What Is Annualization?

To annualize a number means to convert a short-term calculation or rate into an annual rate. Typically, an investment that yields a short-term rate of return is annualized to determine an annual rate of return, which may also include compounding or reinvestment of interest and dividends. It helps to annualize a rate of return to better compare the performance of one security versus another.

Annualization is a similar concept to reporting financial figures on an annual basis.

Understanding Annualization

When a number is annualized, it’s usually for rates of less than one year in duration. If the yield being considered is subject to compounding, annualization will also account for the effects of compounding. Annualizing can be used to determine the financial performance of an asset, security, or company.

When a number is annualized, the short-term performance or result is used to forecast the performance for the next twelve months or one year. Below are a few of the most common examples of when annualizing is utilized.

Company Performance

An annualized return is similar to a run rate, which refers to the financial performance of a company based on current financial information as a predictor of future performance. The run rate functions as an extrapolation of current financial performance and assumes that current conditions will continue.

Loans

The annualized cost of loan products is often expressed as an annual percentage rate (APR). The APR considers every cost associated with the loan, such as interest and origination fees, and converts the total of these costs to an annual rate that is a percentage of the amount borrowed.

Loan rates for short-term borrowings can be annualized as well. Loan products including payday loans and title loans, charge a flat finance fee such as $15 or $20 to borrow a nominal amount for a few weeks to a month. On the surface, the $20 fee for one month doesn’t appear to be exorbitant. However, annualizing the number equates to $240 and could be extremely large relative to the loan amount.

Tax Purposes

Taxpayers annualize by converting a tax period of less than one year into an annual period. The conversion helps wage earners establish an effective tax plan and manage any tax implications.

For example, taxpayers can multiply their monthly income by 12 months to determine their annualized income. Annualizing income can help taxpayers estimate their effective tax rate based on the calculation and can be helpful in budgeting their quarterly taxes.

Example: Investments

Investments are annualized frequently. Let’s say a stock returned 1% in one month in capital gains on a simple (not compounding) basis. The annualized rate of return would be equal to 12% because there are 12 months in one year. In other words, you multiply the shorter-term rate of return by the number of periods that make up one year. A monthly return would be multiplied by 12 months.

However, let’s say an investment returned 1% in one week. To annualize the return, we’d multiply the 1% by the number of weeks in one year or 52 weeks. The annualized return would be 52%.

Quarterly rates of return are often annualized for comparative purposes. A stock or bond might return 5% in Q1. We could annualize the return by multiplying 5% by the number of periods or quarters in a year. The investment would have an annualized return of 20% because there are four quarters in one year or (5% * 4 = 20%).

Special Considerations and Limitations of Annualizing

The annualized rate of return or forecast is not guaranteed and can change due to outside factors and market conditions. Consider an investment that returns 1% in one month; the security would return 12% on an annualized basis. However, the annualized return of a stock cannot be forecasted with a high degree of certainty using the stock’s short-term performance.

There are many factors that could impact a stock’s price throughout the year such as market volatility, the company’s financial performance, and macroeconomic conditions. As a result, fluctuations in the stock price would make the original annualized forecast incorrect. For example, a stock might return 1% in month one and return -3% the following month.

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.

What Is the Advance/Decline (A/D) Line?

The advance/decline line (or A/D line) is a technical indicator that plots the difference between the number of advancing and declining stocks on a daily basis. The indicator is cumulative, with a positive number being added to the prior number, or if the number is negative it is subtracted from the prior number.

The A/D line is used to show market sentiment, as it tells traders whether there are more stocks rising or falling. It is used to confirm price trends in major indexes, and can also warn of reversals when divergence occurs.

The Formula for Advance/Decline (A/D) Line Is:


$\begin{aligned} &\text{A/D} = \text{Net Advances} + \begin{cases} \text{PA, if PA value exists} \\ \text{0, if no PA value} \\ \end{cases} \\ &\textbf{where:} \\ &\text{Net Advances} = \text{Difference between number of daily} \\ &\text{ascending and declining stocks} \\ &\text{PA} = \text{Previous Advances} \\ &\text{Previous Advances} = \text{Prior indicator reading} \\ \end{aligned}$​A/D=Net Advances+{PA, if PA value exists0, if no PA value​where:Net Advances=Difference between number of dailyascending and declining stocksPA=Previous AdvancesPrevious Advances=Prior indicator reading​

How to Calculate the A/D Line

1. Subtract the number of stocks that finished lower on the day from the number of stocks that finished higher on the day. This will give you the Net Advances.
2. If this is the first time calculating the average, the Net Advances will be the first value used for the indicator.
3. On the next day, calculate the Net Advances for that day. Add to the total from the prior day if positive or subtract if negative.
4. Repeat steps one and three daily.

What Does the A/D Line Tell You?

The A/D line is used to confirm the strength of a current trend and its likelihood of reversing. The indicator shows if the majority of stocks are participating in the direction of the market. 

If the indexes are moving up but the A/D line is sloping downwards, called bearish divergence, it’s a sign that the markets are losing their breadth and may be about to reverse direction. If the slope of the A/D line is up and the market is trending upward, then the market is said to be healthy.

Conversely, if the indexes are continuing to move lower and the A/D line has turned upwards, called bullish divergence, it may be an indication that the sellers are losing their conviction. If the A/D line and the markets are both trending lower together, there is a greater chance that declining prices will continue.

Difference Between the A/D Line and Arms Index (TRIN)

The A/D line is typically used as a longer-term indicator, showing how many stocks are rising and falling over time. The Arms Index (TRIN), on the other hand, is typically a shorter-term indicator that measures the ratio of advancing stocks to the ratio of advancing volume. Because the calculations and the time frame they focus on are different, both these indicators tell traders different pieces of information.

Limitations of Using the A/D Line

The A/D line won’t always provide accurate readings in regards to NASDAQ stocks. This is because the NASDAQ frequently lists small speculative companies, many of which eventually fail or get delisted. While the stocks get delisted on the exchange, they remain in the prior calculated values of the A/D line. This then affects future calculations which are added to the cumulative prior value. Because of this, the A/D line will sometimes fall for extended periods of time, even while NASDAQ-related indexes are rising.

Another thing to be aware of is that some indexes are market capitalization weighted. This means that the bigger the company the more impact they have on the index’s movement. The A/D line gives equal weight to all stocks. Therefore, it is a better gauge of the average small to mid-cap stock, and not the fewer in number large or mega-cap stocks.

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What Is Adverse Selection?

Adverse selection refers generally to a situation in which sellers have information that buyers do not have, or vice versa, about some aspect of product quality. In other words, it is a case where asymmetric information is exploited. Asymmetric information, also called information failure, happens when one party to a transaction has greater material knowledge than the other party.

Typically, the more knowledgeable party is the seller. Symmetric information is when both parties have equal knowledge.

In the case of insurance, adverse selection is the tendency of those in dangerous jobs or high-risk lifestyles to purchase products like life insurance. In these cases, it is the buyer who actually has more knowledge (i.e., about their health). To fight adverse selection, insurance companies reduce exposure to large claims by limiting coverage or raising premiums.

Understanding Adverse Selection

Adverse selection occurs when one party in a negotiation has relevant information the other party lacks. The asymmetry of information often leads to making bad decisions, such as doing more business with less profitable or riskier market segments.

In the case of insurance, avoiding adverse selection requires identifying groups of people more at risk than the general population and charging them more money. For example, life insurance companies go through underwriting when evaluating whether to give an applicant a policy and what premium to charge.

Underwriters typically evaluate an applicant’s height, weight, current health, medical history, family history, occupation, hobbies, driving record, and lifestyle risks such as smoking; all these issues impact an applicant’s health and the company’s potential for paying a claim. The insurance company then determines whether to give the applicant a policy and what premium to charge for taking on that risk.

Consequences of Adverse Selection

A seller may have better information than a buyer about products and services being offered, putting the buyer at a disadvantage in the transaction. For example, a company’s managers may more willingly issue shares when they know the share price is overvalued compared to the real value; buyers can end up buying overvalued shares and lose money. In the secondhand car market, a seller may know about a vehicle’s defect and charge the buyer more without disclosing the issue.

The general consequence of adverse selection is that it increases costs since consumers lack information held by sellers or producers, creating an asymmetry in the market. This can also lower consumption as buyers may be wary of the quality of the products that are offered for sale. Or, it may exclude certain consumers that do not have access to or cannot afford to obtain information that could lead them to make better buying decisions.

One indirect effect of this is a negative impact on consumers’ health and well-being. If you buy a faulty product or dangerous medication because you don’t have good information, consuming these products can cause physical harm. Or, by refraining from buying certain healthcare products (e.g., vaccines), consumers may wrongly judge a safe intervention as overly risky.

Adverse Selection in Insurance

Because of adverse selection, insurers find that high-risk people are more willing to take out and pay greater premiums for policies. If the company charges an average price but only high-risk consumers buy, the company takes a financial loss by paying out more benefits or claims.

However, by increasing premiums for high-risk policyholders, the company has more money with which to pay those benefits. For example, a life insurance company charges higher premiums for race car drivers. A car insurance company charges more for customers living in high-crime areas. A health insurance company charges higher premiums for customers who smoke. In contrast, customers who do not engage in risky behaviors are less likely to pay for insurance due to increasing policy costs.

A prime example of adverse selection in regard to life or health insurance coverage is a smoker who successfully manages to obtain insurance coverage as a nonsmoker. Smoking is a key identified risk factor for life insurance or health insurance, so a smoker must pay higher premiums to obtain the same coverage level as a nonsmoker. By concealing their behavioral choice to smoke, an applicant is leading the insurance company to make decisions on coverage or premium costs that are adverse to the insurance company’s management of financial risk.

Another example of adverse selection in the case of auto insurance would be a situation where the applicant obtains insurance coverage based on providing a residence address in an area with a very low crime rate when the applicant actually lives in an area with a very high crime rate. Obviously, the risk of the applicant’s vehicle being stolen, vandalized, or otherwise damaged when regularly parked in a high-crime area is substantially greater than if the vehicle was regularly parked in a low-crime area.

How to Minimize Adverse Selection

Adverse selection by increasing access to information, thus minimizing asymmetries. For consumers, the internet has greatly increased access while reducing costs. Crowdsourced information in the form of user reviews along with more formal reviews by bloggers or specialist websites are often free and warn potential buyers about otherwise obscure issues around quality.

Warranties and guarantees offered by sellers can also help, allowing consumers to use a product risk-free for a certain period to see if it has flaws or quality issues and the ability to return them without consequence if there are issues. Laws and regulations can also help, such as Lemon Laws in the used car industry. Federal regulatory authorities such as the FDA also help ensure that products are safe and effective for consumers.

Insurers reduce adverse selection by requesting medical information from applicants in the form of requiring paramedical examinations, querying doctors’ offices for medical records, and looking at one’s family history. This gives the insurance company more information that an applicant may fail to disclose on their own.

Moral Hazard vs. Adverse Selection

Like adverse selection, moral hazard occurs when there is asymmetric information between two parties, but where a change in the behavior of one party is exposed after a deal is struck. Adverse selection occurs when there’s a lack of symmetric information prior to a deal between a buyer and a seller.

Moral hazard is the risk that one party has not entered into the contract in good faith or has provided false details about its assets, liabilities, or credit capacity. For instance, in the investment banking sector, it may become known that government regulatory bodies will bail out failing banks; as a result, bank employees may take on excessive amounts of risk to score lucrative bonuses knowing that if their risky bets do not pan out, the bank will be saved anyhow.

The Lemons Problem

The lemons problem refers to issues that arise regarding the value of an investment or product due to asymmetric information possessed by the buyer and the seller.

The lemons problem was put forward in a research paper, “The Market for ‘Lemons’: Quality Uncertainty and the Market Mechanism,” written in the late 1960s by George A. Akerlof, an economist and professor at the University of California, Berkeley. The tag phrase identifying the problem came from the example of used cars Akerlof used to illustrate the concept of asymmetric information, as defective used cars are commonly referred to as lemons. The takeaway is that due to adverse selection, the only used cars left on the market will ultimately be lemons.

The lemons problem exists in the marketplace for both consumer and business products, and also in the arena of investing, related to the disparity in the perceived value of an investment between buyers and sellers. The lemons problem is also prevalent in financial sector areas, including insurance and credit markets. For example, in the realm of corporate finance, a lender has asymmetrical and less-than-ideal information regarding the actual creditworthiness of a borrower.

The Bottom Line

Contrary to assumptions made by mainstream economic and financial models, information is not symmetrically accessible and available to all actors in a market. In particular, sellers and producers often have far more information about what they are selling than do buyers. This information asymmetry can lead to market inefficiencies via what is known as adverse selection. In insurance markets, applicants have more information about themselves than do insurers, meaning that they withhold key information about being higher-risk.