In finance, arbitrage pricing theory (APT) is a multi-factor model for asset pricing which relates various macro-economic (systematic) risk variables to the pricing of financial assets. Proposed by economist Stephen Ross in 1976, it is widely believed to be an improved alternative to its predecessor, the Capital Asset Pricing Model (CAPM). APT is founded upon the law of one price, which suggests that within an equilibrium market, rational investors will implement arbitrage such that the equilibrium price is eventually realised. As such, APT argues that when opportunities for arbitrage are exhausted in a given period, then the expected return of an asset is a linear function of various factors or theoretical market indices, where sensitivities of each factor is represented by a factor-specific beta coefficient or factor loading. 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. Model APT is a single-period static model, which helps investors understand the trade-off between risk and return. The average investor aims to optimise the returns for any given level or risk and as such, expects a positive return for bearing greater risk. As per the APT model, risky asset returns are said to follow a factor intensity structure if they can be expressed as: where is a constant for asset is a systematic factor is the sensitivity of the th asset to factor , also called factor loading, and is the risky asset's idiosyncratic random shock with mean zero. Idiosyncratic shocks are assumed to be uncorrelated across assets and uncorrelated with the factors. The APT model states that if asset returns follow a factor structure then the following relation exists between expected returns and the factor sensitivities: where is the risk premium of the factor, is the risk-free rate, That is, the expected return of an asset j is a linear function of the asset's sensitivities to the n factors. Note that there are some assumptions and requirements that have to be fulfilled for the latter to be correct: There must be perfect competition in the market, and the total number of factors may never surpass the total number of assets (in order to avoid the problem of matrix singularity). General Model