In summary, CAPM is a single-factor model that uses market risk as the only factor to determine the expected rate of return, making it simpler and more suitable for short-term investment decisions. On the other hand, APT is a multi-factor model that considers multiple factors in addition to market risk, making it more complex and more appropriate for long-term investments. We can see that the expected returns of the stocks are consistent with their factor exposures and risk premiums. If we find another stock, C, that has the same factor exposures as A, but has an expected return of 14%, we can conclude that C is overpriced and we can create an arbitrage opportunity by selling C and buying A. Similarly, if we find another stock, D, that has the same factor exposures as B, but has an expected return of 8%, we can conclude that D is underpriced and we can create an arbitrage opportunity by buying D and selling B. CAPM is widely used in the finance industry due to its simplicity and ease of implementation.
B – Sensitivity of the stock with respect to the factor; also referred to as beta factor 1, 2 …
The reason for this was that CAPM has long struggled to prove itself accurate in empirical tests. Intuitively, the notion of one single factor explaining the return on any asset sounds unlikely, and it has generally proven to be this way. In particular there are size effects and value effects which cause inaccuracies in CAPM for small stocks and value stocks.
It equals the expected return on the pure factor portfolio i.e. a portfolio that is only sensitive to that risk factor minus the risk-free rate. On the other hand, it is not always possible to know the right factors or to find the right data, which is when CAPM may be preferred. We will review some of the empirical studies and tests that have been conducted to evaluate the performance and accuracy of each model, and what are the main findings and conclusions. We will also discuss some of the practical uses and examples of each model in various fields and contexts, such as portfolio management, capital budgeting, asset valuation, and performance measurement. An analyst determines the Rf, Rm, and βi figures, but investors usually use a beta figure provided by a third party.
Two of the most influential models in this field are the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT). Both models attempt to capture the relationship between risk and return, but they differ in their assumptions, implications, and empirical validity. In this section, we will review some of the empirical studies that have tested and compared the performance of CAPM and APT, and discuss their strengths and limitations. Expert insights suggest that the choice between CAPM and APT depends on the specific investment context.
Arbitrage Pricing Theory Formula
The APT also does not require the existence of a risk-free asset or a market portfolio, and it does not assume that investors are homogeneous or hold the same portfolio. The next model, proposed by Ross (1976), the Arbitrage Pricing Theory (APT), is yet another significant asset pricing model. APY is different from CAPM and Fama-French in that it allows for numerous systematic factors that affect asset returns rather than assuming a single market driver. According to APT, an assets sensitivity to several macroeconomic and fundamental factors determines its predicted return. Contrary to CAPM, APT uses factor loadings to calculate expected returns rather than the beat notion. A big difference between CAPM and the arbitrage pricing theory is that APT does not spell out specific risk factors or even the number of factors involved.
Watch this video to see an example of how investors use APT to their advantage. Given that CAPM is relatively easy to calculate, I suggest computing this initially, and then evaluating whether it is worthwhile to continue to evaluate the APT. Either method should give you a reasonable estimate of whether an asset merits your investment at the current time. Whereas, the CAPM model is not much robust as the APT and can evaluate the asset return over the risk compared to the fixed asset return. The Required ROI getting from the APT model can be used to evaluate if the stocks are over-priced or underpriced as they have the best investment options.
It assumes that investors are rational, risk-averse, and have homogenous expectations, and that all relevant information is reflected in stock prices (Fama, 1970). Both CAPM and APT provide frameworks for understanding the relationship between risk and return. CAPM, a cornerstone of modern finance, posits a simplified relationship between an asset’s return and its correlation with the overall market (systematic risk).
- This led to the development of the Fama-French Three-Factor Model, which incorporates the market factor along with the size and value factors to provide a more comprehensive explanation of asset returns.
- Contrary to CAPM, APT uses factor loadings to calculate expected returns rather than the beat notion.
- Likewise if you return to an APT model after a few months, you need to consider whether the factors you have used still make sense.
- The fact that both models have stood the test of time indicates that both have their merits.
- Historical associations are less accurate at forecasting future asset returns because of shifting economic conditions and market dynamics.
Assumptions
At first glance, the CAPM and APT formulas look identical, but the CAPM has only one factor and one beta. Conversely, the APT formula has multiple factors that include non-company factors, which requires the asset’s beta in relation to each separate factor. However, the APT does not provide insight into what these factors could be, so users of the APT model must analytically determine relevant factors that might affect the asset’s returns. On the other hand, the factor used in the CAPM is the difference between the expected market rate of return and the risk-free rate of return. Additionally, each model relies on historical data and makes the assumption that relationships from the past will continue into the future.
CAPM focuses on a single factor, the market risk, which is represented by the beta coefficient. On the other hand, APT considers multiple factors that can influence asset returns, such as interest rates, inflation, industry-specific factors, and macroeconomic variables. APT allows for a more comprehensive analysis of the factors affecting asset prices. While the CAPM is a single-factor model, APT allows for multi-factor models to describe risk and return relationship of a stock. Furthermore, researchers are also investigating how non-financial elements including environmental, social, and governance (ESG) considerations affect asset price. New models that combine ESG measures and assess the financial effects of these factors on asset returns have been developed as a result of the increased interest in sustainable and responsible investment.
- Third, it may not capture all the sources of risk that affect an asset’s return, as it ignores other factors such as size, value, momentum, liquidity, and industry effects.
- Generally speaking APT performs better in empirical contexts, however you have to decide for yourself what relevance academic studies have to your investment decisions.
- While CAPM is simpler to use and widely accepted, APT provides a more comprehensive and flexible framework for estimating expected returns, making it suitable for more complex investment scenarios.
- However, the factors must be systematic in nature because any unique risk can be diversified away and isn’t compensated by an efficient market.
Let’s consider an example to explain the CAPM Model :
The issue is whether the accuracy gain is enough to merit the time and effort involved in deciding what factors to use, and gathering the relevant data. An asset’s or portfolio’s beta measures the theoretical volatility in relation to the overall market. For example, if a portfolio has a beta of 1.25 in relation to the Standard & Poor’s 500 Index (S&P 500), it is theoretically 25% more volatile than the S&P 500 Index. Estimating the empirical performance of APT is a more difficult job, as the usefulness of the model is dependent on the choice of factors, however the APT does generally perform well empirically. The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets.
A review of the empirical studies that have tested and compared the performance of CAPM and APT
The use of historical data, the assumptions behind the models, the dependence on simplified risk metrics, and the assumptions relating to investor behaviour are all problems. However, current research tries to overcome these constraints by investigating other models, adding extra elements, and utilising technology developments. Researchers attempt to give more precise and comprehensive frameworks for comprehending and forecasting asset returns in difference between capm and apt actual financial markets by continuing to develop and refine asset pricing models.
For investors seeking a simple and readily applicable model, the CAPM may suffice. For sophisticated investors and analysts seeking a more comprehensive understanding of risk and return, the APT, despite its complexity, offers a more robust framework. Statistical data supports the notion that multiple factors influence asset prices, lending credence to the APT’s multi-factor approach. The CAPM’s simplicity makes it a practical tool for investors and portfolio managers. Its reliance on readily available market data and a single risk factor simplifies the calculation of expected returns.
N – Risk premium associated with respective factor
To account for the effects of long-term sustainability and social responsibility on asset valuations and expected returns, ESG concerns are being incorporated into asset pricing models (Bollen and Whaley, 2019). Technology developments and the availability of enormous volumes of data have created new opportunities for asset pricing research. The analysis and modelling of asset returns can be done at a higher level thanks to the application of machine learning algorithms and artificial intelligence approaches. The accuracy of asset pricing predictions can be increased by using these approaches, which can spot intricate patterns and nonlinear linkages that conventional models could miss (Tsai et al., 2019). Thereafter, in 1976, economist Stephen Ross developed the arbitrage pricing theory (APT) as an alternative to the CAPM.
Second, it is difficult to empirically test and validate, as it requires the estimation of the true market portfolio, which is unobservable and may vary over time. Third, it may not capture all the sources of risk that affect an asset’s return, as it ignores other factors such as size, value, momentum, liquidity, and industry effects. Navigating the intricate world of stock valuation requires a deep understanding of the tools and models designed to predict potential returns. Two prominent models, the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT), offer distinct approaches to assessing asset prices and expected returns.