When I’ve heard about the Silkroad the first time in 2012 it all began. What an exciting place, where you could buy all that forbidden stuff and they where using that strange internet money Bitcoin. I got intrigued and purchased some, just in case I need it some day. But I also read the Bitcoin whitepaper and was instantly fascinated of the concept of a trust-less and censorship resistant money. Life happens and for some reason I forgot about it, rugged myself and lost my keys. The painful memory of my lost possession hit when BTC reached the $10k mark.

Second Round

After I wanted to purchase something online and they accepted Bitcoin Cash, I re-discovered crypto in 2018 again. This was when I rugged myself the second time. Too lazy to sign up on a registered exchange, I tried a p2p platform. Well, what should I say… I was just stupid. After overcoming the obstacles and finally made my purchase, I was amazed how easy and fast the transaction went through.

To be honest, I had my problems with crypto in the beginning. I’ve invested in stocks for quite some time, but a pure digital asset was too abstract for me. Nothing to touch or look at, only 1s and 0s. So it took a while until I could process and understand this kind of innovation. But the curiosity kept me digging and sucked me down the rabbit hole.

Only pushing around coins and use them for payments is kinda boring and the DeFi, NFT and the entire Web3 space got me hooked. Today I’m literally obsessed and crypto fills every free minute I have. This is the future and is a once in a decade opportunity. I believe Web3 has the power to shape the world and can change the life of many people for the better.

I made a lot of mistakes through my journey in crypto and Web3, but I’m a strong believer in taking responsibility and creating your own reality. This space gives me a purpose and this is why I want to educate the people around me.

An amalgamation is a combination of two or more companies into a new entity. Amalgamation is distinct from a merger because neither company involved survives as a legal entity. Instead, a completely new entity is formed to house the combined assets and liabilities of both companies.

The term amalgamation has generally fallen out of popular use in the United States, being replaced with the terms merger or consolidation even when a new entity is formed. But it is still commonly used in countries such as India.

Understanding Amalgamations

Amalgamation typically happens between two or more companies engaged in the same line of business or those that share some similarity in operations. Companies may combine to diversify their activities or to expand their range of services.

Since two or more companies are merging together, an amalgamation results in the formation of a larger entity. The transferor company—the weaker company—is absorbed into the stronger transferee company, thus forming an entirely different company. This leads to a stronger and larger customer base, and also means the newly formed entity has more assets.

Amalgamations generally take place between larger and smaller entities, where the larger one takes over smaller firms.

The Pros and Cons of Amalgamations

Amalgamation is a way to acquire cash resources, eliminate competition, save on taxes, or influence the economies of large-scale operations. Amalgamation may also increase shareholder value, reduce risk by diversification, improve managerial effectiveness, and help achieve company growth and financial gain.

On the other hand, if too much competition is cut out, amalgamation may lead to a monopoly, which can be troublesome for consumers and the marketplace. It may also lead to the reduction of the new company's workforce as some jobs are duplicated and therefore make some employees obsolete. It also increases debt: by merging the two companies together, the new entity assumes the liabilities of both.

Pros

• Can improve competitiveness

• Can reduce taxes

• Increases economies of scale

• Potential to increase shareholder value

• Diversifies the firm

Cons

• Can concentrate too much power into a monopolistic firm

• Can lead to job losses

• Increases the firm's debt load

Amalgamation Procedure

The terms of amalgamation are finalized by the board of directors of each company. The plan is prepared and submitted for approval. For instance, the High Court and Securities and Exchange Board of India (SEBI) must approve the shareholders of the new company when a plan is submitted.1

The new company officially becomes an entity and issues shares to shareholders of the transferor company. The transferor company is liquidated, and all assets and liabilities are taken over by the transferee company.

Example of Amalgamation

In late 2021, it was announced that media companies Time Warner and Discovery, Inc. would combine in a deal worth an estimated $43 billion. Owned by AT&T, Time Warner (which the telecom company acquired in 2018) would be spun off and then amalgamated with Discovery. The new entity, known as Warner Bros. Discovery, Inc., is expected to close at some point in late 2022 and will be headed by Discovery CEO David Zaslav.2

Types of Amalgamation

One type of amalgamation—similar to a merger—pools both companies’ assets and liabilities, and the shareholders’ interests together. All assets of the transferor company become that of the transferee company.

The business of the transferor company is carried on after the amalgamation. No adjustments are made to book values. Shareholders of the transferor company holding a minimum of 90% face value of equity shares become shareholders of the transferee company.

The second type of amalgamation is similar to a purchase. One company is acquired by another, and shareholders of the transferor company do not have a proportionate share in the equity of the combined company. If the purchase consideration exceeds the net asset value (NAV), the excess amount is recorded as goodwill. If not, it is recorded as capital reserves.

ZZZZ Best was a carpet cleaning and restoration company founded by Barry Minkow that served as a front for a famous Ponzi scheme. The company went public in December 1986 and was quickly valued at over $300 million. Within just seven months of the initial public offering (IPO), however, ZZZZ Best was bankrupt and its assets were auctioned for approximately $64,000.1

KEY TAKEAWAYS

• ZZZZ Best was a company set up as a front for a Ponzi scheme.

• Its founder Barry Minkow engaged in a range of criminal acts including insurance scams and check kiting.

• Minkow and his business associate Tom Padgett set up a fake company called Interstate Appraisal to defraud financial institutions out of millions.

• Minkow was eventually sentenced to 25 years in prison for fraud. When released, he ended up convicted for fraud again and sentenced to five more years.

• The fraud was discovered by a woman who chased the paper trail, al due to an overcharge of only a few hundred dollars.

Understanding ZZZZ Best

Barry Minkow formed ZZZZ Best in his parents' garage. The business performed poorly and 15-year-old Minkow was often inundated with customer complaints and supplier collection requests. To create an illusion of a profitable business, Minkow began committing criminal acts, such as check kiting, theft, insurance scams, and fraud, to fund operations and pay suppliers.2

Within a few years of ZZZZ Best's inception, Minkow launched fictitious insurance restoration and appraisal businesses. While active, ZZZZ Best was at the center of a credit card scheme involving over $70,000 in fraudulent charges. Although Minkow assigned blame to contractors and employees, he repaid all of the victims except for one: a homemaker swindled out of a few hundred dollars.3

The Scheme and the Downfall

Minkow and business associate Tom Padgett created a fictitious company, Interstate Appraisal Service, to defraud banks and other lending institutions out of millions of dollars. Tom Padgett, an insurance claims adjuster, conspired with Minkow to forge documents crediting ZZZZ Best for restoration work and use Interstate Appraisal Services as the source to verify the claims. Increasingly, investors and bankers developed an interest in ZZZZ Best based on fraudulent financial statements produced by Minkow’s firm.2

Barry Minkow claimed his fraudulent actions were driven by a need to repay organized crime.

As the Ponzi scheme continued, ZZZZ Best experienced significant cash flow problems. As a solution, Minkow planned to acquire KeyServ, Sears' authorized carpet cleaner, for $25 million. According to Minkow, the revenues from KeyServ would provide enough cash flow to end the Ponzi scheme. Before the deal was closed, the jilted homemaker sparked a campaign against ZZZZ Best that would expose more than the fraud committed against her.4

The L.A. Times featured her story, which caused ZZZZ Best's stock price to decline sharply. Lenders began to call their loans and more investigations commenced, unraveling Minkow's dark web of deceit and fraud. Eventually, the truth behind the fictitious companies was revealed and the Ponzi scheme was exposed.

How Auditors Were Misled

To launch an IPO, the Securities and Exchange Commission (SEC) requires a firm to compile a prospectus, which must include a set of audited financial statements. Independent certified public accountant (CPA) firm Ernst & Whinney (now Ernst & Young) audited ZZZZ Best's financials to provide an opinion as to whether the financial statements were free of material misstatement. 

Assuming an independent third party provided the paperwork, the CPAs used false appraisal documents to perform its audit. When the CPA firm requested to visit a building refurbishing customer site, Minkow and his associates rented a building and created a bogus customer job site.5

Minkow After ZZZZ Best

In January 1988, Minkow and 11 other company insiders were indicted by a grand jury on counts of racketeering, money laundering, securities fraud, embezzlement, mail fraud, bank fraud, and tax evasion. Separately, Minkow was also indicted on counts of credit card fraud. Approximately a year later, Minkow was found guilty on all charges, was sentenced to 25 years in prison, and was ordered to pay over $26 million in restitution.5

After his early release in 1995, he became an ordained minister and served as a pastor of a church in California. Minkow informally investigated and reported other Ponzi schemes. From this success, he formed the fraudulent Fraud Discovery Institute.4

In 2011, he was again convicted for fraud and sentenced to five years in prison. It was discovered that while filming and producing his biography, he simultaneously was using his anti-fraud company to short stocks of companies he was investigating.6 A few years later, Minkow was sentenced to an additional five years in prison for defrauding his church and tax evasion. His restitution balance has increased ten-fold to $612 million.4

ZZZZ Best Frequently Asked Questions

What Accounting Procedures Did ZZZZ Best Fail to Follow?

ZZZZ Best failed because it was a Ponzi scheme so, in essence, the company followed almost no proper accounting procedures. However, it took the company going public before the fraud was discovered so there is an argument that exists that Minkow was quite skilled with his accounting.

How Was the ZZZZ Best Fraud Discovered?

Minkow was visited by his past when a homemaker who was overcharged just a few hundred dollars by Minkow tracked down a few others who Minkow had defrauded. When the homemaker located the others, she passed her findings onto the Los Angeles Times. The newspaper then ran a story exposing Minkow's relatively minor fraud. This caused a domino effect and ZZZZ Best was quickly outed as a Ponzi scheme.

When Did Barry Minkow Get Out of Prison?

Barry Minkow was released from prison most recently in 2018 after serving time for insider trading and embezzlement from his church. Before that conviction, he served a significant jail sentence from 1989 to 1995, being released only six years into his 25-year sentence.

Is There a Barry Minkow Movie Being Made?

There was a Barry Minkow movie made in 2011 that was eventually released in 2018, titled Con-Man. During the filming, Barry was arrested and pleaded guilty to insider trading charges. In January of 2022, a docuseries titled King of the Con was released on Discovery+.

The Bottom Line

Barry Minkow's company ZZZZ Best committed serious fraud and is one of the best-known Ponzi schemes in history. Even though Barry was released from prison early, he squandered the second chance and eventually ended up in much bigger trouble and ended up back in prison. Although there are multiple cinematic versions of his story, he is by no means a role model. ZZZZ Best was an excellent company on paper and at one point was valued over a quarter billion dollars, then bankrupted shortly afterward.

Learn the Basics of Trading and Investing

Looking to learn more about trading and investing? No matter your learning style, there are more than enough courses to get you started. With Udemy, you’ll be able to choose courses taught by real-world experts and learn at your own pace, with lifetime access on mobile and desktop. You’ll also be able to master the basics of day trading, option spreads, and more. Find out more about Udemy and get started today.

Z-scores reveal to statisticians and traders whether a score is typical for a specified data set or if it is atypical. Z-scores also make it possible for analysts to adapt scores from various data sets to make scores that can be compared to one another more accurately.

Edward Altman, a professor at New York University, developed and introduced the Z-score formula in the late 1960s as a solution to the time-consuming and somewhat confusing process investors had to undergo to determine how close to bankruptcy a company was.1 In reality, the Z-score formula that Altman developed actually ended up providing investors with an idea of the overall financial health of a company.

Over the years, Altman continued to reevaluate his Z-score. From 1969 until 1975, Altman looked at 86 companies in distress. From 1976 to 1995, he observed 110 companies. Finally, from 1997 to 1999, he evaluated an additional 120 companies. From his findings, it was revealed that the Z-score had an accuracy of between 82% and 94%.2

In 2012, Altman released an updated version of the Z-score, which is called the Altman Z-score Plus. It can be used to evaluate public and private companies, manufacturing and non-manufacturing companies, and U.S. and non-U.S. companies.3

A Z-score is the output of a credit-strength test that helps gauge the likelihood of bankruptcy for a publicly traded company. The Z-score is based on five key financial ratios that can be found and calculated from a company's annual 10-K report. The calculation used to determine the Altman Z-score is as follows

A zero-coupon swap is an exchange of cash flows in which the stream of floating interest-rate payments is made periodically, as it would be in a plain vanilla swap, but where the stream of fixed-rate payments is made as one lump-sum payment at the time when the swap reaches maturity, instead of periodically over the life of the swap.

KEY TAKEAWAYS

• A zero-coupon swap involves the fixed side of the swap being paid in one lump sum when the contract reaches maturity.

• The variable side of the swap still makes regular payments, as they would in a plain vanilla swap.

• Because the fixed leg is paid as a lump sum, valuing a zero-coupon swap involves determining the present value of those cash flows using a zero-coupon bond's implied interest rate.

Understanding a Zero-Coupon Swap

A zero-coupon swap is a derivative contract entered into by two parties. One party makes floating payments which changes according to the future publication of the interest rate index (e.g. LIBOR, EURIBOR, etc.) upon which the rate is benchmarked. The other party makes payments to the other based on an agreed fixed interest rate.

The fixed interest rate is tied to a zero-coupon bond, or a bond that pays no interest for the life of the bond but is expected to make one single payment at maturity. In effect, the amount of the fixed-rate payment is based on the swap's zero-coupon rate. The bondholder on the end of the fixed leg of a zero-coupon swap is responsible for making one payment at maturity, while the party on the end of the floating leg must make periodic payments over the contract life of the swap. However, zero-coupon swaps can be structured so that both floating and fixed-rate payments are paid as a lump sum.

Since there’s a mismatch in the frequency of payments, the floating party is exposed to a substantial level of default risk. The counterparty that does not receive payment until the end of the agreement incurs a greater credit risk than it would with a plain vanilla swap in which both fixed and floating interest rate payments are agreed to be paid on certain dates over time.

Valuing a Zero-Coupon Swap

Valuing a zero-coupon swap involves determining the present value of the cash flows using a spot rate (or zero-coupon rate). The spot rate is an interest rate that applies to a discount bond that pays no coupon and produces just one cash flow at the maturity date. The present value of each fixed and floating leg will be determined separately and summed together.

Since the fixed rate payments are known ahead of time, calculating the present value of this leg is straightforward. To derive the present value of cash flows from the floating rate leg, the implied forward rate must be calculated first. The forward rates are usually implied from spot rates. The spot rates are derived from a spot curve which is built from bootstrapping, a technique that shows a sequence of spot (or zero-coupon) rates that are consistent with the prices and yields on coupon bonds.

Variations of the zero-coupon swap exist to meet different investment needs. A reverse zero-coupon swap pays the fixed lump-sum payment upfront when the contract is initiated, reducing credit risk for the pay-floating party. Under an exchangeable zero-coupon swap, the party scheduled to receive a fixed sum at the maturity date can use an embedded option to turn the lump-sum payment into a series of fixed payments.

The floating payer will benefit from this structure if volatility declines and interest rates are relatively stable to declining. It is also possible for the floating-rate payments to be paid as a lump sum in a zero-coupon swap under an exchangeable zero-coupon swap.

Learn the Basics of Trading and Investing

Looking to learn more about trading and investing? No matter your learning style, there are more than enough courses to get you started. With Udemy, you’ll be able to choose courses taught by real-world experts and learn at your own pace, with lifetime access on mobile and desktop. You’ll also be able to master the basics of day trading, option spreads, and more. Find out more about Udemy and get started today.

ZZZZ Best was a carpet cleaning and restoration company founded by Barry Minkow that served as a front for a famous Ponzi scheme. The company went public in December 1986 and was quickly valued at over $300 million. Within just seven months of the initial public offering (IPO), however, ZZZZ Best was bankrupt and its assets were auctioned for approximately $64,000.1

KEY TAKEAWAYS

• ZZZZ Best was a company set up as a front for a Ponzi scheme.

• Its founder Barry Minkow engaged in a range of criminal acts including insurance scams and check kiting.

• Minkow and his business associate Tom Padgett set up a fake company called Interstate Appraisal to defraud financial institutions out of millions.

• Minkow was eventually sentenced to 25 years in prison for fraud. When released, he ended up convicted for fraud again and sentenced to five more years.

• The fraud was discovered by a woman who chased the paper trail, al due to an overcharge of only a few hundred dollars.

Understanding ZZZZ Best

Barry Minkow formed ZZZZ Best in his parents' garage. The business performed poorly and 15-year-old Minkow was often inundated with customer complaints and supplier collection requests. To create an illusion of a profitable business, Minkow began committing criminal acts, such as check kiting, theft, insurance scams, and fraud, to fund operations and pay suppliers.2

Within a few years of ZZZZ Best's inception, Minkow launched fictitious insurance restoration and appraisal businesses. While active, ZZZZ Best was at the center of a credit card scheme involving over $70,000 in fraudulent charges. Although Minkow assigned blame to contractors and employees, he repaid all of the victims except for one: a homemaker swindled out of a few hundred dollars.3

The Scheme and the Downfall

Minkow and business associate Tom Padgett created a fictitious company, Interstate Appraisal Service, to defraud banks and other lending institutions out of millions of dollars. Tom Padgett, an insurance claims adjuster, conspired with Minkow to forge documents crediting ZZZZ Best for restoration work and use Interstate Appraisal Services as the source to verify the claims. Increasingly, investors and bankers developed an interest in ZZZZ Best based on fraudulent financial statements produced by Minkow’s firm.2

Barry Minkow claimed his fraudulent actions were driven by a need to repay organized crime.

As the Ponzi scheme continued, ZZZZ Best experienced significant cash flow problems. As a solution, Minkow planned to acquire KeyServ, Sears' authorized carpet cleaner, for $25 million. According to Minkow, the revenues from KeyServ would provide enough cash flow to end the Ponzi scheme. Before the deal was closed, the jilted homemaker sparked a campaign against ZZZZ Best that would expose more than the fraud committed against her.4

The L.A. Times featured her story, which caused ZZZZ Best's stock price to decline sharply. Lenders began to call their loans and more investigations commenced, unraveling Minkow's dark web of deceit and fraud. Eventually, the truth behind the fictitious companies was revealed and the Ponzi scheme was exposed.

How Auditors Were Misled

To launch an IPO, the Securities and Exchange Commission (SEC) requires a firm to compile a prospectus, which must include a set of audited financial statements. Independent certified public accountant (CPA) firm Ernst & Whinney (now Ernst & Young) audited ZZZZ Best's financials to provide an opinion as to whether the financial statements were free of material misstatement. 

Assuming an independent third party provided the paperwork, the CPAs used false appraisal documents to perform its audit. When the CPA firm requested to visit a building refurbishing customer site, Minkow and his associates rented a building and created a bogus customer job site.5

Minkow After ZZZZ Best

In January 1988, Minkow and 11 other company insiders were indicted by a grand jury on counts of racketeering, money laundering, securities fraud, embezzlement, mail fraud, bank fraud, and tax evasion. Separately, Minkow was also indicted on counts of credit card fraud. Approximately a year later, Minkow was found guilty on all charges, was sentenced to 25 years in prison, and was ordered to pay over $26 million in restitution.5

After his early release in 1995, he became an ordained minister and served as a pastor of a church in California. Minkow informally investigated and reported other Ponzi schemes. From this success, he formed the fraudulent Fraud Discovery Institute.4

In 2011, he was again convicted for fraud and sentenced to five years in prison. It was discovered that while filming and producing his biography, he simultaneously was using his anti-fraud company to short stocks of companies he was investigating.6 A few years later, Minkow was sentenced to an additional five years in prison for defrauding his church and tax evasion. His restitution balance has increased ten-fold to $612 million.4

ZZZZ Best Frequently Asked Questions

What Accounting Procedures Did ZZZZ Best Fail to Follow?

ZZZZ Best failed because it was a Ponzi scheme so, in essence, the company followed almost no proper accounting procedures. However, it took the company going public before the fraud was discovered so there is an argument that exists that Minkow was quite skilled with his accounting.

How Was the ZZZZ Best Fraud Discovered?

Minkow was visited by his past when a homemaker who was overcharged just a few hundred dollars by Minkow tracked down a few others who Minkow had defrauded. When the homemaker located the others, she passed her findings onto the Los Angeles Times. The newspaper then ran a story exposing Minkow's relatively minor fraud. This caused a domino effect and ZZZZ Best was quickly outed as a Ponzi scheme.

When Did Barry Minkow Get Out of Prison?

Barry Minkow was released from prison most recently in 2018 after serving time for insider trading and embezzlement from his church. Before that conviction, he served a significant jail sentence from 1989 to 1995, being released only six years into his 25-year sentence.

Is There a Barry Minkow Movie Being Made?

There was a Barry Minkow movie made in 2011 that was eventually released in 2018, titled Con-Man. During the filming, Barry was arrested and pleaded guilty to insider trading charges. In January of 2022, a docuseries titled King of the Con was released on Discovery+.

The Bottom Line

Barry Minkow's company ZZZZ Best committed serious fraud and is one of the best-known Ponzi schemes in history. Even though Barry was released from prison early, he squandered the second chance and eventually ended up in much bigger trouble and ended up back in prison. Although there are multiple cinematic versions of his story, he is by no means a role model. ZZZZ Best was an excellent company on paper and at one point was valued over a quarter billion dollars, then bankrupted shortly afterward.

Learn the Basics of Trading and Investing

Looking to learn more about trading and investing? No matter your learning style, there are more than enough courses to get you started. With Udemy, you’ll be able to choose courses taught by real-world experts and learn at your own pace, with lifetime access on mobile and desktop. You’ll also be able to master the basics of day trading, option spreads, and more. Find out more about Udemy and get started today.

A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.

In finance, Z-scores are measures of an observation's variability and can be used by traders to help determine market volatility. The Z-score is also sometimes known as the Altman Z-score.

• A Z-Score is a statistical measurement of a score's relationship to the mean in a group of scores.

• A Z-score can reveal to a trader if a value is typical for a specified data set or if it is atypical.

• In general, a Z-score below 1.8 suggests a company might be headed for bankruptcy, while a score closer to 3 suggests a company is in solid financial positioning.

0 seconds of 1 minute, 55 secondsVolume 75%

1:55

Z-Score

How Z-Scores Work

Z-scores reveal to statisticians and traders whether a score is typical for a specified data set or if it is atypical. Z-scores also make it possible for analysts to adapt scores from various data sets to make scores that can be compared to one another more accurately.

Edward Altman, a professor at New York University, developed and introduced the Z-score formula in the late 1960s as a solution to the time-consuming and somewhat confusing process investors had to undergo to determine how close to bankruptcy a company was.1 In reality, the Z-score formula that Altman developed actually ended up providing investors with an idea of the overall financial health of a company.

Over the years, Altman continued to reevaluate his Z-score. From 1969 until 1975, Altman looked at 86 companies in distress. From 1976 to 1995, he observed 110 companies. Finally, from 1997 to 1999, he evaluated an additional 120 companies. From his findings, it was revealed that the Z-score had an accuracy of between 82% and 94%.2

In 2012, Altman released an updated version of the Z-score, which is called the Altman Z-score Plus. It can be used to evaluate public and private companies, manufacturing and non-manufacturing companies, and U.S. and non-U.S. companies.3

A Z-score is the output of a credit-strength test that helps gauge the likelihood of bankruptcy for a publicly traded company. The Z-score is based on five key financial ratios that can be found and calculated from a company's annual 10-K report. The calculation used to determine the Altman Z-score is as follows:4

Z-Scores vs. Standard Deviation

Standard deviation is essentially a reflection of the amount of variability within a given data set. Standard deviation is calculated by first determining the difference between each data point and the mean. The differences are then squared, summed, and averaged. This produces the variance. The standard deviation is the square root of the variance.

The Z-score, by contrast, is the number of standard deviations a given data point lies from the mean. For data points that are below the mean, the Z-score is negative. In most large data sets, 99% of values have a Z-score between -3 and 3, meaning they lie within three standard deviations above and below the mean.

Criticisms of Z-Scores

The Z-score should be calculated and interpreted with care. For example, the Z-score is not immune to false accounting practices. Since companies in trouble may sometimes misrepresent or cover up their financials, the Z-score is only as accurate as the data that goes into it.

Additionally, the Z-score isn't very effective for new companies with little to zero earnings. Regardless of their actual financial health, these companies will score low. Moreover, the Z-score doesn't address the cash flows of a company. Rather, it only hints at it through the use of the net working capital-to-asset ratio.

Finally, Z-scores can swing from quarter to quarter if a company records one-time write-offs. These events can change the final score and may falsely suggest a company is on the brink of bankruptcy.

The Fundamentals of Corporate Finance and Accounting

Whatever your learning style, understanding corporate finance and accounting is easy when you can choose from 183,000 online video courses. With Udemy, you’ll be able to learn accounting terminology and how to prepare financial statements and analyze business transactions. What’s more, each course has new additions published every month and comes with a 30-day money-back guarantee. Learn more about Udemy and sign up today.

Real gross domestic product (real GDP) is an inflation-adjusted measure that reflects the value of all goods and services produced by an economy in a given year (expressed in base-year prices) and is often referred to as constant-price GDP, inflation-corrected GDP, or constant dollar GDP.

KEY TAKEAWAYS

• Real gross domestic product (real GDP) is an inflation-adjusted measure that reflects the value of all goods and services produced by an economy in a given year (expressed in base-year prices). and is often referred to as "constant-price," "inflation-corrected", or "constant dollar" GDP.

• Real GDP makes comparing GDP from year to year and from different years more meaningful because it shows comparisons for both the quantity and value of goods and services.

• Real GDP is calculated by dividing nominal GDP over a GDP deflator.

0 seconds of 2 minutes, 37 secondsVolume 75%

2:37

Nominal vs. Real GDP

Understanding Real GDP

Real GDP is a macroeconomic statistic that measures the value of the goods and services produced by an economy in a specific period, adjusted for inflation. Essentially, it measures a country's total economic output, adjusted for price changes.

Governments use both nominal and real GDP as metrics for analyzing economic growth and purchasing power over time. This is done using the GDP price deflator (also called the implicit price deflator), which measures the changes in prices for all of the goods and services produced in an economy.

The Bureau of Economic Analysis (BEA) provides a quarterly report on GDP with headline data statistics representing real GDP levels and real GDP growth.1 Nominal GDP is also included in the BEA’s quarterly report under the name current dollar. Unlike nominal GDP, real GDP accounts for changes in price levels and provides a more accurate figure of economic growth.2

6.9%

*U.S. real GDP growth rate (annualized) during the fourth quarter of 2021, up from 2.3% growth in the third quarter. For all of 2021, real GDP grew by 5.7%, versus a 3.4% decline in 2020.3 *

Nominal GDP vs. Real GDP

Because GDP is one of the most important metrics for evaluating the economic activity, stability, and growth of goods and services in an economy, it is usually reviewed from two angles: nominal and real. Nominal GDP is a macroeconomic assessment of the value of goods and services using current prices in its measure; it's also referred to as the current dollar GDP.

Real GDP takes into consideration adjustments for changes in inflation. This means that if inflation is positive, real GDP will be lower than nominal, and vice versa. Without a real GDP adjustment, positive inflation greatly inflates GDP in nominal terms.

U.S. real GDP grew at 5.7% for 2021, but nominal GDP (called current-dollar GDP by the BEA) grew at 10%.3

Economists use the BEA’s real GDP headline data for macroeconomic analysis and central bank planning. The main difference between nominal GDP and real GDP is the taking of inflation into account. Since nominal GDP is calculated using current prices, it does not require any adjustments for inflation. This makes comparisons from quarter to quarter and year to year much simpler, though less relevant, to calculate and analyze.

As such, real GDP provides a better basis for judging long-term national economic performance than nominal GDP. Using a GDP price deflator, real GDP reflects GDP on a per quantity basis. Without real GDP, it would be difficult to identify just from examining nominal GDP whether production is actually expanding—or it's just a factor of rising per-unit prices in the economy.

A positive difference in nominal minus real GDP signifies inflation and a negative difference signifies deflation. In other words, when nominal is higher than real, inflation is occurring and when real is higher than nominal, deflation is occurring. 

The GDP price deflator is considered to be a more appropriate inflation measure for measuring economic growth than the consumer price index (CPI) because it isn't based on a fixed basket of goods.

Real GDP Calculation

Calculating real GDP is a complex process typically best provided by the BEA. In general, calculating real GDP is done by dividing nominal GDP by the GDP deflator (R).

\begin{aligned}&\text{Real GDP} = \frac{\text{Nominal GDP}}{\text{R}}\\&\textbf{where:}\\&\text{GDP}=\text{Gross domestic product}\\&\text{R} =\text{GDP deflator}\end{aligned}​Real GDP=RNominal GDP​where:GDP=Gross domestic productR=GDP deflator​

The BEA provides the deflator on a quarterly basis. The GDP deflator is a measurement of inflation since a base year (currently 2017 for the BEA). Dividing the nominal GDP by the deflator removes the effects of inflation.4

For example, if an economy's prices have increased by 1% since the base year, the deflating number is 1.01. If nominal GDP was $1 million, then real GDP is calculated as $1,000,000 / 1.01, or $990,099.

What Does 'Real' Mean in Real GDP?

Real GDP tracks the total value of goods and services calculating the quantities but using constant prices that are adjusted for inflation. This is opposed to nominal GDP that does not account for inflation. Adjusting for constant prices makes it a measure of "real" economic output for apples-to-apples comparison over time and between countries.

What Does Real GDP Measure?

Real GDP is an inflation-adjusted measurement of a country’s economic output over the course of a year. The U.S. GDP is primarily measured based on the expenditure approach and calculated using the following formula: GDP = C + G + I + NX (where C=consumption; G=government spending; I=Investment; and NX=net exports). 

How Will Real and Nominal GDP Differ From One Another?

In inflationary periods, real GDP will be lower than nominal GDP. In deflationary times, real GDP will be higher. Take, for example, a hypothetical country that had a nominal GDP of $100 Billion in 2000, which grew by 50% to $150 billion by 2020. Over the same period of time, inflation reduced the relative purchasing power of the dollar by 50%. Looking at just the nominal GDP, the economy appears to be performing very well, whereas the real GDP expressed in 2000 dollars would actually indicate a reading of $75 billion, revealing in fact a net overall decline in economic growth had occurred. It is due to this greater accuracy that real GDP is favored by economists as a method of measuring economic performance.

Why Is Measuring Real GDP Important?

Countries with larger GDPs will have a greater amount of goods and services generated within them, and will generally have a higher standard of living. For this reason, many citizens and political leaders see GDP growth as an important measure of national success, often referring to “GDP growth” and “economic growth” interchangeably. GDP enables policymakers and central banks to judge whether the economy is contracting or expanding, whether it needs a boost or restraint, and if a threat such as a recession or inflation looms on the horizon. By accounting for inflation, real GDP is a better gauge of the change in production levels from one period to another.

What Are Some Critiques of Using GDP?

Many economists have argued that GDP should not be used as a proxy for overall economic success, as it does not account for the informal economy, does not count care work or domestic labor in the home, ignores business-to-business activity, and counts costs and wastes as economic activity, among other shortcomings.

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In statistics, the p-value is the probability of obtaining results at least as extreme as the observed results of a statistical hypothesis test, assuming that the null hypothesis is correct. The p-value serves as an alternative to rejection points to provide the smallest level of significance at which the null hypothesis would be rejected. A smaller p-value means that there is stronger evidence in favor of the alternative hypothesis.

P-value is often used to promote credibility for studies or reports by government agencies. For example, the United States Census Bureau stipulates any analysis with a p-value greater than 0.10 must be accompanied by a statement that the difference is not statistically different from zero The Census Bureau also has standards in place stipulating what p-values are acceptable for various publications.1

KEY TAKEAWAYS

• A p-value is a statistical measurement used to validate a hypothesis against observed data.

• A p-value measures the probability of obtaining the observed results, assuming that the null hypothesis is true.

• The lower the p-value, the greater the statistical significance of the observed difference.

• A p-value of 0.05 or lower is generally considered statistically significant.

• P-value can serve as an alternative to or in addition to preselected confidence levels for hypothesis testing.

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Click Play to Learn How P-Value Is Calculated

How Is P-Value Calculated?

P-values are usually found using p-value tables or spreadsheets/statistical software. These calculations are based on the assumed or known probability distribution of the specific statistic tested. P-values are calculated from the deviation between the observed value and a chosen reference value, given the probability distribution of the statistic, with a greater difference between the two values corresponding to a lower p-value.

Mathematically, the p-value is calculated using integral calculus from the area under the probability distribution curve for all values of statistics that are at least as far from the reference value as the observed value is, relative to the total area under the probability distribution curve. The calculation for a p-value varies based on the type of test performed. The three test types describe the location on the probability distribution curve: lower-tailed test, upper-tailed test, or two-sided test.

In a nutshell, the greater the difference between two observed values, the less likely it is that the difference is due to simple random chance, and this is reflected by a lower p-value.

The P-Value Approach to Hypothesis Testing

The p-value approach to hypothesis testing uses the calculated probability to determine whether there is evidence to reject the null hypothesis. The null hypothesis, also known as the “conjecture,” is the initial claim about a population (or data-generating process). The alternative hypothesis states whether the population parameter differs from the value of the population parameter stated in the conjecture.

In practice, the significance level is stated in advance to determine how small the p-value must be in order to reject the null hypothesis. Because different researchers use different levels of significance when examining a question, a reader may sometimes have difficulty comparing results from two different tests. P-values provide a solution to this problem.

For example, suppose a study comparing returns from two particular assets was undertaken by different researchers who used the same data but different significance levels. The researchers might come to opposite conclusions regarding whether the assets differ. If one researcher used a confidence level of 90% and the other required a confidence level of 95% to reject the null hypothesis and the p-value of the observed difference between the two returns was 0.08 (corresponding to a confidence level of 92%), then the first researcher would find that the two assets have a difference that is statistically significant, while the second would find no statistically significant difference between the returns.

To avoid this problem, the researchers could report the p-value of the hypothesis test and allow readers to interpret the statistical significance themselves. This is called a p-value approach to hypothesis testing. Independent observers could note the p-value and decide for themselves whether that represents a statistically significant difference or not.

Example of P-Value

An investor claims that their investment portfolio’s performance is equivalent to that of the Standard & Poor’s (S&P) 500 Index. To determine this, the investor conducts a two-tailed test. The null hypothesis states that the portfolio’s returns are equivalent to the S&P 500’s returns over a specified period, while the alternative hypothesis states that the portfolio’s returns and the S&P 500’s returns are not equivalent—if the investor conducted a one-tailed test, the alternative hypothesis would state that the portfolio’s returns are either less than or greater than the S&P 500’s returns.

The p-value hypothesis test does not necessarily make use of a preselected confidence level at which the investor should reset the null hypothesis that the returns are equivalent. Instead, it provides a measure of how much evidence there is to reject the null hypothesis. The smaller the p-value, the greater the evidence against the null hypothesis. Thus, if the investor finds that the p-value is 0.001, there is strong evidence against the null hypothesis, and the investor can confidently conclude the portfolio’s returns and the S&P 500’s returns are not equivalent.

Although this does not provide an exact threshold as to when the investor should accept or reject the null hypothesis, it does have another very practical advantage. P-value hypothesis testing offers a direct way to compare the relative confidence that the investor can have when choosing among multiple different types of investments or portfolios relative to a benchmark such as the S&P 500.

For example, for two portfolios, A and B, whose performance differs from the S&P 500 with p-values of 0.10 and 0.01, respectively, the investor can be much more confident that portfolio B, with a lower p-value, will actually show consistently different results.

Is a 0.05 P-Value Significant?

A p-value less than 0.05 is typically considered to be statistically significant, in which case the null hypothesis should be rejected. A p-value greater than 0.05 means that deviation from the null hypothesis is not statistically significant, and the null hypothesis is not rejected.

What Does a P-Value of 0.001 Mean?

A p-value of 0.001 indicates that if the null hypothesis tested were indeed true, there would be a one in 1,000 chance of observing results at least as extreme. This leads the observer to reject the null hypothesis because either a highly rare data result has been observed, or the null hypothesis is incorrect.

How Can You Use P-Value to Compare Two Different Results of a Hypothesis Test?

If you have two different results, one with a p-value of 0.04 and one with a p-value of 0.06, the 0.04 will be considered statistically significant while the 0.06 will not. Beyond this simplified example, you could compare a 0.04 p-value to a 0.001 p-value. Both are statistically significant, but the 0.001 provides an even stronger case against the null hypothesis than the 0.04.

Correction–April 2, 2022: A previous version incorrectly described the p-value as the probability of results arising through random chance.

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Macroeconomics is a branch of economics that studies how an overall economy—the market or other systems that operate on a large scale—behaves. Macroeconomics studies economy-wide phenomena such as inflation, price levels, rate of economic growth, national income, gross domestic product (GDP), and changes in unemployment.

Some of the key questions addressed by macroeconomics include: What causes unemployment? What causes inflation? What creates or stimulates economic growth? Macroeconomics attempts to measure how well an economy is performing, to understand what forces drive it, and to project how performance can improve.

Macroeconomics deals with the performance, structure, and behavior of the entire economy, in contrast to microeconomics, which is more focused on the choices made by individual actors in the economy (like people, households, industries, etc.).

KEY TAKEAWAYS

• Macroeconomics is the branch of economics that deals with the structure, performance, behavior, and decision-making of the whole, or aggregate, economy.

• The two main areas of macroeconomic research are long-term economic growth and shorter-term business cycles.

• Macroeconomics in its modern form is often defined as starting with John Maynard Keynes and his theories about market behavior and governmental policies in the 1930s; several schools of thought have developed since.

• In contrast to macroeconomics, microeconomics is more focused on the influences on and choices made by individual actors in the economy (people, companies, industries, etc.).

Macroeconomics

Understanding Macroeconomics

There are two sides to the study of economics: macroeconomics and microeconomics. As the term implies, macroeconomics looks at the overall, big-picture scenario of the economy. Put simply, it focuses on the way the economy performs as a whole and then analyzes how different sectors of the economy relate to one another to understand how the aggregate functions. This includes looking at variables like unemployment, GDP, and inflation. Macroeconomists develop models explaining relationships between these factors. Such macroeconomic models, and the forecasts they produce, are used by government entities to aid in the construction and evaluation of economic, monetary, and fiscal policy; by businesses to set strategy in domestic and global markets; and by investors to predict and plan for movements in various asset classes.

Given the enormous scale of government budgets and the impact of economic policy on consumers and businesses, macroeconomics clearly concerns itself with significant issues. Properly applied, economic theories can offer illuminating insights on how economies function and the long-term consequences of particular policies and decisions. Macroeconomic theory can also help individual businesses and investors make better decisions through a more thorough understanding of the effects of broad economic trends and policies on their own industries.

Limits of Macroeconomics

It is also important to understand the limitations of economic theory. Theories are often created in a vacuum and lack certain real-world details like taxation, regulation, and transaction costs. The real world is also decidedly complicated and includes matters of social preference and conscience that do not lend themselves to mathematical analysis.

Even with the limits of economic theory, it is important and worthwhile to follow the major macroeconomic indicators like GDP, inflation, and unemployment. The performance of companies, and by extension their stocks, is significantly influenced by the economic conditions in which the companies operate and the study of macroeconomic statistics can help an investor make better decisions and spot turning points.

Likewise, it can be invaluable to understand which theories are in favor and influencing a particular government administration. The underlying economic principles of a government will say much about how that government will approach taxation, regulation, government spending, and similar policies. By better understanding economics and the ramifications of economic decisions, investors can get at least a glimpse of the probable future and act accordingly with confidence.

Areas of Macroeconomic Research

Macroeconomics is a rather broad field, but two specific areas of research are representative of this discipline. The first area is the factors that determine long-term economic growth, or increases in the national income. The other involves the causes and consequences of short-term fluctuations in national income and employment, also known as the business cycle.

Economic Growth

Economic growth refers to an increase in aggregate production in an economy. Macroeconomists try to understand the factors that either promote or retard economic growth in order to support economic policies that will support development, progress, and rising living standards.

Adam Smith's classic 18th-century work, An Inquiry into the Nature and Causes of the Wealth of Nations, which advocated free trade, laissez-faire economic policy, and expanding the division of labor*,* was arguably the first, and certainly one of the seminal works in this body of research. By the 20th century, macroeconomists began to study growth with more formal mathematical models. Growth is commonly modeled as a function of physical capital, human capital, labor force, and technology.1

Business Cycles

Superimposed over long term macroeconomic growth trends, the levels and rates-of-change of major macroeconomic variables such as employment and national output go through occasional fluctuations up or down, expansions and recessions, in a phenomenon known as the business cycle. The 2008 financial crisis is a clear recent example, and the Great Depression of the 1930s was actually the impetus for the development of most modern macroeconomic theory.

History of Macroeconomics

While the term "macroeconomics" is not all that old (going back to the 1940s), many of the core concepts in macroeconomics have been the focus of study for much longer. Topics like unemployment, prices, growth, and trade have concerned economists almost from the very beginning of the discipline, though their study has become much more focused and specialized through the 20th and 21st centuries. Elements of earlier work from the likes of Adam Smith and John Stuart Mill clearly addressed issues that would now be recognized as the domain of macroeconomics.

Macroeconomics, as it is in its modern form, is often defined as starting with John Maynard Keynes and the publication of his book The General Theory of Employment, Interest, and Money in 1936. Keynes offered an explanation for the fallout from the Great Depression, when goods remained unsold and workers unemployed. Keynes's theory attempted to explain why markets may not clear.

Prior to the popularization of Keynes' theories, economists did not generally differentiate between micro- and macroeconomics. The same microeconomic laws of supply and demand that operate in individual goods markets were understood to interact between individuals markets to bring the economy into a general equilibrium, as described by Leon Walras. The link between goods markets and large-scale financial variables such as price levels and interest rates was explained through the unique role that money plays in the economy as a medium of exchange by economists such as Knut Wicksell, Irving Fisher, and Ludwig von Mises.

Throughout the 20th century, Keynesian economics, as Keynes' theories became known, diverged into several other schools of thought.

Macroeconomic Schools of Thought

The field of macroeconomics is organized into many different schools of thought, with differing views on how the markets and their participants operate.

Classical

Classical economists held that prices, wages, and rates are flexible and markets tend to clear unless prevented from doing so by government policy, building on Adam Smith's original theories. The term “classical economists” is not actually a school of macroeconomic thought, but a label applied first by Karl Marx and later by Keynes to denote previous economic thinkers with whom they respectively disagreed, but who themselves did not actually differentiate macroeconomics from microeconomics at all. 

Keynesian

Keynesian economics was largely founded on the basis of the works of John Maynard Keynes, and was the beginning of macroeconomics as a separate area of study from microeconomics. Keynesians focus on aggregate demand as the principal factor in issues like unemployment and the business cycle. Keynesian economists believe that the business cycle can be managed by active government intervention through fiscal policy (spending more in recessions to stimulate demand) and monetary policy (stimulating demand with lower rates). Keynesian economists also believe that there are certain rigidities in the system, particularly sticky prices that prevent the proper clearing of supply and demand.

Monetarist

The Monetarist school is a branch of Keynesian economics largely credited to the works of Milton Friedman. Working within and extending Keynesian models, Monetarists argue that monetary policy is generally a more effective and more desirable policy tool to manage aggregate demand than fiscal policy. Monetarists also acknowledge limits to monetary policy that make fine tuning the economy ill advised and instead tend to prefer adherence to policy rules that promote stable rates of inflation.

New Classical

The New Classical school, along with the New Keynesians, is built largely on the goal of integrating microeconomic foundations into macroeconomics in order to resolve the glaring theoretical contradictions between the two subjects. The New Classical school emphasizes the importance of microeconomics and models based on that behavior. New Classical economists assume that all agents try to maximize their utility and have rational expectations, which they incorporate into macroeconomic models. New Classical economists believe that unemployment is largely voluntary and that discretionary fiscal policy is destabilizing, while inflation can be controlled with monetary policy.

New Keynesian

The New Keynesian school also attempts to add microeconomic foundations to traditional Keynesian economic theories. While New Keynesians do accept that households and firms operate on the basis of rational expectations, they still maintain that there are a variety of market failures, including sticky prices and wages. Because of this "stickiness", the government can improve macroeconomic conditions through fiscal and monetary policy.

Austrian

The Austrian School is an older school of economics that is seeing some resurgence in popularity. Austrian economic theories mostly apply to microeconomic phenomena, but because they, like the so-called classical economists never strictly separated micro- and macroeconomics, Austrian theories also have important implications for what are otherwise considered macroeconomic subjects. In particular the Austrian business cycle theory explains broadly synchronized (macroeconomic) swings in economic activity across markets as a result of monetary policy and the role that money and banking play in linking (microeconomic) markets to each other and across time. 

Macroeconomics vs. Microeconomics

Macroeconomics differs from microeconomics, which focuses on smaller factors that affect choices made by individuals and companies. Factors studied in both microeconomics and macroeconomics typically have an influence on one another. For example, the unemployment level in the economy as a whole has an effect on the supply of workers from which a company can hire.

A key distinction between micro- and macroeconomics is that macroeconomic aggregates can sometimes behave in ways that are very different or even the opposite of the way that analogous microeconomic variables do. For example, Keynes referenced the so-called Paradox of Thrift, which argues that while for an individual, saving money may be the key building wealth, when everyone tries to increase their savings at once it can contribute to a slowdown in the economy and less wealth in the aggregate.

Meanwhile, microeconomics looks at economic tendencies, or what can happen when individuals make certain choices. Individuals are typically classified into subgroups, such as buyers, sellers, and business owners. These actors interact with each other according to the laws of supply and demand for resources, using money and interest rates as pricing mechanisms for coordination.

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Junk bonds are bonds that carry a higher risk of default than most bonds issued by corporations and governments. A bond is a debt or promise to pay investors interest payments along with the return of invested principal in exchange for buying the bond. Junk bonds represent bonds issued by companies that are financially struggling and have a high risk of defaulting or not paying their interest payments or repaying the principal to investors.

Junk bonds are also called high-yield bonds since the higher yield is needed to help offset any risk of default.

KEY TAKEAWAYS

• A junk bond is debt that has been given a low credit rating by a ratings agency, below investment grade.

• As a result, these bonds are riskier since chances that the issuer will default or experience a credit event are higher.

• Because of the higher risk, investors are compensated with higher interest rates, which is why junk bonds are also called high-yield bonds.

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Junk Bond

Junk Bonds Explained

From a technical viewpoint, a high-yield, or "junk" bond is very similar to regular corporate bonds. Both represent debt issued by a firm with the promise to pay interest and to return the principal at maturity. Junk bonds differ because of their issuers' poorer credit quality.

Bonds are fixed-income debt instruments that corporations and governments issue to investors to raise capital. When investors buy bonds, they're effectively loaning money to the issuer who promises to repay the money on a specific date called the maturity date. At maturity, the investor is repaid the principal amount invested. Most bonds pay investors an annual interest rate during the life of the bond, called a coupon rate.

For example, a bond that has a 5% annual coupon rate means that an investor who purchases the bond earns 5% per year. So, a bond with a $1,000 face—or par—value will receive 5% x $1,000 which comes to $50 each year until the bond matures.

Higher Risk Equates to Higher Yield

A bond that has a high risk of the underlying company defaulting is called a junk bond. Companies that issue junk bonds are typically start-ups or companies that are struggling financially. Junk bonds carry risk since investors are unsure whether they'll be repaid their principal and earn regular interest payments. As a result, junk bonds pay a higher yield than their safer counterparts to help compensate investors for the added level of risk. Companies are willing to pay the high yield because they need to attract investors to fund their operations.

Pros

• Junk bonds return higher yields than most other fixed-income debt securities.

• Junk bonds have the potential of significant price increases should the company's financial situation improve.

• Junk bonds serve as a risk indicator of when investors are willing to take on risk or avoid risk in the market.

Cons

• Junk bonds have a higher risk of default than most bonds with better credit ratings.

• Junk bond prices can exhibit volatility due to uncertainty surrounding the issuer's financial performance.

• Active junk bond markets can indicate an overbought market meaning investors are too complacent with risk and may lead to market downturns.

Junk Bonds as a Market Indicator

Some investors buy junk bonds to profit from potential price increases as the financial security of the underlying company improves, and not necessarily for the return of interest income. Also, investors that predict bond prices to rise are betting there will be increased buying interest for high-yield bonds—even these lower rated ones—due to a change in market risk sentiment. For example, if investors believe economic conditions are improving in the U.S. or abroad, they might purchase junk bonds of companies that will show improvement along with the economy.

As a result, increased buying interest of junk bonds serves as a market-risk indicator for some investors. If investors are buying junk bonds, market participants are willing to take on more risk due to a perceived improving economy. Conversely, if junk bonds are selling off with prices falling, it usually means that investors are more risk averse and are opting for more secure and stable investments.

Although a surge in junk bond investing usually translates to increased optimism in the market, it could also point to too much optimism in the market.

It's important to note that junk bonds have much larger price swings than bonds of higher quality. Investors looking to purchase junk bonds can either buy the bonds individually through a broker or invest in a junk bond fund managed by a professional portfolio manager.

Improving Financials Affect Junk Bonds

If the underlying company performs well financially, its bonds will have improved credit ratings and usually attract buying interest from investors. As a result, the bond's price rises as investors flood in, willing to pay for the financially viable issuer. Conversely, companies that are performing poorly will likely have low or lowered credit ratings. These falling opinions might cause buyers to back off. Companies with poor credit ratings typically offer high yields to attract investors and to compensate them for the added level of risk.

The result is bonds issued by companies with positive credit ratings usually pay lower interest rates on their debt instruments as compared to companies with poor credit ratings. Many bond investors monitor the credit ratings of bonds.

Credit Ratings and Junk Bonds

Although junk bonds are considered risky investments, investors can monitor a bond's level of risk by reviewing the bond's credit rating. A credit rating is an assessment of the creditworthiness of an issuer and its outstanding debt in the form of bonds. The company's credit rating, and ultimately the bond's credit rating, impact the market price of a bond and its offering interest rate.

Credit-rating agencies measure the creditworthiness of all corporate and government bonds, giving investors insight into the risks involved in the debt securities. Credit rating agencies assign letter grades for their view of the issue.

For example, Standard & Poor’s has a credit rating scale ranging from AAA—excellent—to lower ratings of C and D. Any bond that carries a rating lower than BB is said to be of speculative-grade or a junk bond. This should be a red flag to risk-averse investors. The various letter grades from credit agencies represent the financial viability of the company and the likelihood that the contract terms of the bond terms will be honored.

Investment Grade

Bonds with a rating of investment-grade come from corporations that have a high probability of paying the regular coupons and returning the principal to investors. For example, Standard & Poor's ratings include:

• AAA—excellent

• AA—very good

• A—good

• BBB—adequate

"Junk" (Speculative)

As mentioned earlier, once a bond's rating drops into the double-B category, it falls into the junk bond territory. This area can be a scary place for investors who would be harmed by a total loss of their investment dollars in the case of a default.

Some speculative ratings include:

• CCC—currently vulnerable to nonpayment

• C—highly vulnerable to nonpayment

• D—in default

Companies having bonds with these low credit ratings might have difficulty raising the capital needed to fund ongoing business operations. However, if a company manages to improve its financial performance and it's bond's credit rating is upgraded, a substantial appreciation in the bond’s price could happen. Conversely, if a company's financial situation deteriorates, the credit rating of the company and its bonds might be downgraded by credit rating agencies. It is crucial for investors in junk debt to fully investigate the underlying business and all financial documents available before buying.

Bond Defaults

If a bond misses a principal and interest payment, the bond is considered to be in default. Default is the failure to repay a debt including interest or principal on a loan or security. Junk bonds have a higher risk of default because of an uncertain revenue stream or a lack of sufficient collateral. The risk of bond defaults increases during economic downturns making these bottom level debts even riskier.

Real World Example of a Junk Bond

Tesla Inc. (TSLA) issued a fixed-rate bond with a maturity date of March 1, 2021 and a fixed semi-annual coupon rate of 1.25%. The debt received an S&P rating of B- in 2014 when it was issued. In October 2020, S&P upgraded its rating to BB- from B+. This is still in junk bond rating territory. A BB rating from S&P means the rating issue is less vulnerable to nonpayment, but still faces major uncertainties or exposure to adverse business or economic conditions.

Also, the current price of the Tesla offering is $577 as of Oct. 2020, much higher than its 2014 $100 face value, which represents the extra yield that investors are getting above the coupon payment. In other words, despite the BB- rating, the bond is trading at very large premium to its face value. This is because the bonds are convertible to equity. Thus, with shares of Tesla soaring 600% over the last twelve months ending Oct. 26, 2020, the bonds are proving to be valuable surrogates for the equity.

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In finance, “FAANG” is an acronym that refers to the stocks of five prominent American technology companies: Meta (FB) (formerly known as Facebook), Amazon (AMZN), Apple (AAPL), Netflix (NFLX); and Alphabet (GOOG) (formerly known as Google). 

The term was popularized by Jim Cramer, the television host of CNBC's Mad Money, in 2013, who praised these companies for being “totally dominant in their markets." Originally, the term "FANG" was used, with Apple—the second “A” in the acronym—added in 2017.

KEY TAKEAWAYS

• FAANG is an acronym referring to the stocks of the five most popular and best-performing American technology companies: Meta (formerly known as Facebook), Amazon, Apple, Netflix, and Alphabet (formerly known as Google). 

• In addition to being widely known among consumers, the five FAANG stocks are among the largest companies in the world, with a combined market capitalization of nearly $7.1 trillion as of Aug. 19, 2021.

• Some have raised concerns that the FAANG stocks may be in the midst of a bubble, whereas others argue that their growth is justified by the stellar financial and operational performance they have shown in recent years.

What if you had started investing years ago?

Find out what a hypothetical investment would be worth today.

SELECT A STOCK

TSLA

TESLA INC

AAPL

APPLE INC

NKE

NIKE INC

AMZN

AMAZON.COM, INC

WMT

WALMART INC

SELECT INVESTMENT AMOUNT

$

SELECT A PURCHASE DATE

              2 years ago                      5 years ago                      10 years ago         

CALCULATE

Understanding FAANG Stocks

In addition to being widely known among consumers, the five FAANG stocks are among the largest companies in the world, with a combined market capitalization of around $7 trillion as of Q1 2022.12345

Their substantial growth has been buoyed recently by high-profile purchases made by large and influential investors such as Berkshire Hathaway (BRK), Soros Fund Management, and Renaissance Technologies. These are just a few of the many large investors who have added FAANG stocks to their portfolios because of their perceived strength, growth, or momentum. 

Each of the FAANG stocks trades on the Nasdaq exchange and is included in the S&P 500 Index. Since the S&P 500 is a broad representation of the market, the movement of the market mirrors the index's movement. As of August 2021, the FAANGs make up about 19% of the S&P 500—a staggering figure considering the S&P 500 is generally viewed as a proxy for the United States economy as a whole.

This large influence over the index means that volatility in the stock price of the FAANG stocks can have a substantial effect on the performance of the S&P 500 in general. In August 2018, for example, FAANG stocks were responsible for nearly 40% of the index’s gain from the lows reached in February 2018.

Example of FAANG Stocks

The extraordinary size and influence of the FAANG stocks have prompted concerns about a potential bubble in FAANG stocks. These concerns started gaining prominence in 2018, when technology stocks, which had been driving consistent gains in the stock market, began losing their former strength. In November 2018, several FAANG stocks lost more than 20% of their valuations and were declared to be in bear territory.6 By some estimates, FAANG stocks lost more than a trillion dollars from their peak valuations as a result of the steep drop in the markets in November 2018.6

Although their valuations have since recovered, the level of volatility sometimes shown by FAANG stocks—and the oversized influence these stocks can have on the market overall—is a source of concern for some investors.

On the other hand, those who believe in the fundamental strength of the FAANG stocks have abundant evidence for this claim. For example, Facebook is the world’s largest social network with approximately 2.8 billion users. In its 2021 annual report, Meta posted revenues of $118 billion and net income of $39.4 billion.7

Amazon, meanwhile, has become a seemingly insurmountable force in business-to-consumer (B2C) e-commerce. With over 120 million products for sale, it has over 300 million active customers in the United States, of whom more than half pay for monthly Amazon Prime memberships.8 With 2021 TTM revenues of $470 billion and a net income of $33.4 billion, it is not hard to understand why investors believe Amazon’s vast market capitalization is justified.9

Overall, it is through strong financial performance such as this that the FAANG stocks have prospered recently. Over the past five years, for instance, Meta and Amazon have seen stock-price increases of 185% and 500%, respectively. For their part, Apple and Alphabet saw price increases of about 175% over that same timeframe, whereas Netflix saw its value rise by nearly 450%.

What Makes FAANG Stocks So Popular?

The five stocks that make up the “FAANG” acronym—Meta (FB), Amazon (AMZN), Apple (AAPL), Netflix (NFLX), and Alphabet (GOOG)—are all well-known brands among consumers. But they are also famous for their remarkable growth in recent years, with market capitalizations ranging from $166 billion (in the case of Netflix) to $2.7 trillion (in the case of Apple), as of Q1 2022.32 From an investment perspective, these five stocks are generally praised for their stellar historical track records and clear leadership positions within their industries.

Are FAANG Stocks Overvalued?

Investors disagree about whether the FAANG stocks are overvalued. Their proponents will argue that their valuations are justified based on their fundamental strength as businesses. But critics argue that, even with impressive business performance, the FAANG stocks’ prices have become so expensive that it may be difficult to realize attractive long-term profits from investing in them. Ultimately, this “debate” between investors is best captured by the buying and selling patterns in the FAANG stocks themselves.

Are FAANG Stocks Hard to Acquire?

No. The FAANG stocks are all easy to acquire, in the sense that they are publicly traded companies with substantial daily trading volumes. They are also routinely included in popular exchange-traded funds (ETFs). However, investors who believe that the FAANG stocks may be overvalued would argue that they are difficult to acquire at an economical price. These investors may be tempted to delay purchasing FAANG stocks, waiting for their valuations to decline.

Who Coined the Term FANG Stocks?

While Jim Cramer certainly popularized the term, he himself credits Bob Lang, a Real Money and The Street colleague of Cramer's, with identifying these four stocks and inventing the acronym.10

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In finance, the acronym "FANG" refers to the stocks of four prominent American technology companies: Meta (FB) (formerly Facebook), Amazon (AMZN), Netflix (NFLX), and Alphabet (GOOG). FANG stocks are famous for the impressive growth they have shown in recent years, with each member more than doubling over the past five years.

In 2017, the company Apple (AAPL) was also added by some analysts, resulting in the new acronym "FAANG."

KEY TAKEAWAYS

• The term "FANG" refers to the stocks of four popular American technology companies: Meta, Amazon, Netflix, and Alphabet.

• Each of the FANG companies has shown extraordinary growth in recent years, reflected in both their revenues and their net profits.

• Although their business models vary, they each share the use of advanced technologies to acquire and retain users.

Understanding FANG Stocks

The term FANG Stocks was coined by CNBC's "Mad Money" host Jim Cramer in 2013.1 It is now widely used by market commentators and analysts. The stocks referred to by the acronym are all well-known and richly-valued technology companies that trade on the NASDAQ exchange, a collection of approximately 3,300 American technology companies.2 Many other companies included in the NASDAQ exchange are also viewed as growth investments, although very few have matched the impressive growth of the FANG stocks in recent years.

Despite their common reputation as successful growth companies, the business models of the FANG stocks are distinct. Facebook, for example, is the world’s preeminent social networking platform. With a monthly user-base of more than 2.85 billion people as of April. 2021, Meta can claim over 35% of the world's population as its customers.3 To monetize this extraordinary user base, Facebook sells ads that are targeted based on users’ personal preferences and usage patterns.

Amazon, meanwhile, is a leading business-to-consumer (B2C) e-commerce platform that uses leading-edge cloud computing and data analytics technologies to sell a retail catalog. Although Amazon initially pioneered the sale of books online, books now represent only about one-third of their overall product catalog. In 2020, the company had sold products to over 300 million active customers in the U.S. alone, with half of those customers opting to subscribe to its paid membership service, Amazon Prime.4

Netflix is also known for its impressive customer growth. An online entertainment streaming service specializing in movies and television shows, the company's subscriber base has grown exponentially in recent years, from 22 million in 2011 to more than 209 million in 2020.5 To compete with new entrants to the streaming market, Netflix has also begun aggressively producing its own exclusive content, moving beyond its traditional role as a content aggregator to a major content producer in its own right.

Alphabet has leveraged its core expertise as the world’s foremost search engine, developing a highly profitable online advertising business while driving user retention through popular web applications such as YouTube, Google Docs, and Google Maps. The company receives an average of over 60,000 search requests every second of every day, and its mobile operating system, Android, has gained an estimated 75% share of the global smartphone market.

Example of FANG Stocks

With these impressive facts in mind, it is no wonder why investors have been enthusiastic about the FANG Stocks' business prospects. In recent years, this enthusiasm has been supported by the companies' financial performance, which has caused substantial increases in their respective stock prices.

In the trailing twelve months (TTM) as of August 2021, for example, Meta has reported revenues of over $104 billion, and net income of over $39 billion.6 Amazon, meanwhile, showed revenue of an astounding $443 billion, producing a net income of $29 billion.7 Over the past five years, these two companies’ stock prices increased by roughly 191% and 335%, respectively.89

Netflix and Google have also shown strong TTM performance, with Netflix posting revenues of over $27 billion and net income of over $4.3 billion.10 Google, for its part, generated $220 billion in revenues along with nearly $62 billion in net income.11 Buoyed by these earnings, Netflix’s stock rose by 480% in the past five years, while Google's rose by about 276% over the same timeframe.1213

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What Does the Acronym FANG Stand for?

The acronym FANG Stocks was coined by CNBC's "Mad Money" host Jim Cramer in 2013. This acronym refers to the stocks of four prominent American technology companies—Meta (FB) (formerly Facebook), Amazon (AMZN), Netflix (NFLX), and Alphabet (GOOG). By adding Apple (AAPL) in 2017, "FANG" became "FAANG."

Why Are FANG Stocks Popular?

FANG stocks are famous for the impressive growth they have shown in recent years, with each member more than doubling over the past five years. However, despite exhibiting growth stock behavior, FANG stocks are not too volatile. It's this stability, along with delivering superior rates of return, that has made these quite attractive to investors.

What Businesses Are FANGs in?

Although they each share the use of advanced technologies to acquire and retain users, FANGs have distinct business models. Facebook is the world’s preeminent social networking platform. Amazon is a leading business-to-consumer (B2C) e-commerce platform. Netflix is an online entertainment streaming service that has also begun aggressively producing its own exclusive content. Alphabet (Google) has leveraged its core expertise as the world’s foremost search engine to develop a highly profitable online advertising business.

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The correlation coefficient is a statistical measure of the strength of the relationship between the relative movements of two variables. The values range between -1.0 and 1.0. A calculated number greater than 1.0 or less than -1.0 means that there was an error in the correlation measurement. A correlation of -1.0 shows a perfect negative correlation, while a correlation of 1.0 shows a perfect positive correlation. A correlation of 0.0 shows no linear relationship between the movement of the two variables.

Correlation statistics can be used in finance and investing. For example, a correlation coefficient could be calculated to determine the level of correlation between the price of crude oil and the stock price of an oil-producing company, such as Exxon Mobil Corporation. Since oil companies earn greater profits as oil prices rise, the correlation between the two variables is highly positive.

KEY TAKEAWAYS

• Correlation coefficients are used to measure the strength of the relationship between two variables.

• Pearson correlation is the one most commonly used in statistics. This measures the strength and direction of a linear relationship between two variables.

• Values always range between -1 (strong negative relationship) and +1 (strong positive relationship). Values at or close to zero imply a weak or no linear relationship.

• Correlation coefficient values less than +0.8 or greater than -0.8 are not considered significant.

Understanding the Correlation Coefficient

There are several types of correlation coefficients, but the one that is most common is the Pearson correlation (r). This measures the strength and direction of the linear relationship between two variables. It cannot capture nonlinear relationships between two variables and cannot differentiate between dependent and independent variables.1

A value of exactly 1.0 means there is a perfect positive relationship between the two variables. For a positive increase in one variable, there is also a positive increase in the second variable. A value of -1.0 means there is a perfect negative relationship between the two variables. This shows that the variables move in opposite directions—for a positive increase in one variable, there is a decrease in the second variable. If the correlation between two variables is 0, there is no linear relationship between them.

The strength of the relationship varies in degree based on the value of the correlation coefficient. For example, a value of 0.2 shows there is a positive correlation between two variables, but it is weak and likely unimportant. Analysts in some fields of study do not consider correlations important until the value surpasses at least 0.8. However, a correlation coefficient with an absolute value of 0.9 or greater would represent a very strong relationship.2

Investors can use changes in correlation statistics to identify new trends in the financial markets, the economy, and stock prices.

Correlation Statistics and Investing

The correlation between two variables is particularly helpful when investing in the financial markets. For example, a correlation can be helpful in determining how well a mutual fund performs relative to its benchmark index, or another fund or asset class. By adding a low or negatively correlated mutual fund to an existing portfolio, the investor gains diversification benefits.

In other words, investors can use negatively correlated assets or securities to hedge their portfolios and reduce market risk due to volatility or wild price fluctuations. Many investors hedge the price risk of a portfolio, which effectively reduces any capital gains or losses because they want the dividend income or yield from the stock or security.

Correlation statistics also allow investors to determine when the correlation between two variables changes. For example, bank stocks typically have a highly positive correlation to interest rates, since loan rates are often calculated based on market interest rates. If the stock price of a certain bank is falling while interest rates are rising, investors can glean that something's askew with that particular bank. If the stock prices of other banks in the sector are also rising, investors can conclude that the decline of the outlier bank's stock is not due to interest rates. Instead, the poorly performing bank is likely dealing with an internal, fundamental issue.

Correlation Coefficient Equation

To calculate the Pearson product-moment correlation, one must first determine the covariance of the two variables in question. Next, one must calculate each variable's standard deviation. The correlation coefficient is determined by dividing the covariance by the product of the two variables' standard deviations.

\begin{aligned} &\rho_{xy} = \frac { \text{Cov} ( x, y ) }{ \sigma_x \sigma_y } \\ &\textbf{where:} \\ &\rho_{xy} = \text{Pearson product-moment correlation coefficient} \\ &\text{Cov} ( x, y ) = \text{covariance of variables } x \text{ and } y \\ &\sigma_x = \text{standard deviation of } x \\ &\sigma_y = \text{standard deviation of } y \\ \end{aligned}​ρxy​=σx​σy​Cov(x,y)​where:ρxy​=Pearson product-moment correlation coefficientCov(x,y)=covariance of variables x and yσx​=standard deviation of xσy​=standard deviation of y​

Standard deviation is a measure of the dispersion of data from its average. Covariance is a measure of how two variables change together, but its magnitude is unbounded, so it is difficult to interpret. By dividing covariance by the product of the two standard deviations, one can calculate the normalized version of the statistic. This is the correlation coefficient.2

What Is Meant by the Correlation Coefficient?

The correlation coefficient describes how one variable moves in relation to another. A positive correlation indicates that the two move in the same direction, with a +1.0 correlation when they move in tandem. A negative correlation coefficient tells you that they instead move in opposite directions. A correlation of zero suggests no correlation at all.

How Do You Calculate the Correlation Coefficient?

The correlation coefficient is calculated by first determining the covariance of the variables and then dividing that quantity by the product of those variables’ standard deviations.

How Is the Correlation Coefficient Used in Investing?

Correlation coefficients are a widely-used statistical measure in investing. They play a very important role in areas such as portfolio composition, quantitative trading, and performance evaluation. For example, some portfolio managers will monitor the correlation coefficients of individual assets in their portfolios in order to ensure that the total volatility of their portfolios is maintained within acceptable limits.

Similarly, analysts will sometimes use correlation coefficients to predict how a particular asset will be impacted by a change to an external factor, such as the price of a commodity or an interest rate.

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After-hours trading starts at 4 p.m. U.S. Eastern Time after the major U.S. stock exchanges close. The after-hours trading session can run as late as 8 p.m., though volume typically thins out much earlier in the session. Trading in the after-hours is conducted through electronic communication networks (ECNs).

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What's After-Hours Trading?

KEY TAKEAWAYS

• After-hours trading starts at 4 p.m. and ends at around 8 p.m.

• Stocks are not as liquid during after-hours trading.

• The spread between the bid and the ask may be wider in after-hours trading.

Understanding After-Hours Trading

The Spark

After-hours trading is something traders or investors can use if news breaks after the close of the stock exchange. In some cases, the news, such as an earnings release, may prompt an investor to either buy or sell a stock.

Volume

The volume for a stock may spike on the initial release of the news but most of the time thins out as the session progresses. The amount of volume generally slows significantly by 6 p.m. There is a substantial risk when trading in illiquid stocks after-hours. 

Price

Not only does volume sometimes come at a premium in the after-hours trading sessions but so does price. It is not unusual for the spreads to be wide in the after-hours. The spread is the difference between the bid and the ask prices. Due to fewer shares trading, the spread may be significantly wider than during the normal trading session.

Participation

If liquidity and prices weren’t enough of a reason to make after-hours trading risky, the lack of participants makes it even riskier. In some cases, certain investors or institutions may choose simply not to participate in after-hours trading, regardless of the news or the event.

This means that it is quite possible for a stock to fall sharply in the after-hours only to rise once the regular trading session resumes the next day at 9:30 a.m., should many big institutional investors have a different view of the price action during the after-hours trading session.

Because volume is thin and spreads are wide in after-hours trading it is much easier to push prices higher or lower, requiring fewer shares to make a substantial impact. Since after-hours trading can have a significant impact on a stock's price, it's not a bad idea to put a limit order on any shares you intend to buy or sell outside of regular trading periods.

Real-World Example of After-Hours Trading

Nvidia Corp. (NVDA) earnings results in February 2019 are an excellent example of how after-hours trading works and the dangers that come with it. Nvidia reported quarterly results on February 14.1 The stock was greeted by a big jump in price, rising to nearly $169 from $154.50 in the 10 minutes following the news.

As the chart shows, volume was steady in the first 10 minutes and then dropped quickly after 4:30 p.m. During the first 5 minutes of trading, around 700,000 shares traded and the stock jumped nearly 6%. However, volume slowed materially with just 350,000 shares trading between 4:25 and 4:30. By 5 p.m., the amount of volume trading slowed to only 100,000 shares, while the stock was still trading around $165.

Image by Sabrina Jiang © Investopedia 2020

However, the next morning was a different story, which was when all the market participants had a chance to weigh in on Nvidia’s results. From 9:30 a.m. 9:35 a.m., nearly 2.3 million shares traded, more than three times greater than the volume in the initial minutes of the previous day's after-hours, and the price dropped from $164 to $161.

The stock proceeded to trade lower throughout the rest of the day, closing at $157.20. That was just $3 higher than the previous day's close, after being up nearly $15 in the after-hours session. Nearly all of the after-hours gains had evaporated.

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