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TYPES OF KURTOSIS A PICTORIAL RAPRESENTATION

ABOUT KURTOSIS

       

     

                                         DEFINITION OF 'KURTOSIS'

Like skewness, kurtosis is a statistical measure that is used to describe the distribution. Wherea  skewness differentiates extreme values in one versus the other tail, kurtosis measures extreme values in either tail.   Distributions with large kurtosis exhibit tail data exceeding the tails of the normal distribution (e.g., five or more standard deviations from the mean). Distributions with low kurtosis exhibit tail data that is generally less extreme than the tails of the normal distribution. For investors, high kurtosis of the return distribution implies that the investor will experience occasional extreme returns (either positive or negative), more extreme than the usual + or - three standard deviations from the mean that is predicted by the normal distribution of returns. This phenomenon is known as kurtiousis

Kurtosis is a measure of the combined weight of a distribution's tails relative to the center of the distribution. When a set of approximately normal data is graphed via a histogram, it shows a bell peak and most data within + or - three standard deviations of the mean. However, when high kurtosis is present, the tails extend farther than the + or - three standard deviations of the normal bell-curved distribution. Kurtosis is sometimes confused with a measure of the peakedness of a distribution. However, kurtosis is a measure that describes the shape of a distribution's tails in relation to its overall shape. A distribution can be infinitely peaked with low kurtosis, and a distribution can be perfectly flat-topped with infinite kurtosis. Thus, kurtosis measures “tailedness,” not “peakedness.

Types  of  Kurtosis

There are three categories of kurtosis that can be displayed by a set of data. All measures of kurtosis are compared against a standard normal distribution, or bell curve.

              mesokurtic.The first category of kurtosis is a mesokurtic distribution. This distribution has kurtosis statistic similar to that of the normal distribution, meaning that the extreme value characteristic of the distribution is similar to that of a normal distribution

              leptokurtic. The second category is a leptokurtic distribution. Any distribution that is leptokurtic displays greater kurtosis than a mesokurtic distribution. Characteristics of this type of distribution is one with long tails (outliers). The prefix of "lepto-" means "skinny," making the shape of a leptokurtic distribution easier to remember. The “skinniness” of a leptokurtic distribution is a consequence of the outliers, which stretch the horizontal axis of the histogram graph, making the bulk of the data appear in a narrow (“skinny”) vertical range. Some have thus characterized leptokurtic distributions as “concentrated toward the mean,” but the more relevant issue (especially for investors) is that there are occasional extreme outliers that cause this “concentration” appearance. Examples of leptokurtic distributions are the T-distributions with small degrees of freedom.

              platykurtic.The final type of distribution is a platykurtic distribution. These types of distributions have short tails (paucity of outliers). The prefix of "platy-" means "broad," and it is meant to describe a short and broad-looking peak, but this is an historical error. Uniform distributions are platykurtic and have broad peaks, but the beta(.5,1) distribution is also platykurtic and has an infinitely pointy peak. The reason both these distributions are platykurtic is that their extreme values are less than that of the normal distribution. For investors, platykurtic return distributions are stable and predictable, in the sense that there will rarely (if ever) be extreme (outlier) returns.

                       

figure1: Types Of Kurtosis A Grahical Representation

Table no1: Ststistical  Analysis Tabular Column

STSTISTICS	VALUE
KURTOSIS	3.18
SKEWNESS	0.11
SHARP RATIO	1.34
STANDARD DEVIATION	6.77

about me in simple view..............

                                                              CURRICULAM VITAE

S.V. ARJUN KRISHNAN             Mobile : 9947710534

E Mail : arjunkanayam@gmail.com

CAREER OBJECTIVE

To be associated in a challenging environment with a reputed organization, where I can enhance my potentials and qualifications for the growth of the organization.  Looking for better prospects, inurn build on my skills and experience and provide for an overall growth.

QUALIFICATIONS

• SSLC from Technical Higher Secondary School (THS) Shoranur with First Class
• VHSE from 9VHSC Shoranur) with First Class
• B. Sc. Physics from M.P.M.M.S.N. Trusts College, Shoranur with First Class
• B. Ed. From IDEL Education Centre, Cherppulassery with Second Class
• M. Sc. Physics from M.P.M.M.S.N. Trusts College (Pursuing)

ADDITIONAL QUALIFICATION

• Basic Computer Knowledge
• Two wheeler, Four wheeler

KEY SKILLS

• Communication Skills
• Ability to interact, create relations.
• Ability to organizes

PERSONAL DETAILS

NAME : S.V. ARJUN KRISHNAN

PARENTS NAME : P.V. GOPALAKRISHNAN

S.V. JAYALAKSHMI

DATE OF BIRTH   :   22-05-1988

ADDRESS   :   KANAYATHU VARIYAM,

KANAYAM P.O.,

SHORANUR – 2, PALAKKAD, KERALA.

PIN – 679 122

GENDER   :   MALE

RELIGION : HINDU

MARITAL STATUS : SINGLE

LANGUAGES KNOWN : MALAYALAM, ENGLISH, TAMIL

DECLARATION

I do hereby declare that all the above mentioned particulars are true to the best of my knowledge and belief.  I feel the above attributes and my educational qualification make me eminently suited for taking up a very competitive job in your esteemed organization.  Looking forward to an interview opportunity with you.

YOURS TRULY

S.V. ARJUN KRISHNAN