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Definition of Quant Funds

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Quant funds are used to minimize human efforts or help humans get things done more accurately and with a profit-oriented view while considering investment type or other decisions relating to the investment process. Although all the work is done digitally in Quant funds, there is still importance and a manager’s work requirement. A manager checks all the work of this process, and decisions are subject to the manager’s discretion.

How Do Quant Funds Work?

The working process of Quant funds is divided into three parts; the manager monitors all three parts.

Providing Input: This is the Quant funds’ first step or working part. This input provides to the computer system. A computer then sorts the list of all the profitable companies, yields dividends, and can grow in the future. It neglects almost all those companies with high risk, insufficient capital, and debts.

Prophesy Regarding the Company: In this second step, prophesy or estimates regarding the company’s condition or price, risk, and other factors are made.

Construction of Portfolio: After the above two steps, the next step in Quant funds is portfolio construction to know the impact of funds on each other. It also helps in reducing the risk and to generate returns. A manager has the same or more responsibility than a computer because a computer helps get things done in Quant funds, but it is a manager due to which the things get done. So, without a manager, Quant funds can’t work.

Example of Quant Funds

There are many types, like ICICI Prudential funds and DSP funds, but let us take an example of a DSP fund. Such funds are used in input to get consistent earnings and a high rate of returns. So when we use DBS Quant funds in input, we will get companies providing a high return rate and consistent earning, and it will eliminate companies providing less return.

Quant Fund’s Performance

A Quant fund performs exceptionally well as it helps select the best possible investment, which yields dividends, a high rate of return, consistent payment, and helps avoid risks. Automated programs and analytical methods work in these funds, and quantitative models provide comparatively more proper and accurate results. Most of the work is done digitally; however, it cannot outshine the importance of humans because it is the manager whose decision matters the most in Quant funds.


Save Human Power: With these funds, most of the work is done by analytical methods, automated programs, and quantitative models. So, it saves human efforts, and the same human power can be utilized elsewhere.

Low Risk: The work done digitally is more accurate and correct than the work done by man, due to which there is low risk. In quant fund, the system sort companies with low risk and high rate of return.

No Impact of Human Emotions: In these funds, the work is done by computer, so there is no effect on human feelings or emotions on the investment.

Quick Decision Making: The decisions made in Quant Funds are quick as there is no delay in making decisions because it uses the best machines, minds, and algorithms to make them more accurate and quick.

Difficulty in Getting the Desired Result: As machines in Quant funds do the work, it gets difficult to get the desired result, so they are tested a number of times until they meet the desired return.

Experienced Traders Can Work More Correctly: A skilled and experienced trader can make investment decisions more correctly compared to academic researchers as skilled traders have faced all these things before and have a better knowledge market, and it can only be earned by experience, not by any research.

Too Many Conditions: Quant funds have many conditions in buying and selling stocks, and they will do trade only when it meets all the predefined conditions. Due to this, a good stock is left unpurchased if it can’t meet other conditions.

Ever-Changing Market: The market is dynamic. It is ever-changing, and the work carried out in Quant funds purely depends on historical data. So it may prove to be wrong sometimes.

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The Us Is Making Its Biggest Investment In Broadband Internet Ever

Last Friday, the House of Representatives passed a historic infrastructure bill, which includes $1.2 trillion allocated towards supporting planes, trains, energy systems—and the largest investment ever for broadband internet, to the tune of $65 billion. President Biden is expected to sign it into law on Monday.

More than 30 million Americans live in areas with no broadband infrastructure, meaning their access to high speed internet is limited. This is a bipartisan issue, and its effects were felt most during the early stages of the COVID-19 pandemic, when employees worked from home and kids went to school online. 

“This is something both sides of the political aisle have talked about for a long time,” says Kevin DeGood, director of infrastructure policy at the Center for American Progress. “This bill is in line with the sort of rough estimates of what it will take to try to bring broadband internet to everybody in America.”

Here’s what you need to know about what this bill means for internet access.

What will the bill do?

The government has allocated $42.4 billion towards a Broadband Equity Access and Deployment Program, which is just what it sounds like, says DeGood. In areas without internet service, or with spotty, intermittent service, there will be an auction in which private companies can bid on how much money they would need in order to build out real broadband internet access. 

The Pew Research Center consistently finds that affordability is a huge barrier to broadband adoption in the United States. A program called the Affordable Connectivity Fund seeks to address this, allocating $14.2 billion to provide a $30 monthly subsidy to bring down the cost of monthly internet access charges for households that are at or below 200 percent of the federal poverty line. This program is a continuation of the $3.2 billion Emergency Broadband Benefit Program, or EBBP, started during the pandemic to help low-income Americans get online.

Two billion dollars will go towards making sure indigenous communities have access to the internet, and $2.75 billion will go towards “digital equity plans,” like computer labs for your local library.

Did COVID-19 spur this?

The pandemic definitely played a role in pushing this bill to pass. “I think we’ve known for a long time that access to broadband was unevenly distributed,” Tejas Narechania, faculty director at the Berkeley Center for Law & Technology, says. “But the pandemic, working from home, schooling from home, ordering online, and relying on streaming services for entertainment sharpened our focus on the need for reliable internet everywhere.”

Narechania points out that the EBBP benefit, which started during the pandemic, is what has been modified and extended in this bill. But the EBB offered households subsidies of $50, while this new bill will only offer a subsidy of $30, so some households will have to pay $20 more out of pocket for internet service.

“But the program was due to expire, so these consumers are in fact better off than they otherwise would have been,” says Narechania. 

Will this bill be enough to get internet access to everyone?

Experts have made different estimates on how much it would cost to get wall-to-wall coverage nationally. It’s tricky to know how much this bill will narrow the digital divide because we don’t have accurate maps of where service is or isn’t, says DeGood, because of the nature of the technology. 

One of the provisions in the bill is to give the government more authority to demand better data from these private network providers. Unlike road maps, where experts can look at a map and see where there is or isn’t a road, with the internet, experts can examine a map and see that fiber optic cable has been laid down, but not know who is accessing that cable. 

Our estimate is “based on guesses as to whether or not people are being served based on fiber maps and other wireline technology,” says DeGood. Just because a line might pass by someone’s property doesn’t mean they automatically have internet access. 

“Based on the best estimates that are out there, this $65 billion should probably get the job done,” says DeGood. “But if it’s a little bit short, I have every reason to believe that Congress will come back and spend more in future years if there are gaps left.”

Is this changing how we view the internet?

In 2023, the UN General Assembly declared internet access “a human right.” But for a long time, the internet was seen more as an optional add-on than a necessity. But this could be the beginning of a shift in the way we see the internet, says DeGood, looking at it as more of a public good—like electricity or water—than a private luxury.

Adie Tomer, senior fellow in the Metropolitan Policy Program at the Brookings Institution, thinks the internet can indeed now be compared to a utility like electricity. “No one living in a modern economy right now can imagine a day without electricity,” he says. “From charging your phone to the dishwasher, everything runs on the electric grid. And as of March 2023, broadband became an essential utility for Americans.”

But unlike electricity, Timer says broadband is a privately run utility service that is highly underregulated, specifically lacking regulation around a universal mandate to provide affordable and ubiquitous service.

And broadband access is one of the most pressing issues in our society today. “This is easily the infrastructure sector with the biggest gaps in the United States,” says Tomer. “So it is really, really important that we get to work on this.”

Early Humans And The Making Of Tools


The early human beings were hunter-gatherers and dependent mostly on food hunting. These hunter-gatherers used to live in a small band of people, a maximum of 100-150 people. They used to roam here and there in search of food.

There were many archaic humans there in the early age of humanity. There were Neanderthals, homo sapiens, homo Rhodesians, etc. At the start of the stone age around 50000 BCE, only homo sapiens survived and started dominating the earth. Homo sapiens are known as early modern humans.

Early Modern Human Lifestyle

Early modern humans are known as homo Sapiens or human beings. These homo sapiens are the ancestors of the humans currently living on the planet earth. This human being is the only surviving human species and currently dominates the planet earth.

The lifestyle of modern human beings started to develop in the early stone age.

Stone age – The stone age is a period of roughly between 5,00,00 BCE to 4000 BCE, in this age the primary work of human beings was hunter-gathering.

The stone age is further divided into three periods −

Old stone age or Palaeolithic age.

Middle stone age or Mesolithic age.

New stone age or Neolithic age.

Old Stone Age or Palaeolithic Age

This period started with the growth of human beings and their evolution. The era was around 500,00 BCE to 10,000 BCE, the early stone age was further subdivided into three stages −

Early old stone age

Middle old stone age

Upper old stone age

Stone Age Hut

Middle Stone or Mesolithic Age

The period between the 10000 BCE to 8000 BCE is known as the middle stone age. In this period hunter-gathers started to develop new types of stone and bones for hunting.

New Stone Age or Neolithic Age

This stage started around 8000 BCE and ended around 4000BCE with the rise of agriculture and other metals such as copper/ bronze and iron. In this age, hunters-gatherers started to use stone blades, etc.

Fire and Debate Around Which Hominid Started Cooking

An American anthropologist, Richard Wrangham has studied the origin of the fire and the development of humans. He has argued that it was Homo Erectus that developed a fire somewhere 1.8 million years ago; the homo sapiens and Neanderthals have learned from the homo Erectus.

Fire was the revolutionizing invention of the human; it is said that what separates humans from all other living beings are their ability to control fire. Only human intelligence can burn and control fire.

HE argued that before the invention of fire, human teeth were too big, and the digestive system was too complicated with a small brain. But since humans started to cook, the size of teeth started becoming smaller, and the digestive system became less complicated because the intestines can easily digest cooked food. The Brain now has more cognitive energy to use, this has made the human brain bigger.

Which Early Humans Made Tools?

Recently around 2023 the early stone tools have been found at the bank of lake Turkana(Kenya). The carbon dating of stone tools suggested that they are around 3.3- million-year-old. The finding suggests that the earliest human species that have used these tools are Australopithecus afarensis or Kenyanthropus platyops. Until recently it was believed that homo Habilis were the first humans to make tools but now it has been suggested that homo fossils(homo Erectus) were the first people to use the tools.

Kenyanthropus Platyops

Rama, Kenyanthropus platyops IMG 2945-white, CC BY-SA 3.0 FR

How Did Early Humans Use the Tools?

Early humans used the tool mainly for hunting, cooking, and making a ditch. The primary source of energy for humans was hunting, that’s why their tools were for hunting most of the time. The early humans made the tools by craving the stone, they carved stone in such a way that one side of the tool has a narrow shape and the other side was used for handling.

The early humans had all types of tools necessary to kill the animal for food. Initially, the hunter-gathers started to use raw stone to hunt the animal, but with time they started to develop the techniques to cut the stone in such a way that makes it a better tool −

Direct percussion flaking techniques − This technique is used to directly hit one stone with another stone to get the shape by breaking it.

Indirect percussion flaking techniques − This technique is used to make more sophisticated tools. In this technique, the cutting is done through indirect hitting.

Grinding and polishing The techniques are used to make blades, bows, arrows, etc. and polishing is sometimes used to make it sharp and give it aesthetic value.


Early human beings started using tools for their day-to-day needs somewhere 1.8 million years ago, there were many species of humans on the planet, and all species except homo sapiens survived till the end of the stone age. There are many theories as to why only homo sapiens have survived, but since the domination of homo sapiens started on the earth, they have changed the nature of the earth.

The early human beings were hunter-gatherers, dependent on hunting for energy needs. To hunt animals, human beings started making sophisticated tools, the development of tools of humans are classified by scholars in the various epoch of human development, for example, the old stone age of human history has tools that are not sophisticated. The stone age succeeded with the copper, bronze, and iron age. In all three ages, the tools of human beings have changed. The society of hunter-gathers was usually a tribal society, the band of some 40-50 people used to roam here and there in search of food. The culture of tribes was not static as they are changing the pattern of hunting, staying, and eating.


Q1. What is known as the agricultural revolution?

Ans. The agricultural revolution is the age of invasion of agriculture by human beings. Just after the end of the stone age, human beings started settling in one place to grow crops. The agricultural revolution has completely changed the lifestyle of human beings. Agriculture has given rise to private property, civilization, and city-states.

Q2. What do you mean by the bronze age?

Ans. The period after the end of the stone age is known as the bronze age. The period of the bronze age is roughly between 3300 BCE to 1200 BCE, in this age humans discovered bronze, a type of metal for use in day-to-day life.

Q3. What do you mean by Iron age?

Ans. The iron age is the period after the bronze age, this is the last period in the 3-period system of early human beings. The Iron age is known for the use of Iron, a hard metal that will help human beings in performing daily activities.

Q4. Which was the first civilization on the earth?

Ans. The first modern civilization on earth is known as the Mesopotamian civilization, this civilization started during the bronze age. The civilization was concentrated on the Tigris and Euphrates rivers in present-day Iraq.

Mike Eruzione And The Making Of A Miracle

Mike Eruzione and the Making of a Miracle

In an excerpt from his new book, timed to the 40th anniversary of the US Olympic hockey team’s stunning upset of the Russians in 1980, BU alum, Olympic hockey hero, and US team captain Mike Eruzione takes readers inside the final desperate minutes of the game

I gathered the puck and turned toward the net, putting the puck on my forehand.

I was in the high slot—the exact same spot I had been in when I had scored in Madison Square Garden two weeks before, when I’d fired at the left post and beat the Soviet goalie Vladislav Tretiak.

Out of the corner of my eye, I saw both John Harrington and Billy Baker crashing toward the net.

The options came to me in a split second.

If the defenseman stayed, I’d use him as a screen to block the goalie’s view. He dropped to his knees to block the shot.

I had an opportunity to make a play.

Moving to my right, I pulled the puck a bit and fired it back the other way.

Toward the left post.

“Just get it on net,” I said as I followed through on the shot. I lost the puck. I couldn’t see it. What I saw was the net.

The back of the net suddenly bulged out, punched back by something. It took a moment to realize it. But then I saw the fans behind the goal leaping up out of their seats, hands in the air, and I knew. The roar was deafening.

With every stop in play, the cheering revved up again. “USA! USA! USA!” There was incredible energy in the building, and it was going from us on the ice to the crowd, and they gave it right back to us in the chants and cheers. It was strange, though. When I was on the ice, I was so focused on playing that I couldn’t hear the crowd, I couldn’t hear anything. But when I was on the bench, the crowd, the “USA!” chant, was the only thing I could hear.

The Soviets gained control of the puck off the face-off and threw it into our zone, but Mike Ramsey cleared it. Harrington took the puck at center ice, skated in, and fired a wrist shot. The goalie gloved it, forcing another whistle and another face-off in their zone, with 3:23 left. Each face-off in their end was good for us. The more ice we could keep between the Soviets and our goalie Jim Craig [Wheelock’79], the better.

Mark “Magic” Johnson, Dave Silk [CAS’80, MET’92, Questrom’93], and Robby McClanahan went over the boards. They lined up against the three oldest guys the Soviets had. The two young guys who’d given us the most trouble were on the bench. This late in the game, I liked the matchup.

The Soviets again took the puck into our zone, but they couldn’t even get a shot off. They were gasping for air. Bill Baker stole the puck and carried it out. At the far blue line, a whistle. We went offsides, but it was another chance to catch a breather and change lines.

There was 2:31 left to play. Our coach Herb Brooks kept rolling four lines. The Soviets got control of the puck, but our guys swarmed them, bottled the Soviets into their own zone. Frustrated and tired, the Soviets iced it.

Now there was just 1:59 to play and another line change. Mark Wells’s line came to the bench, and my line went out for the face-off. They got control and threw the puck out to center ice. Billy Baker threw it right back in. Steve Christoff chased the Soviets on the forecheck—and they did it again. The Soviets iced it. The greatest hockey team in the world was behind by a goal in the Olympics, and they were panicking.

Only 1:29 to play now. The crowd was going insane, on their feet, cheering as loud as ever. “USA! USA! USA!” No one was sitting. Mark Johnson’s line replaced us. Again they lined up against the same guys: Herb held one finger up in the air to remind Mark, Dave, and Robby to send only one forward into the Soviet zone on the forecheck. The other two should stay back. Be smart. Be defensive.

I sat on the bench, my chest heaving after my shift. I was thinking that the Soviets would try to get the puck into our end and then pull their goalie for an extra attacker on this shift. That’s what you do when you’re down by a goal with a minute left: you pull the goalie. If we had been trailing, Herb would have brought Jimmy Craig back to the bench and tried to get Mark Johnson on the ice as much as possible. We had a plan for this situation. But had the Soviets ever been down with a minute left? Had they ever had to pull their goalie?

Mike Eruzione on His Game-Winning Goal

Watch the video


The Soviets won the face-off. Vladimir Petrov carried the puck to our blue line and slid the puck into the zone. It had barely enough steam to reach the net, and Jimmy just pushed it to the corner. But it counted as a shot on goal. In fact, it was incredible. It was the first shot on goal the Soviets had gotten in more than four minutes. This was the high-powered Soviet team that had averaged ten goals a game. In the most crucial part of the game, we held the Soviets without a shot for almost five minutes.

Thirty seconds left. Petrov got the puck at the red line and fired a slap shot at Jimmy—again from seventy feet away. It might as well have been from 170 feet away. Jimmy saw it all the way, came out, and kicked it to the boards. We didn’t realize it then, but that would be the Soviets’ final shot on goal of the game. In the final six minutes, they got three shots on Jimmy—one was actually a dump-in that barely amounted to a shot. The other two were slap shots by Petrov from outside the blue line. Herb had told us to think of the game in five-minute segments. In the last of those segments, the Russians didn’t get a single shot from inside our zone.

I was standing up on the bench now, yelling to the guys on the ice. “Come on, get it out!” We were all yelling, banging our sticks on the boards. Herb was just behind us, still staring with no hint of emotion.

Ten seconds left. I wasn’t ready to celebrate yet. We had scored against Sweden in the last minute. “Get it out! Get it out!” I was saying to myself. “It’s not over until we get it out.”

“Do you believe in miracles? Yes!”—one of the greatest calls in sports.

Everyone charged over the boards. Dave Christian and Billy Baker got to Jimmy first and knocked him to the ice. Neal flung his stick straight up into the air. I whipped mine around and let it go to the rafters. Somehow Neal Broten and I came together behind the pile and hugged as sticks clattered back down. Jack O’Callahan [CAS’79] and Mike Ramsey hugged and fell to the ice, Rammer on his back, Jack kneeling with his arms thrust into the air, shouting out in jubilation, revealing his missing teeth. It is that scene, with OC and Rammer in the foreground and the pile on Jimmy in the background, that would become the picture everyone remembers, the picture that comes to everyone’s mind when they hear “Miracle on Ice.”

“It took a moment. But then I saw the fans behind the goal leaping up out of their seats…and I knew. The roar was deafening.”

It was delirious. Steve Christoff hugged Mark Pavelich. Baker swung his arms around Craig Patrick. I left Neal and found Robby. Rammer got up and hugged Steve Janaszak. OC turned to find someone to grab and shake. Herb wasn’t on the ice with us. The second the game had ended, he had left the bench and disappeared down the tunnel.

On the ice, I looked at the scoreboard, and one thought ran through my mind.

In the video above, Mike Eruzione scores the thrilling, game-winning goal. Pictured above, Mike Ramsey (center) has the puck. Photo by Henry Zbyszynski

I can’t believe it, I said to myself even as I hugged one teammate and the next and the next.

I can’t believe it.

I can’t believe we beat the Russians.

The Russians. They watched, stared, from their blue line.

They were probably asking themselves the same thing: Did this really just happen? Finally we got ourselves together and lined up for the postgame handshake. I think maybe the Soviets were somehow relieved. Maybe they could finally go back home and relax and be just another hockey team, not have to be perfect all the time. Maybe it was a relief to them, because I swear, a couple of the Soviets in that handshake line were almost smiling.

Then the four of us found one another. It wasn’t planned, it just happened. OC got to Jimmy first. Dave Silk joined them, throwing his left arm around Jimmy’s shoulders and his right around Jack’s. I was the last to arrive. A photographer caught the moment. The four of us are practically nose to nose. Silky is on the right, reaching behind Jimmy, grabbing my jersey, pulling me in. I’m on the left, shouting with joy. Jimmy’s back is to the photographer, his face obscured, but the blue nameplate with “CRAIG” in white letters stands out on his jersey. Jack, in the center, is smiling, a gloved hand patting my head.

The BU four.

You ask any one of us about that photo, and I guarantee you’ll get the same response: “Sometimes you gotta get regional.” 

Mike Eruzione (Wheelock’77) is director of special outreach at BU. Neal E. Boudette (COM’84) is a reporter for the New York Times. He lives in Ann Arbor, Mich. 

This excerpt was reprinted with permission from HarperCollins Publishers.

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Bayesian Decision Theory – Discriminant Functions And Normal Density(Part 3)

This article was published as a part of the Data Science Blogathon


This is Part-3 of the 4-part blog series on Bayesian Decision Theory.

In the previous article, we discussed the generalized cases for taking decisions in the Bayesian Decision Theory. Now, in this article, we will cover some new concepts including Discriminant Functions and Normal Density in Bayesian Decision Theory.

For previous articles, Links are Part-1 and Part-2.

The topics covered in this article are:

1. Classifiers, Discriminant Functions, and Decision Surfaces

2. The Normal Density

Univariate normal density

Multivariate normal density


Let’s get started,

Pattern classifiers can be represented in many different ways. Most used among all is using a set of discriminant function gi(x), i=1, . . . , c. The decision of the classifier works as assigning feature vector x to class wi– if a certain decision rule is to be followed like the followed earlier i.e.

Hence this classifier can be viewed as a network that computes the c discriminant function and chooses the action to choose the state of nature that has the highest discriminant.

Fig. The functional structure of a general statistical pattern classifier includes d inputs and discriminant functions gi(x). A subsequent step determines which of the discriminant values is the maximum and categorizes the input pattern accordingly. The arrows show the direction of the flow of information, though frequently the arrows are omitted when the direction of flow is self-evident.

      Image Source: Google Images

Thus the choice of a discriminant function is not unique. We can temper the function by multiplying by the same positive constant or by shifting them by the same constant without any influence on the decision. These observations eventually lead to significant computational and analytical simplification. An example of discriminant function modification with tempering with the output decision is :

There will be no change in the decision rule.

Fig. In this two-dimensional two-category classifier, the probability densities are Gaussian, the decision boundary consists of two hyperbolas, and thus the decision region R2 is not simply connected. The ellipses mark where the density is 1/e times that at the peak of the distribution.

Image Source: Google Images

  The Two Category Case

g(x) ≡ g1(x) − g2(x),

Hence dichotomizer can be seen as a system that computes a single discriminant function g(x) and classifies the x according to the sign of the output. The above equation can be further simplified as

Normal Density

Further in this article, we get a brief exposition of multivariate normal density.

Univariate Normal density

The continuous univariate normal density p(x) can be given as,

The expected value of x or the average or mean over the feature space.

𝜇 ≡ E [ x ] = Integration (from – ∞ to ∞ ): xp(x) dx

Variance is given as

σ2 ≡ E [ (x − μ)2 ] = Integration (from – ∞ to ∞ ): (x − μ)2p(x) dx

This density is fully governed by these two parameters: its mean and variance. We also write p(x)=N (𝜇, 𝜎2) which is read as x is distributed normally with the mean of 𝜇 and variance 𝜎2

The entropy of any distribution is given by

H(p(x)) =   Integration (from – ∞ to ∞ ): p(x) ln p(x) dx

Which is measured in nats, but if log2 is used then the unit is a bit. The entropy of any distribution is a non-negative entity that given as an idea of fundamental uncertainty in the values of instances selected randomly from a distribution. As matter of fact, the normal distribution has the maximum entropy of all distribution having a given mean and variance.

Why Gaussian is Important?

The central limit theorem, states that the aggregated effect of a large number of small random independent disturbances will eventually lead to Gaussian distribution. Many real-life patterns -from handwritten characters to speech sounds — can be viewed as some ideal or prototype pattern corrupted by a large number of random processes.

Multivariate Normal Density

A multivariate normal distribution in dimensions of d is given as,


x = d-component column vector

μ = d-component mean vector

Σ = d by d covariance matrix

(x – μ)t is the transpose of (x – μ)

Some basic prerequisites are

Inner product 

atb = sum(from i=1 to i=d): aibi


μ ≡ E [ x ] = Integration (from – ∞ to ∞ ): xp(x) dx

Covariance matrix

Σ ≡ E [(x − μ)(x − μ)t] = Integration (from – ∞ to ∞ ): (x − μ)(x − μ)tp(x) dx

If xi is the ith component of x, μi the ith component of μ, and σij the ijth component of Σ, then

μi = E [ xi ]


σij = E [(xi − μi)(xj − μj)]

The covariance matrix holds a very important part of the discussion. The covariance matrix is always positive semidefinite and symmetric, here we will restrict our attention to the case in which the covariance matrix is positive definite, for the determinants to be positive.

σii are the variances and σij are the covariances. If σij =0 then xi and xj are statistically independent.

This ends today’s discussion!

In the next article, we will discuss the calculation of discriminant functions for normal density under different conditions and try to interpret all of those functions, and see the uses of all those cases in the real-life use-cases of Bayesian Decision Theory.

  Discussion Problem

Note: Here N(x, y) indicates the normal density.

  End Notes

Thanks for reading!

Please feel free to contact me on Linkedin, Email.

About the author Chirag Goyal

Currently, I am pursuing my Bachelor of Technology (B.Tech) in Computer Science and Engineering from the Indian Institute of Technology Jodhpur(IITJ). I am very enthusiastic about Machine learning, Deep Learning, and Artificial Intelligence.

The media shown in this article are not owned by Analytics Vidhya and is used at the Author’s discretion.


How Does Investment Partnership Work?

What is an Investment Partnership?

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How does Investment Partnership work?

In an investment partnership, a fund manager becomes a partner in the business by investing cash and only then earns the authority to exercise influence on the decision-making of the business. Therefore, the fund manager’s capital contribution to the business should be higher than that of the other general limited partners, who are mere investors and have no say in the investment decisions. The fund manager becomes eligible for additional profit distribution over and above the interest holding (owing to invested capital) if the profits derived from the business exceed a certain level of returns, which is also known as the hurdle rate.

Examples of Investment Partnership

Investment partnership businesses usually invest in alternative investment funds. Some of the most common examples of such investments are mentioned below:

1. Hedge Fund

Typically, institutional investors, high-net-worth individuals, and other accredited investors invest in this type of financial instrument. This investment vehicle is usually used to hedge risk by simultaneously buying and shorting assets in a long-short equity strategy, hence the “hedge fund.”

2. Private Equity

It is a type of alternative investment class that comprises capital that is invested in unlisted companies. Generally, this type of fund either directly invests in private companies or buyout public companies leading to their delisting from the stock exchange. It is considered to be a high-risk, high-return investment.

3. Venture Capital 4. Mutual Fund

In this type of financial instrument, the fund manager pools money from a large number of investors and then invests the raised capital in different types of financial securities, such as equity stocks, bonds, short-term debt funds, etc. The collective holdings of a mutual fund are popularly called its portfolio.

How is an Investment Partnership taxed?

An investment partnership enjoys favorable tax treatment, as reflected from the instances mentioned below.

In North Carolina, a firm operating as an investment partnership is not considered to be doing business. Hence, such a firm is not mandated to file an income tax return, nor is it liable to pay any income tax on behalf of its non-resident partners.

In Illinois, an investment partnership is not required to pay replacement tax for tax years ending on or after December 31, 2004. Also, its non-resident partner needs to pay tax on the income passed through the investment partnership, only if the partner’s contribution to the business is made in connection with a business conducted only partially within Illinois.

Advantages of Investment Partnership

An investment partnership falls in the category of alternative investment funds, which means the investments go into risky securities that offer higher return potential.

The regulations are limited for these investment funds. Hence, the fund managers enjoy a greater degree of discretion regarding managing the investments to generate higher returns.

These investment funds, in many cases, put their money into companies that are just in their initial phase of business. These financing options help these start-ups secure their growth funding.

One of the best things about investment partnerships is that the general partners or investors outsource the fund management to professionally trained fund managers.

The profit distribution generated from the business enjoys favorable tax treatment.

First, in most cases, the general partners don’t possess much knowledge about the business, especially financial statements. Likewise, the investors have a very limited idea about how the fund managers are managed.

Given these are high-risk, high-return investments, a wrong move with regard to an investment strategy can prove lethal and may wipe out the entire wealth accumulated over the years.

Small retail investors seldom get an opportunity to invest in an investment partnership business as the fund managers usually seek funding from wealthy and accredited investors only.

Key Takeaways

Some of the key takeaways of the article are:

In investment partnerships, more than 90% of the business assets are held in the form of investments in financial instruments. As a result, more than 90% of its income comes from these financial assets.

The fund manager invests cash in the business to become one of the partners, after which he/ she can exercise influence on the decision-making. Typically, the fund manager’s contribution is higher than that of the other general limited partners.

Investment partnership is classified as alternative investment funds. These funds invest in risky securities that offer higher return potential. Hence, even a slight mistake can wipe out the entire wealth accumulated over the years.

Usually, fund managers prefer wealthy and accredited investors over small retail investors.


Apart from providing the required growth funding to start-ups, investment partnerships help investors earn amazing returns on their investments. In this way, this business model facilitates better efficiency in the financial market. However, the general partners or investors remain exposed to significant risk due to the investments’ nature and lack of transparency.

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