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Definition of Tail Risk

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Usually, the financial market follows a normal distribution but with the introduction of tail risk, the idea that the distribution of returns is not normal but has fatter tails crosses the mind. A tail risk or fat tail risk is an event of a risk for the portfolios of assets. It occurs when there is a possibility of fluctuation in the investment from its mean point to three standard deviations. Although the probability of such events to occur is quite low but still, it can cause great negative consequences for the market as well as for the portfolios.

How does It Work?

A tail risk occurs when there is a possibility of three standard deviations to move further than the mean point. Usually, in financial markets, it is believed that returns that are generated from the securities and portfolios have a normal distribution. Such distribution is also called bell-shaped distribution. But tail risk suggests that these distributions are not normal but has fatter tails, the left side of the tail represents the lowest return an investor can get on the investment while the right side of the tail represents the highest return an investor can get. It can also be named as left tail risk and right tail risk depending upon the sides; left tail risk shows negative returns while right tail risk shows positive returns of a portfolio.

Example of Tail Risk

A tail risk can be understood better by taking a real-life example. In 2007, the health of 30 public companies of the United States of America was contained in the Dow Index, these companies were also a part of the S&P 500 Index. The index showed great performance and went above the 24k mark in December 2023 and continued to show an upward movement since then.

In January 2023, the index which had been continuing to show an upward movement hit the mark of 26k and investors were expecting that this growth will continue to flourish but due to trade wars and economic slowdown, the whole market of the US suffered. It also created an impact on the Dow Index and it reached fall back to the 24k mark in October 2023. It was a massive fall for the market and the Dow index fell to 21k in December 2023. It was a 19℅ downward move in the year. The tail risk in the Dow Index was when it went below the 24k mark in October 2023, as the downfall from 26k to 24k was a behavioral movement but when it went below that, the condition got worse.

Graphical Representation of Tail Risk

A tail risk can be better understood with the help of graphical representation. Here,

The bluebell curve indicates the normal distribution that is generated from the securities or the portfolios.

The green bell curve indicates the tail risk fluctuations that could happen in the investment from the mean point to the three normal deviations.

The left tail of the green curve shows how that much loss an investor can suffer while the right tail of the green curve shows how much the investor can gain on investments.

Uses of Tail Risk

It shows investors all the possible risks that could happen which makes them able to gauge the risks.

Tail risk enables investors to take quick and accurate decisions in the investment strategy.

Tail risk is used to support hedging which results in better and increased cash flow in the market.

Tail risk is used to get knowledge about the negative activity that could happen in the market.


Enhanced decision making: Tail risk enables the investor in measuring the unforeseen risks which enable the investor to take accurate decisions.

Encouragement of hedging: Tail risk encourages hedging which results in the better and increased flow of funds in the market.

Create awareness: Tail risk creates awareness about all the possible risks that could happen in the future which could create a great negative impact thus creating awareness.

Possibility of not occurring: There is a high possibility for the tail risk that it wouldn’t occur even onetime as there is a quite low chance of such occurring.

The fear among the investors: Tail risk creates a sense of fear among the investors which can result in fewer investments and can create a negative outlook.


The possibility of losses that could happen shortly due to any unforeseen event is known as tail risk. It can be on both the sides of the curve as the right tail and the left tail, the right side indicates gains while the left side indicates losses. It is beneficial for the businesses and the investors as they can study tail risk which will help them to take accurate decisions for investment.

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Synatx Of Example Of Matlab Polyfit()

Introduction of Matlab polyfit()

MATLAB function polyfit() is defined to fit a specific set of data points to a polynomialquickly and easily computing polynomial with the least squares for the given set of data. It generates the coefficients for the elements of the polynomial, which are used for modeling a curve to fit to the given data.

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Polyfit() function uses input vector (x) to form Vandermonde matrix (V ) having n+1 columns and r = length(x) rows, which is nothing but results in a linear system.

Syntax of Matlab polyfit()

Syntax of Matlab polyfit() are given below:


poly = polyfit(x,y,n) It generates the coefficients of the resultant polynomial p(x) with a degree of ‘n’, for the data set in yas the best fit in the view of a least-square. The coefficients in p are assigned to power in descending order and matching length of p to n+1.

[poly,Struct] = polyfit(x,y,n) It results in a structure S which can be used as input to the function polyval() in order to obtain error estimation.

[poly,Struct,mu] = polyfit(x,y,n) It results in a two-element vector having values-centered and scaled.

mu(1) holds a value of the mean of (x), and

mu(2) ) holds the value of standard of (x).

Using these two values, function polyfit()makes x centered at zero and scaledx to have a unit standard deviation,

Input Arguments

Query Points: Query points are specified as an input of vector type. If x is non-vector element, then this function polyfit() converts x into a column chúng tôi data points in x and their corresponding fitted function values contained in the vector y are formed.


If the vector x has recurring data points or if it needs centering and scaling, warning messages may result out.

Fitted values at query points: Fitted values as inputs are available at query points being specified with the vector data type. The data points in x and their corresponding fitted function values contained in the vector y are formed. If y is the non-vector element, then this function polyfit() converts y into a column vector.

Degree of polynomial fit: Degree of polynomial fit as inputs, are available being specified as any positive integer scalar. In the respective syntax, ‘n’refers to the polynomial power to that of the left-most coefficient in the polynomial ‘p’.

Example of Matlab polyfit()

The below code is designed to generate data points placed equally spaced across a sine curve drawn in a specific interval.


hold off


Use Cases for polyfit() Function

Use cases for polyfit() function are given below:

Fitting  Polynomial to Set of data Points: The below code snippet carry out the fitting process on the polynomial poly of degree 4 towards 5  points.




Fitting the Polynomial function to Error Function: The below code generate a vector having x data points being placed equally in the interval of [0,3.5] and co-efficient are assigned to the polynomial assuming the degree as 6.


hold off


Improving Numerical Properties using Centering and Scaling: While solving the equation p = Vy, the condition number for V is usually large for higher-order fits and results in a matrix with singular coefficient, as the columns of V (Vandermonde matrix) are powers of the x vector.

In such cases, functions like scaling and centering are helpful to improve the numerical properties associated with the system in order to find a fit that is more reliable. In the below example polyfit() is called on three outputs to fit a polynomial of degree 5 along with the process of centering and scaling. The data is centered for the quarter, at 0, and scaled to have a unit standard deviation.


hold off


Simple Linear Regression: A simple linear regression model can be used to apply a fitting to a set of discrete two-dimensional data points.



Combining Linear Regression and Error Estimation: A linear model can be set fit to a set of specified data points and the results can be plotted including an estimation of a prediction interval of 95%.

A few vectors can be created containing sample data points. The function polyfit can be called to fit a polynomial of degree 1 to the given set of data. Dual outputs can be specified to hold the values of coefficients supporting a linear fit as well as a structure containing error estimation.


[poly,Samp] = polyfit(xdata,ydata,1);

/*The error estimation structure is specified as the third input so that the function polyval()computes an estimated standard error. The estimated standard error estimate is stored in the second output variable delta. */

title(‘Usage of polyfit and polyval’)


Additional Note

For n number of data points, a polynomial can be fit to that of degree n-1 to passing exactly through the points.

With the increase in the degree of the polynomial, a fitting process using polyfit()loses the accuracy resulting in to a poorer fit for the data. In such cases, a low-order polynomial is preferable to use that tends to be smoother between the data points or apply a different technique, based on the requirement.

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Learn The Example Of Opencv Puttext

Introduction to OpenCV putText()

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It is also needed that the starting point for the text has to be defined within the matrix. there is also a requirement for defining the font color for the text, the font style for the text, and the weight that the text has two be specified with. The function is present in the OpenCV library of Python programming language, which is a one-stop solution that has been designed in order to solve problems related to computer vision.

Syntax for OpenCV putText()

cv2.put Text (* image *, text *, org *, font *, fontScale *, color [*, thickness [,line Type [*,*  bottom Left Origin *] *] *] *) * Parameters for OpenCV put text function

The following parameters are accepted by the OpenCV putText() function:

Parameters Description of the parameters:

image this parameter represents the original image that the user has selected to add text by the system

text This parameter represents the text that has to be drawn by the system as specified by the user

org This parameter is used to represent the coordinate with respect to the text present on the bottom left corner of the image. These coordinates are represented with the help of 2 double values that are passed, which represent the X coordinate and the Y coordinate values, respectively

font This parameter is used to represent the type or style of font, which would be denoted for the string text that the user specifies. some instances for the kinds of font types that can be used are FONT * _ * HERSHEY * _ * PLAIN OR FONT * _ * HERSHEY * _ * SIMPLEX

font * scale This parameter represents the best size for the specified font size, which is relevant to the font scale factor, which acts as a multiplying factor further font size of the text that has to be entered

thickness this parameter represents the thickness that has to be given for the line of text that has to be entered by the user. it is measured in terms of pixel size

color this parameter represents the specific color that has to be given to the text string that is being entered into the image that is being drawn on the screen. The color is extracted from the BGR tuple, which is passed to it. for instance, for a text of blue color the tuple to be passed would be * (* 255 *, * 0 *, * 0) *

Line * Type This parameter is used to define the type of line used for the text, which has to be entered into the image. This parameter is an optional parameter.

Bottom * Left * Origin this parameter is used for defining the position for the image data origin with respect to the directional position in the image. this parameter is an optional parameter. If the parameter is taken as true, the image data origin is found to be placed at the bottom left corner of the image. If it is not true, the image data origin is placed at the top left corner of the image.

Return * Value This method is responsible for returning an output image that is to be loaded from the file which has been specified.

Example of OpenCV putText()

Following is the example which is used in order to demonstrate how the OpenCV putText() command is utilized in the Python programming language

# command used to import the OpenCV library to utilize OpenCV read image function import cv2 # path being defined from where the system will read the image path = r'C:Users Priyanka Desktop educba OpenCV edu cba logo.png' # command used for reading an image from the disk disk, cv2.imread function is used image1 = cv2.imread(path) # Window name being specified where the image will be displayed window_name1 = 'image' # font for the text being specified font1 = cv2.FONT_HERSHEY_SIMPLEX # org for the text being specified org1 = (50, 50) # font scale for the text being specified fontScale1 = 1 # Blue color for the text being specified from BGR color1 = ( 255 , 0 , 0 ) # Line thickness for the text being specified at 2 px thickness1 = 2 # Using the cv2.putText() method for inserting text in the image of the specified path image_1 = cv2.putText(image1, 'EDU CBA', org1, font1, fontScale1, color1, thickness1, cv2.LINE_AA) # Displaying the output image cv2.imshow(window_name, image_1) cv2.waitKey(0) cv2.destroyAllWindows()


The OpenCV putText() method is a very useful function present in the OpenCV library, which allows the system to add text to an image that the user has provided. There are several image processing areas where text needs to be associated with the images that are being processed, and there needs to be a variety in the color, font style, width, and orientation in terms of the position whether the text has to be placed on the image which can easily be utilized by using the put text method. It also reduces the verbosity of the program that is being written and increases the overall processing speed for the program to be executed.

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5 Of The Most Useful Graphical Git Clients For Linux

To some, the idea of a graphical Git client is sacrilege. Git is a command line tool, after all. It’s actually one of the easiest command-line tools to use, so why use a GUI in the first place? That comes down to the visual areas that the command line falls short in. GUI clients are for graphs, charts, highlighting, and all the nice things that help to wrap your head around the complexities of your project. These clients are all rich in those very things, and any one would be an excellent addition to your Git workflow.

The following are some of the best graphical Git clients for Linux.

1. Git Cola

Git Cola has been around for a decent amount of time, and it’s a classic example of an open-source Linux tool that does exactly what it needs to, without getting bogged down with a lot of unnecessary extras.

Git Cola is written in Python and features a GTK interface, so it integrates perfectly with most desktops. Since it’s open source, it’s also available in most distribution repositories, making it easy to update and maintain.

The interface is broken down into four panes. Each displays a separate aspect of your project’s Git repo. It lets you easily visualize the difference between commits in your files, and you can quickly navigate and browse between branches.

2. GitEye

GitEye is a cross-platform freeware client for Git. It may not be open source, but it is freely available and free to use. Interestingly, GitEye doesn’t install on your computer. Instead, it comes packaged in binary form, and you can simply run it from its own directory.

GitEye brings with it a more detailed interface. It has an excellent file tree browser to the left of the screen. GitEye also makes browsing and checking out your branches very simple. Additionally, GitEye has some neat features that allow you to track the history of a file and manage builds of a project via a build server.

3. Gitg

Gitg is the default graphical Git client for the GNOME desktop. Like many newer GNOME utilities, it’s sort of bare bones in appearance. GNOME’s minimalist design choices don’t mean that Gitg can’t do exactly what you need it to.

Gitg has a great visualization of the project’s history, and it lets you select your branch on the fly. Its commit screen is a little confusing at first, but its actually very easy to use once you get the hang of it. It presents you with the staged changes, and you can easily evaluate them right there and create your commit.

Gitg is an excellent option if you’re looking for something simple that fits right in with your desktop.

4. QGit

If Gitg is the GNOME client, QGit is the Plasma/Qt one. QGit has been around for a while, and it’s really refined its approach. QGit also has an excellent visual representation of your project’s history that’s intuitive to navigate. You can not only see what the commit was but the affected files as well.

It also has a great file tree browser that lets you dig through your project in a snap and view files and the changes made to them by revision.

QGit taks a more classic approach to its controls. Most of them are in the toolbar to the top of the window. You can manage everything from your own commits to branches from there. It’s nothing groundbreaking but is effective.

5. SmartGit

SmartGit is another proprietary option. This time, though, it’s packaged for use on Linux systems. SmartGit is free for personal use but does require a license for the enterprise. SmartGit looks and feels a bit like an IDE. If you like programs like Netbeans and Eclipse, chances are SmartGit is for you.

It’s packed with utilities and tools, and it makes navigating your project a breeze. It also has some excellent highlighting and visualization for your commits and changes to your projects.

SmartGit’s toolbar is among the best. It makes most of your common tasks as effortless as possible while still allowing you maximum control when you need it.

All of these clients are great. The choice between them comes down to a matter of taste. Remember, you can use Git comfortably without a GUI, so this choice is all about extras. Which one appeals to you most, and do you think it will help with the way you work?

This article was first published in January 2012 and was updated in June 2023.

Nick Congleton

Nick is a freelance tech. journalist, Linux enthusiast, and a long time PC gamer.

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Character Representation In Kids Cartoons


Children or kids are interested and spending time only in play schools or kindergarten and at home, the child’s craving for knowledge or idea does not extinguish. Moreover, kids invest more time in watching TV than in any of the above-mentioned structures. And Researchers from various Universities have found or concluded that children of the age group 2–5 years watch cartoons 32 hours a week, children of the age group 6–11 years watch cartoons 28 hours a week. And Scientists have also proved that children kids not only learn or grasp from cartoons but also learn and copy the behaviour or nature of cartoon characters or personalities due to their thinking abilities. So, the role of parents is very important here to guide their kids and prevent or stop negative consequences, by explaining to children all these impacts.

What are Cartoon Stereotypes?

In the latest times, people or individuals have spoken or pointed out against certain (specific) cartoon characters as they illustrate qualities that reflect or review current or present social issues. Cartoon art illustrating racial and cultural characteristics or personalities may be based on assumed or predicted physical characteristics or alleged or claimed religious practices that have a bean of legitimacy or legality in real or actual physical characteristics or actual or real rituals.

And this sign or mark of reality makes negative stereotypes specifically effective and tough to conflict since they appear or are found to be accurate or actual in the opinion (point of view) of those who hold them. And throughout the latter or last half of the 19th century, nationality was the topic or headline of many or several magazine cartoons. Most of these cartoons are recognized or appreciated by today’s readers as comical. Although the history or past of racial and traditional stereotypes is not proud enough, still it is a part or segment of history.

How do Cartoon characters’ influence Children?

There are both positive and negative impacts of cartoon characters on children-

Positive Effects

It helps children get an early or primary start on learning and this can be seen or observed especially in the case of educational cartoons that teach good things to the kids.

It also helps in developing the learning and thinking power of children. Furthermore, it helps in enhancing logical as well as reasoning capability along with visual and audial processing.

It also helps in language development, creativity enhancement, encouraging laughter or smiling, and relieving stress.

Negative Effects

In many cartoons, it encourages or promotes violence among kids. Violence in cartoons can encourage or promote children to become violent in real or day-to-day life.

It also promotes rude behaviour and a Lack of sympathy, various cartoons show or have characters playing rude or disrespectful behaviour toward their parents, teachers, or elders and children try to copy or mimic the same.

It encourages the use of bad or foul language, it also promotes unsocial behaviour, and may consequence in health problems due to an inactive lifestyle.

Why is representation in Cartoons important?

Cartoon characters and animated film characters reflect or represent a vast spectrum or range of people who introduce children or kids to diverse or different cultures as well as experiences. It also teaches children to be obtaining and sympathetic towards different types of people. But most importantly, depiction or representation in cartoons teaches kids children that it’s completely fine to be themselves. If the kids watch more characters like them or similar to them, it gives or provides them confidence that there are others like them.

A child’s self-image is mainly obtained from what exactly they observe or watch around them. That’s why it is so imperious that the media they have or consume reflects or shows diversity. So it’s our responsibility to encourage cartoonists to produce or form good or decent characters playing cartoons with all social norms or values.

Who is the most Famous Cartoon Character?

Every individual has a specific role model in their life, which is very much obvious given that we all have a desired or favourite cartoon character or superhero that we aim to be like or become. Let’s have a look at some widely known and famous cartoon characters and they are-Mickey Mouse, Donald Duck, Scooby-Doo, Tom Cat, Jerry Mouse, Bugs Bunny, Daffy Duck, Snoopy, Winnie-the-pooh, etc. These characters have very powerful and extraordinary impacts on the mind of kids and even the youths enjoy watching them in their free time. Tom and Jerry is the most popular series among kids, and parents, as well as grandparents, enjoy watching this series.


Each cartoon and animated film characters portray its ideologies and aesthetic messages which are having different impact or effect on the Socialization of children. Cartoon art illustrating racial and cultural characteristics or personalities may be based on assumed or predicted physical characteristics or alleged or claimed religious practices that have a bean of legitimacy or legality in real or actual physical characteristics or actual or real rituals. Watching cartoons helps in language development, creativity enhancement, encouraging laughter or smiling, and relieving stress. It encourages the use of bad or foul language, it also promotes unsocial Behaviour and may consequence in health problems due to an inactive lifestyle. A child’s self-image is mainly obtained from what exactly they observe or watch around them. That’s why it is so imperious that the media they have or consume reflects or shows diversity.


Q1. How are cartoons used in representing the ideas?

Ans. Cartoons represent the experience of the creators or makers around the world, to entertain, induce, or express outrage.

Q2. How do cartoons help in enhancing creativity?

Ans. Cartoons enhance creativity by helping kids or students to feel interested in different fields of art and languages.

Q3. What type of cartoons should kids watch?

Ans. Kids must be encouraged to watch educational cartoons which include information like shapes, sizes, colour uses, poems, fine language, etc.

How To Measure Credit Risk With Types And Uses?

Definition of Credit Risk

Credit risk infers the possibility of a loss emerging from a borrower’s downfall to pay back a loan or meet contractual commitments. Conventionally, it pertains to the risk arising from lenders’ inability to return the owed interest and principal, impacting the cash flows and increasing assemblage costs. It’s inconceivable to predict who will default on agreements accurately. Still, a proper assessment and risk management can help you mitigate such credit risk to a remarkable extent by reducing the stringency of losses.

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When any lender extends loans such as mortgages, credit cards, or other similar loans, there is an avoidable risk that the borrower will not repay the loan amounts. Furthermore, if a company offers such credit to the customer, there’s the same risk that the customer will not pay back. It also incorporates other related risks, such as that the bond issuer may not make payment at the time of maturity and the risk occurring out of the incapacity of the insurance company to compensate for the claim. A higher level of credit risk in a profitable market will correlate with the elevated borrowing cost. Because of this, it is evaluated technically to mitigate such risk to a certain level.

How to Measure Credit Risk?

One of the modest ways to calculate credit risk loss is to compute expected loss which is calculated as the product of the Probability of default(PD), exposure at default(EAD), and loss given default(LGD) minus one.

Mathematically, it is depicted as follows-

Expected Loss = PD * EAD * (1 – LGD)

Where PD= Probability of default

EAD= exposure at default

LGD=Loss given default

Example of Credit Risk

Suppose that a bank, XYZ Bank Ltd, has given a loan of $250,000 to a real estate company. As per the bank credibility assessment, the company was rated “A” based on the industry cyclicality witnessed.

Let us formulate the expected loss for XYZ Ltd based on the details below:



Exposure at Default (EAD) $250,000

Probability of Default (PD) 1%

Loss Given Default (LGD) 68%


Expected Loss = PD * EAD * (1 – LGD)

Given, PD= 1%, EAD = $250,000, LGD = 68%

PD = 0.10% * $250,000 * (1 – 68%)

Expected Loss = $800

Types of Credit Risk

Credit risks are the reason why lending institutions undergo a lot of creditability assessments before providing credit. It can be considerably classified into three types.

Credit Default Risk: It includes losses incurred by the lender when the borrower is incapacitated from returning such amount in entire or when the borrower has exceeded 90 days from the due date but hasn’t made any payment.

Concentration Risk: Concentration risks emerge from substantial exposure to any individual or group because any unfavorable incident will likely impose significant losses. It is mainly concerned with any individual industry or company.

Causes of Credit Risk

Most lenders prefer to give loans to specific borrowers only. This causes credit concentration, including lending to a single borrower, a group of related borrowers, a particular industry, or a sector.

Credit Risk Mitigation

Institutions providing loans must consider the following points to mitigate credit risks, including:

Risk-Based Pricing: Pricing should be based on the amount of risk undertaken. Lenders can charge a high-interest rate to those more likely to default. Such practice can mitigate loss from default to a much extent.

Covenants: Lenders can inscribe stipulates on the borrower in the form of an agreement called covenants. Such as,

Periodically reporting the financial status of the borrower.

Pre-payment in case of an unfavorable change in the borrower’s debt-equity ratio or interest coverage ratio.

Diversification lenders face a high probability level in the case of small borrowers with an inevitable risk of default. Lenders can mitigate credit risks by diversifying the borrower funding pool.

Credit Insurance and Credit Alternative: Credit insurance is widely operated to mitigate credit risks. These contracts transmit the risk from the lender to the insurer in exchange for payment. The most general form of a credit derivative is a credit default swap.

Uses of Credit Risk

Credit risk analysis is a type of scrutiny to acknowledge the borrower’s ability to pay back.

Credit risks infer the ability of the individual to pay back what he owes; lenders usually perform various assessments to mitigate any loss that would arrive in the foreseeable future.

Lenders can arrive at a less quantifiable loss probability by properly evaluating such credit risks to curb the chances of loss.


A good credit risk management scheme improves the capacity to foresee, which helps evaluate the potential risk in every transaction.

The banks use the credit risks model to examine the degree of lending which can be financed to prospected or new borrowers.

Credit risk management is an alternative to traditional techniques for pricing options.

Risk management can be a very expensive liaison.

Although there are some quantitative techniques to evaluate credit risk, such decisions are inaccurate as assessing risk thoroughly is impossible.

Generally, lenders apply one rigid model to all mitigation approaches, which is wrong.


Nowadays, technical innovations have improved credit risk management. Such techniques have increased the proficiency in measuring, identifying, and regulating credit risks as a popartBasel III execution.

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