What Is Aggregate Stop-Loss Insurance?

Aggregate stop-loss insurance is a policy designed to limit claim coverage (losses) to a specific amount. This coverage ensures that a catastrophic claim (specific stop-loss) or numerous claims (aggregate stop-loss) do not drain the financial reserves of a self-funded plan. Aggregate stop-loss protects the employer against claims that are higher than expected. If total claims exceed the aggregate limit, the stop-loss insurer covers the claims or reimburses the employer.

Understanding Aggregate Stop-Loss Insurance

Aggregate stop-loss insurance is held for self-funded insurance plans for which an employer assumes the financial risk of providing healthcare benefits to its employees. In practical terms, self-funded employers pay for each claim as it is presented instead of paying a fixed premium to an insurance carrier for a fully insured plan. Stop-loss insurance is similar to purchasing high-deductible insurance. The employer remains responsible for claim expenses under the deductible amount.

Stop-loss insurance differs from conventional employee benefit insurance. Stop-loss only covers the employer and provides no direct coverage to employees and health plan participants.

How Aggregate Stop-Loss Insurance Is Used

Aggregate stop-loss insurance is used by employers as coverage for risk against a high value of claims. Aggregate stop-loss insurance comes with a maximum level for claims. When a maximum threshold is exceeded, the employer no longer needs to make payments and may receive some reimbursements.

Aggregate stop-loss insurance can either be added to an existing insurance plan or purchased independently. The threshold is calculated based on a certain percentage of projected costs (called attachment points)—usually 125% of anticipated claims for the year.

An aggregate stop-loss threshold is usually variable and not fixed. This is because the threshold fluctuates as a percentage of an employer’s enrolled employees. The variable threshold is based on an aggregate attachment factor which is an important component in the calculation of a stop-loss level.

As is the case with high deductible plans, most stop-loss plans will have relatively low premiums. This is because the employer is expected to cover over 100% of the value of claims they receive.

Aggregate Stop-Loss Insurance Calculations

The aggregate attachment associated with a stop-loss plan is calculated as follows: 

Step 1

The employer and stop-loss insurance provider estimate the average dollar value of claims expected by employee per month. This value will depend on the employer’s estimate but often ranges from $200 to $500 per month.

Step 2

Assume the stop-loss plan uses a value of $200. This value would then be multiplied by the stop-loss attachment multiplier which usually ranges from 125% to 175%. Using a claims estimate of $200 and a stop-loss attachment multiplier of 1.25, the monthly deductible would be $250 per month per employee ($200 x 1.25 = $250).

Step 3

This deductible must then be multiplied by the employer’s plan enrollment for the month. Assuming that an employer has 100 employees in the first month of coverage, their total deductible would be $25,000 for the month ($250 x 100).

Step 4

Enrollment can potentially vary per month. Due to enrollment variance, aggregate stop-loss coverage may have either a monthly deductible or an annual deductible.

Step 5

With a monthly deductible, the amount an employer must pay could change every month. With an annual deductible, the amount the employer must pay would be summed for the year and usually based on estimates from the initial month of coverage. Many stop-loss plans will offer an annual deductible that is slightly lower than the summation of deductibles over 12 months.

What Is Aggregate Demand?

Aggregate demand is a measurement of the total amount of demand for all finished goods and services produced in an economy. Aggregate demand is commonly expressed as the total amount of money exchanged for those goods and services at a specific price level and point in time.

Understanding Aggregate Demand

Aggregate demand is a macroeconomic term and can be compared with the gross domestic product (GDP). GDP represents the total amount of goods and services produced in an economy while aggregate demand is the demand or desire for those goods. Aggregate demand and GDP commonly increase or decrease together.

Aggregate demand equals GDP only in the long run after adjusting for the price level. Short-run aggregate demand measures total output for a single nominal price level without adjusting for inflation. Other variations in calculations can occur depending on the methodologies used and the various components.

Aggregate demand consists of all consumer goods, capital goods, exports, imports, and government spending programs. All variables are considered equal if they trade at the same market value.

Aggregate Demand Components

Aggregate demand is determined by the overall collective spending on products and services by all economic sectors on the procurement of goods and services by four components:

Consumption Spending

Consumer spending represents the demand by individuals and households within the economy. While there are several factors in determining consumer demand, the most important is consumer incomes and the level of taxation.

Investment Spending

Investment spending represents businesses’ investment to support current output and increase production capability. It may include spending on new capital assets such as equipment, facilities, and raw materials.

Government Spending

Government spending represents the demand produced by government programs, such as infrastructure spending and public goods. This does not include services such as Medicare or social security, because these programs simply transfer demand from one group to another.

Net Exports

Net exports represent the demand for foreign goods, as well as the foreign demand for domestic goods. It is calculated by subtracting the total value of a country’s exports from the total value of all imports.

Aggregate Demand Formula

The equation for aggregate demand adds the amount of consumer spending, investment spending, government spending, and the net of exports and imports. The formula is shown as follows:

$\begin{aligned} &\text{Aggregate Demand} = \text{C} + \text{I} + \text{G} + \text{Nx} \\ &\textbf{where:}\\ &\text{C} = \text{Consumer spending on goods and services} \\ &\text{I} = \text{Private investment and corporate spending on} \\ &\text{non-final capital goods (factories, equipment, etc.)} \\ &\text{G} = \text{Government spending on public goods and social} \\ &\text{services (infrastructure, Medicare, etc.)} \\ &\text{Nx} = \text{Net exports (exports minus imports)} \\ \end{aligned}$​Aggregate Demand=C+I+G+Nxwhere:C=Consumer spending on goods and servicesI=Private investment and corporate spending onnon-final capital goods (factories, equipment, etc.)G=Government spending on public goods and socialservices (infrastructure, Medicare, etc.)Nx=Net exports (exports minus imports)​

The aggregate demand formula above is also used by the Bureau of Economic Analysis to measure GDP in the U.S.

What Affects Aggregate Demand?

Interest Rates

Interest rates affect decisions made by consumers and businesses. Lower interest rates will lower the borrowing costs for big-ticket items such as appliances, vehicles, and homes and companies will be able to borrow at lower rates, often leading to capital spending increases. Higher interest rates increase the cost of borrowing for consumers and companies and spending tends to decline or grow at a slower pace.

Income and Wealth

As household wealth increases, aggregate demand typically increases. Conversely, a decline in wealth usually leads to lower aggregate demand. When consumers are feeling good about the economy, they tend to spend more and save less.

Inflation Expectations

Consumers who anticipate that inflation will increase or prices will rise tend to make immediate purchases leading to rises in aggregate demand. But if consumers believe prices will fall in the future, aggregate demand typically falls.

Currency Exchange Rates

When the value of the U.S. dollar falls, foreign goods will become more expensive. Meanwhile, goods manufactured in the U.S. will become cheaper for foreign markets. Aggregate demand will, therefore, increase. When the value of the dollar increases, foreign goods are cheaper and U.S. goods become more expensive to foreign markets, and aggregate demand decreases.

Economic Conditions and Aggregate Demand

Economic conditions can impact aggregate demand whether those conditions originated domestically or internationally. The financial crisis of 2007-08, sparked by massive amounts of mortgage loan defaults, and the ensuing Great Recession, offer a good example of a decline in aggregate demand due to economic conditions.

With businesses suffering from less access to capital and fewer sales, they began to lay off workers and GDP growth contracted in 2008 and 2009, resulting in a total production contraction in the economy during that period. A poor-performing economy and rising unemployment led to a decline in personal consumption or consumer spending. Personal savings also surged as consumers held onto cash due to an uncertain future and instability in the banking system.

In 2020, the COVID-19 pandemic caused reductions in both aggregate supply or production, and aggregate demand or spending. Social distancing measures and concerns about the spread of the virus caused a significant decrease in consumer spending, particularly in services as many businesses closed. These dynamics lowered aggregate demand in the economy. As aggregate demand fell, businesses either laid off part of their workforces or otherwise slowed production as employees contracted COVID-19 at high rates.

Aggregate Demand vs. Aggregate Supply

In times of economic crises, economists often debate as to whether aggregate demand slowed, leading to lower growth, or GDP contracted, leading to less aggregate demand. Whether demand leads to growth or vice versa is economists’ version of the age-old question of what came first—the chicken or the egg.

Boosting aggregate demand also boosts the size of the economy regarding measured GDP. However, this does not prove that an increase in aggregate demand creates economic growth. Since GDP and aggregate demand share the same calculation, it only indicates that they increase concurrently. The equation does not show which is the cause and which is the effect.

Early economic theories hypothesized that production is the source of demand. The 18th-century French classical liberal economist Jean-Baptiste Say stated that consumption is limited to productive capacity and that social demands are essentially limitless, a theory referred to as Say’s Law of Markets.

Say’s law, the basis of supply-side economics, ruled until the 1930s and the advent of the theories of British economist John Maynard Keynes. By arguing that demand drives supply, Keynes placed total demand in the driver’s seat. Keynesian macroeconomists have since believed that stimulating aggregate demand will increase real future output and the total level of output in the economy is driven by the demand for goods and services and propelled by money spent on those goods and services.

Keynes considered unemployment to be a byproduct of insufficient aggregate demand because wage levels would not adjust downward fast enough to compensate for reduced spending. He believed the government could spend money and increase aggregate demand until idle economic resources, including laborers, were redeployed.

Other schools of thought, notably the Austrian School and real business cycle theorists stress consumption is only possible after production. This means an increase in output drives an increase in consumption, not the other way around. Any attempt to increase spending rather than sustainable production only causes maldistribution of wealth or higher prices, or both.

As a demand-side economist, Keynes further argued that individuals could end up damaging production by limiting current expenditures—by hoarding money, for example. Other economists argue that hoarding can impact prices but does not necessarily change capital accumulation, production, or future output. In other words, the effect of an individual’s saving money—more capital available for business—does not disappear on account of a lack of spending.

The Bottom Line

Aggregate demand is a concept of macroeconomics that represents the total demand within an economy for all kinds of goods and services at a certain price point. In the long term, aggregate demand is indistinguishable from GDP. However, aggregate demand is not a perfect metric and it is the subject of debate among economists.

What Is Aggregate Supply?

Aggregate supply, also known as total output, is the total supply of goods and services produced within an economy at a given overall price in a given period. It is represented by the aggregate supply curve, which describes the relationship between price levels and the quantity of output that firms are willing to provide. Typically, there is a positive relationship between aggregate supply and the price level.

Aggregate Supply Explained

Rising prices are typically an indicator that businesses should expand production to meet a higher level of aggregate demand. When demand increases amid constant supply, consumers compete for the goods available and, therefore, pay higher prices. This dynamic induces firms to increase output to sell more goods. The resulting supply increase causes prices to normalize and output to remain elevated.

Changes in Aggregate Supply

A shift in aggregate supply can be attributed to many variables, including changes in the size and quality of labor, technological innovations, an increase in wages, an increase in production costs, changes in producer taxes, and subsidies and changes in inflation. Some of these factors lead to positive changes in aggregate supply while others cause aggregate supply to decline. For example, increased labor efficiency, perhaps through outsourcing or automation, raises supply output by decreasing the labor cost per unit of supply. By contrast, wage increases place downward pressure on aggregate supply by increasing production costs.

Aggregate Supply Over the Short and Long Run

In the short run, aggregate supply responds to higher demand (and prices) by increasing the use of current inputs in the production process. In the short run, the level of capital is fixed, and a company cannot, for example, erect a new factory or introduce a new technology to increase production efficiency. Instead, the company ramps up supply by getting more out of its existing factors of production, such as assigning workers more hours or increasing the use of existing technology.

In the long run, however, aggregate supply is not affected by the price level and is driven only by improvements in productivity and efficiency. Such improvements include increases in the level of skill and education among workers, technological advancements, and increases in capital. Certain economic viewpoints, such as the Keynesian theory, assert that long-run aggregate supply is still price elastic up to a certain point. Once this point is reached, supply becomes insensitive to changes in price.

Example of Aggregate Supply

XYZ Corporation produces 100,000 widgets per quarter at a total expense of $1 million, but the cost of a critical component that accounts for 10% of that expense doubles in price because of a shortage of materials or other external factors. In that event, XYZ Corporation could produce only 90,909 widgets if it is still spending $1 million on production. This reduction would represent a decrease in aggregate supply. In this example, the lower aggregate supply could lead to demand exceeding output. That, coupled with the increase in production costs, is likely to lead to a rise in price.

What Is Alpha?

Alpha (α) is a term used in investing to describe an investment strategy’s ability to beat the market, or its “edge.” Alpha is thus also often referred to as “excess return” or “abnormal rate of return,” which refers to the idea that markets are efficient, and so there is no way to systematically earn returns that exceed the broad market as a whole. Alpha is often used in conjunction with beta (the Greek letter β), which measures the broad market’s overall volatility or risk, known as systematic market risk.

Alpha is used in finance as a measure of performance, indicating when a strategy, trader, or portfolio manager has managed to beat the market return over some period. Alpha, often considered the active return on an investment, gauges the performance of an investment against a market index or benchmark that is considered to represent the market’s movement as a whole.

The excess return of an investment relative to the return of a benchmark index is the investment’s alpha. Alpha may be positive or negative and is the result of active investing. Beta, on the other hand, can be earned through passive index investing.

Understanding Alpha

Alpha is one of five popular technical investment risk ratios. The others are beta, standard deviation, R-squared, and the Sharpe ratio. These are all statistical measurements used in modern portfolio theory (MPT). All of these indicators are intended to help investors determine the risk-return profile of an investment.

Active portfolio managers seek to generate alpha in diversified portfolios, with diversification intended to eliminate unsystematic risk. Because alpha represents the performance of a portfolio relative to a benchmark, it is often considered to represent the value that a portfolio manager adds to or subtracts from a fund’s return.

In other words, alpha is the return on an investment that is not a result of a general movement in the greater market. As such, an alpha of zero would indicate that the portfolio or fund is tracking perfectly with the benchmark index and that the manager has not added or lost any additional value compared to the broad market.

The concept of alpha became more popular with the advent of smart beta index funds tied to indexes like the Standard & Poor’s 500 index and the Wilshire 5000 Total Market Index. These funds attempt to enhance the performance of a portfolio that tracks a targeted subset of the market.

Despite the considerable desirability of alpha in a portfolio, many index benchmarks manage to beat asset managers the vast majority of the time. Due in part to a growing lack of faith in traditional financial advising brought about by this trend, more and more investors are switching to low-cost, passive online advisors (often called roboadvisors​) who exclusively or almost exclusively invest clients’ capital into index-tracking funds, the rationale being that if they cannot beat the market they may as well join it.

Moreover, because most “traditional” financial advisors charge a fee, when one manages a portfolio and nets an alpha of zero, it actually represents a slight net loss for the investor. For example, suppose that Jim, a financial advisor, charges 1% of a portfolio’s value for his services and that during a 12-month period Jim managed to produce an alpha of 0.75 for the portfolio of one of his clients, Frank. While Jim has indeed helped the performance of Frank’s portfolio, the fee that Jim charges is in excess of the alpha he has generated, so Frank’s portfolio has experienced a net loss. For investors, the example highlights the importance of considering fees in conjunction with performance returns and alpha.

The Efficient Market Hypothesis (EMH) postulates that market prices incorporate all available information at all times, and so securities are always properly priced (the market is efficient.) Therefore, according to the EMH, there is no way to systematically identify and take advantage of mispricings in the market because they do not exist.

If mispricings are identified, they are quickly arbitraged away and so persistent patterns of market anomalies that can be taken advantage of tend to be few and far between.

Empirical evidence comparing historical returns of active mutual funds relative to their passive benchmarks indicates that fewer than 10% of all active funds are able to earn a positive alpha over a 10-plus year time period, and this percentage falls once taxes and fees are taken into consideration. In other words, alpha is hard to come by, especially after taxes and fees.

Because beta risk can be isolated by diversifying and hedging various risks (which comes with various transaction costs), some have proposed that alpha does not really exist, but that it simply represents the compensation for taking some un-hedged risk that hadn’t been identified or was overlooked.

Seeking Investment Alpha

Alpha is commonly used to rank active mutual funds as well as all other types of investments. It is often represented as a single number (like +3.0 or -5.0), and this typically refers to a percentage measuring how the portfolio or fund performed compared to the referenced benchmark index (i.e., 3% better or 5% worse).

Deeper analysis of alpha may also include “Jensen’s alpha.” Jensen’s alpha takes into consideration the capital asset pricing model (CAPM) market theory and includes a risk-adjusted component in its calculation. Beta (or the beta coefficient) is used in the CAPM, which calculates the expected return of an asset based on its own particular beta and the expected market returns. Alpha and beta are used together by investment managers to calculate, compare, and analyze returns.

The entire investing universe offers a broad range of securities, investment products, and advisory options for investors to consider. Different market cycles also have an influence on the alpha of investments across different asset classes. This is why risk-return metrics are important to consider in conjunction with alpha.

Examples

This is illustrated in the following two historical examples for a fixed income ETF and an equity ETF:

The iShares Convertible Bond ETF (ICVT) is a fixed income investment with low risk. It tracks a customized index called the Bloomberg U.S. Convertible Cash Pay Bond > $250MM Index. The 3-year standard deviation was 18.94%, as of Feb. 28, 2022. The year-to-date return, as of Feb. 28, 2022, was -6.67%. The Bloomberg U.S. Convertible Cash Pay Bond > $250MM Index had a return of -13.17% over the same period. Therefore, the alpha for ICVT was -0 12% in comparison to the Bloomberg U.S. Aggregate Index and a 3-year standard deviation of 18.97%.

However, since the aggregate bond index is not the proper benchmark for ICVT (it should be the Bloomberg Convertible index), this alpha may not be as large as initially thought; and in fact, may be misattributed since convertible bonds have far riskier profiles than plain vanilla bonds.

The WisdomTree U.S. Quality Dividend Growth Fund (DGRW) is an equity investment with higher market risk that seeks to invest in dividend growth equities. Its holdings track a customized index called the WisdomTree U.S. Quality Dividend Growth Index. It had a three-year annualized standard deviation of 10.58%, higher than ICVT.

As of Feb. 28, 2022, DGRW annualized return was 18.1%, which was also higher than the S&P 500 at 16.4%, so it had an alpha of 1.7% in comparison to the S&P 500. But again, the S&P 500 may not be the correct benchmark for this ETF, since dividend-paying growth stocks are a very particular subset of the overall stock market, and may not even be inclusive of the 500 most valuable stocks in America.

Alpha Considerations

While alpha has been called the “holy grail” of investing, and as such, receives a lot of attention from investors and advisors alike, there are a couple of important considerations that one should take into account when using alpha.

1. A basic calculation of alpha subtracts the total return of an investment from a comparable benchmark in its asset category. This alpha calculation is primarily only used against a comparable asset category benchmark, as noted in the examples above. Therefore, it does not measure the outperformance of an equity ETF versus a fixed income benchmark. This alpha is also best used when comparing the performance of similar asset investments. Thus, the alpha of the equity ETF, DGRW, is not relatively comparable to the alpha of the fixed income ETF, ICVT.
2. Some references to alpha may refer to a more advanced technique. Jensen’s alpha takes into consideration CAPM theory and risk-adjusted measures by utilizing the risk-free rate and beta.

When using a generated alpha calculation it is important to understand the calculations involved. Alpha can be calculated using various different index benchmarks within an asset class. In some cases, there might not be a suitable pre-existing index, in which case advisors may use algorithms and other models to simulate an index for comparative alpha calculation purposes.

Alpha can also refer to the abnormal rate of return on a security or portfolio in excess of what would be predicted by an equilibrium model like CAPM. In this instance, a CAPM model might aim to estimate returns for investors at various points along an efficient frontier. The CAPM analysis might estimate that a portfolio should earn 10% based on the portfolio’s risk profile. If the portfolio actually earns 15%, the portfolio’s alpha would be 5.0, or +5% over what was predicted in the CAPM model.