What Is an Asset Class?

An asset class is a grouping of investments that exhibit similar characteristics and are subject to the same laws and regulations. Asset classes are thus made up of instruments that often behave similarly to one another in the marketplace.

Understanding Asset Classes

Simply put, an asset class is a grouping of comparable financial securities. For example, IBM, MSFT, AAPL are a grouping of stocks. Asset classes and asset class categories are often mixed together. There is usually very little correlation and in some cases a negative correlation, between different asset classes. This characteristic is integral to the field of investing.

Historically, the three main asset classes have been equities (stocks), fixed income (bonds), and cash equivalent or money market instruments. Currently, most investment professionals include real estate, commodities, futures, other financial derivatives, and even cryptocurrencies in the asset class mix. Investment assets include both tangible and intangible instruments which investors buy and sell for the purposes of generating additional income, on either a short- or a long-term basis.

Financial advisors view investment vehicles as asset class categories that are used for diversification purposes. Each asset class is expected to reflect different risk and return investment characteristics and perform differently in any given market environment. Investors interested in maximizing return often do so by reducing portfolio risk through asset class diversification.

Financial advisors will help investors diversify their portfolios by combing assets from different asset classes that have different cash flows streams and varying degrees of risk. Investing in several different asset classes ensures a certain amount of diversity in investment selections. Diversification reduces risk and increases your probability of making a return.

Asset Class and Investing Strategy

Investors looking for alpha employ investment strategies focused on achieving alpha returns. Investment strategies can be tied to growth, value, income, or a variety of other factors that help to identify and categorize investment options according to a specific set of criteria. Some analysts link criteria to performance and/or valuation metrics such as earnings-per-share growth (EPS) or the price-to-earnings (P/E) ratio. Other analysts are less concerned with performance and more concerned with the asset type or class. An investment in a particular asset class is an investment in an asset that exhibits a certain set of characteristics. As a result, investments in the same asset class tend to have similar cash flows.

Asset Class Types

Equities (stocks), bonds (fixed-income securities), cash or marketable securities, and commodities are the most liquid asset classes and, therefore, the most quoted asset classes.

There are also alternative asset classes, such as real estate, and valuable inventory, such as artwork, stamps, and other tradable collectibles. Some analysts also refer to an investment in hedge funds, venture capital, crowdsourcing, or cryptocurrencies as examples of alternative investments. That said, an asset’s illiquidity does not speak to its return potential; It only means it may take more time to find a buyer to convert the asset to cash.

What Is the Australian Securities Exchange (ASX)?

The Australian Securities Exchange is headquartered in Sydney, Australia. The Exchange in its current form was created through the merger of the Australian Stock Exchange and Sydney Futures Exchange in 2006. The ASX acts as a market operator, clearing house, and payments facilitator. It also provides educational materials to retail investors.

Understanding the Australian Securities Exchange (ASX)

ASX is consistently ranked among the top exchanges globally. Other major exchanges include the Tokyo Stock Exchange or TSE, the New York Stock Exchange (NYSE), the Nasdaq, and the London Stock Exchange (LSE). Each exchange has specific listing requirements that include regular financial reports and minimum capital requirements. For example, in 2021, the NYSE has a key listing requirement that stipulated aggregate shareholders equity for last three fiscal years of greater than or equal to $10 million, a global market capitalization of $200 million, and a minimum share price of $4. In addition, for initial public offerings and secondary issuers must have 400 shareholders.

Australian Securities Exchange (ASX) and Electronic Trading

As with the majority of international exchanges, ASX’s relies on a hefty data center to help connect it to leading financial hubs and facilitate electronic trading. Electronic trading gained strong traction with NYSE’s 2005 acquisition of rival market the Archipelago Exchange—a fully electronic exchange that listed new and fast-growing companies. NYSE Arca was the new name following the acquisition. Cybersecurity is an increasing concern as exchanges become more interconnected via the internet.

ASX and Education

The Australian Securities Exchange has a strong emphasis on educating visitors to its website, the investing public, and current and potential listers. For example, for first-time investors, ASX offers free resources for understanding the public markets, exploring different asset classes, and developing a personal investment strategy. Visitors can download a series of tutorials and guidebooks. In addition, ASX offers a game-version of trading where players do not have to risk real money; instead, they can learn the basics in a risk-free environment.

What Is an Autoregressive Model?

A statistical model is autoregressive if it predicts future values based on past values. For example, an autoregressive model might seek to predict a stock’s future prices based on its past performance.

Understanding Autoregressive Models

Autoregressive models operate under the premise that past values have an effect on current values, which makes the statistical technique popular for analyzing nature, economics, and other processes that vary over time. Multiple regression models forecast a variable using a linear combination of predictors, whereas autoregressive models use a combination of past values of the variable.

An AR(1) autoregressive process is one in which the current value is based on the immediately preceding value, while an AR(2) process is one in which the current value is based on the previous two values. An AR(0) process is used for white noise and has no dependence between the terms. In addition to these variations, there are also many different ways to calculate the coefficients used in these calculations, such as the least squares method.

These concepts and techniques are used by technical analysts to forecast security prices. However, since autoregressive models base their predictions only on past information, they implicitly assume that the fundamental forces that influenced the past prices will not change over time. This can lead to surprising and inaccurate predictions if the underlying forces in question are in fact changing, such as if an industry is undergoing rapid and unprecedented technological transformation.

Nevertheless, traders continue to refine the use of autoregressive models for forecasting purposes. A great example is the Autoregressive Integrated Moving Average (ARIMA), a sophisticated autoregressive model that can take into account trends, cycles, seasonality, errors, and other non-static types of data when making forecasts.

Example of an Autoregressive Model

Autoregressive models are based on the assumption that past values have an effect on current values. For example, an investor using an autoregressive model to forecast stock prices would need to assume that new buyers and sellers of that stock are influenced by recent market transactions when deciding how much to offer or accept for the security.

Although this assumption will hold under most circumstances, this is not always the case. For example, in the years prior to the 2008 Financial Crisis, most investors were not aware of the risks posed by the large portfolios of mortgage-backed securities held by many financial firms. During those times, an investor using an autoregressive model to predict the performance of U.S. financial stocks would have had good reason to predict an ongoing trend of stable or rising stock prices in that sector. 

However, once it became public knowledge that many financial institutions were at risk of imminent collapse, investors suddenly became less concerned with these stocks’ recent prices and far more concerned with their underlying risk exposure. Therefore, the market rapidly revalued financial stocks to a much lower level, a move which would have utterly confounded an autoregressive model.

It is important to note that, in an autoregressive model, a one-time shock will affect the values of the calculated variables infinitely into the future. Therefore, the legacy of the financial crisis lives on in today’s autoregressive models.

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What Is At The Money (ATM)?

At the money (ATM) is a situation where an option’s strike price is identical to the current market price of the underlying security. An ATM option has a delta of ±0.50, positive if it is a call, negative for a put.

Both call and put options can be simultaneously ATM. For example, if XYZ stock is trading at $75, then the XYZ 75 call option is ATM and so is the XYZ 75 put option. ATM options have no intrinsic value, but will still have extrinsic or time value prior to expiration, and may be contrasted with either in the money (ITM) or out of the money (OTM) options.

Understanding At The Money (ATM)

At the money (ATM), sometimes referred to as “on the money”, is one of three terms used to describe the relationship between an option’s strike price and the underlying security’s price, also called the option’s moneyness.

Options can be in the money (ITM), out of the money (OTM), or ATM. ITM means the option has intrinsic value and OTM means it doesn’t. Simply put, ATM options are not in a position to profit if exercised, but still have value—there is still time before they expire so they may yet end up ITM.

The intrinsic value for a call option is calculated by subtracting the strike price from the underlying security’s current price. The intrinsic value for a put option, on the other hand, is calculated by subtracting the underlying asset’s current price from its strike price.

A call option is ITM when the option’s strike price is less than the underlying security’s current price. Conversely, a put option is ITM when the option’s strike price is greater than the underlying security’s stock price. Meanwhile, a call option is OTM when its strike price is greater than the current underlying security’s price and a put option is OTM when its strike price is less than the underlying asset’s current price.

Special Considerations

Options that are ATM are often used by traders to construct spreads and combinations. Straddles, for instance, will typically involve buying (or selling) both an ATM call and put.

ATM options are the most sensitive to various risk factors, known as an option’s “Greeks”. ATM options have a ±0.50 delta, but have the greatest amount of gamma, meaning that as the underlying moves its delta will move away from ±0.50 rapidly, and most rapidly as time to expiration nears.

ATM options are the most sensitive to time decay, as represented by an option’s theta. Moreover, their prices are most responsive to changes in volatility, especially for farther maturities, and is expressed by an option’s vega. Finally, ATM options are also most sensitive to changes in interest rates, as measured by the rho.

At The Money (ATM) and Near The Money

The term “near the money” is sometimes used to describe an option that is within 50 cents of being ATM. For example, assume an investor purchases a call option with a strike price of $50.50 and the underlying stock price is trading at $50. In this case, the call option is said to be near the money.

In the above example, the option would be near the money if the underlying stock price was trading between about $49.50 and $50.50. Near the money and ATM options are attractive when traders expect a big movement. Options that are even further OTM may also see a jump when a swing is anticipated.

Options Pricing for At The Money (ATM) Options

An option’s price is made up of intrinsic and extrinsic value. Extrinsic value is sometimes called time value, but time is not the only factor to consider when trading options. Implied volatility also plays a significant role in options pricing. 

Similar to OTM options, ATM options only have extrinsic value because they possess no intrinsic value. For example, assume an investor purchases an ATM call option with a strike price of $25 for a price of 50 cents. The extrinsic value is equivalent to 50 cents and is largely affected by the passage of time and changes in implied volatility.

Assuming volatility and the price stay steady, the closer the option gets to expiry the less extrinsic value it has. If the price of the underlying moves above the strike price to $27, the option now has $2 of intrinsic value, plus whatever extrinsic value remains.