the Financial Risk Manager (FRM) exam.

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FRM: Normal probability distribution

This video is a review of the normal density function and its key properties. Subscribe to our channel or visit our website for more financial risk videos! http://www.bionicturtle.com

From playlist Statistics: Distributions

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From playlist Radiation

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FRM: Skew & Kurtosis

I illustrate how to manually calculate skew and kurtosis with Google's daily price data from 2007. The point is the variance, skew and kurtosis are each related MOMENTS of the distribution. A normal distribution has skew = 0 and kurtosis = 3 https://www.dropbox.com/s/9ge1gckgqhahcou/2.a.1

From playlist Statistics: Distributions

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FRM: Normal mixture distribution

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From playlist Statistics: Distributions

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Solving BCBS-185 with Machine Learning

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From playlist Level 1 Chartered Financial Analyst (CFA ®) Volume 1

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From playlist April Fool's Day Favorites

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13. Commodity Models

MIT 18.S096 Topics in Mathematics with Applications in Finance, Fall 2013 View the complete course: http://ocw.mit.edu/18-S096F13 Instructor: Alexander Eydeland This is a guest lecture on commodity modeling, analyzing the methods of generating profit with a constrained system. License: C

From playlist MIT 18.S096 Topics in Mathematics w Applications in Finance

Related pages

Capital asset pricing model | Benoit Mandelbrot | Stochastic volatility | Taleb distribution | Decision theory | Kurtosis | Statistics | Normal distribution | Statistical model | Skewness risk