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In other, we also discuss the relevance of risk factors identified in the academic literature to the valuation of infrastructure companies, and the statistical approach taken to estimate the value of factor prices in unlisted infrastructure.

Models of Expected Returns

The simplest model of expected returns is the well-known capital asset pricing model (CAPM)

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, according to which higher returns can only be achieved by exposing a well-diversified portfolio to higher market risk, also known as a higher market beta. This model serves as the basis for the discount-rate formula described in equation
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.

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The

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 factors used in such models can include industrial and geographic segmentations of the data or various economic mechanisms that can be expected to have a systematic effect on average returns such as the tendency of well-performing firms to continue to perform (the so-called momentum factor), as well as factors sometimes identified as 'anomalies' (like the outperformance of a 'low volatility' factor).

Risk-Factor Pricing

Beyond single- or multi-factor CAPMs, the second building block of modern asset pricing is the arbitrage pricing theory (APT)

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. Under arbitrage pricing, pure arbitrage profits are not possible and differences between expected returns (or prices) and actual returns are the result of individual assets' relative exposure (betas) to a combination of zero-mean risk factors (or 'surprises') 
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. Hence,

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In effect, CAPM and APT are the only two theoretical frameworks that provide a solid foundation for computing the trade-off between risk and returns

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. APT in particular leaves the identification of the relevant factors open and justifies the need to explicitly identify and test the factors impacting returns for different types of financial assets.

References

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