Proposed by economist Stephen Ross in 1976,[1] it is widely believed to be an improved alternative to its predecessor, the capital asset pricing model (CAPM).
Consequently, it provides traders with an indication of ‘true’ asset value and enables exploitation of market discrepancies via arbitrage.
The linear factor model structure of the APT is used as the basis for evaluating asset allocation, the performance of managed funds as well as the calculation of cost of capital.
A 1986 article written by Gregory Connor and Robert Korajczyk, utilised the APT framework and applied it to portfolio performance measurement suggesting that the Jensen coefficient is an acceptable measurement of portfolio performance.
[4] APT is a single-period static model, which helps investors understand the trade-off between risk and return.
It is the realisation of a positive expected return from overvalued or undervalued securities in the inefficient market without any incremental risk and zero additional investments.
The asset price today should equal the sum of all future cash flows discounted at the APT rate, where the expected return of the asset is a linear function of various factors, and sensitivity to changes in each factor is represented by a factor-specific beta coefficient.
The APT differs from the CAPM in that it is less restrictive in its assumptions, making it more flexible for use in a wider range of application.
Thus, it possesses greator explanatory power (as opposed to statistical) for expected asset returns.
In contrast, the APT model suggests that each stock reacts uniquely to various macroeconomic factors and thus the impact of each must be accounted for separately.
In many instances the CAPM, as a model to estimate expected returns, has empirically outperformed the more advanced APT.
[5] Additionally, the APT can be seen as a "supply-side" model, since its beta coefficients reflect the sensitivity of the underlying asset to economic factors.
Thus, factor shocks would cause structural changes in assets' expected returns, or in the case of stocks, in firms' profitabilities.
As with the CAPM, the factor-specific betas are found via a linear regression of historical security returns on the factor in question.
Several a priori guidelines as to the characteristics required of potential factors are, however, suggested: Chen, Roll and Ross identified the following macro-economic factors as significant in explaining security returns:[6] As a practical matter, indices or spot or futures market prices may be used in place of macro-economic factors, which are reported at low frequency (e.g. monthly) and often with significant estimation errors.
In 1983 Bruno Solnik created an extension of the original arbitrage pricing theory to include risk related to international exchange rates hence making the model applicable international markets with multi-currency transactions.
[7] Fama and French originally proposed a three-factor model in 1995 which, consistent with the suggestion from Solnik above suggests that integrated international markets may experience a common set of factors, hence making it possible to price assets in all integrated markets using their model.
The Fama and French three factor model attempts to explain stock returns based on market risk, size, and value.
[8] A 2012 paper aimed to empirically investigate Solnik’s IAPT model and the suggestion that base currency fluctuations have a direct and comprehendible effect on the risk premiums of assets.
This, along with empirical data tests validates the idea that foreign currency fluctuations have a direct effect on risk premiums and the factor loadings included in the APT model, hence, confirming the validity of the IAPT model.