# 1.3 Modern Approach

**Key points**

Modern asset pricing assumes the existence of a trade-off between risk and returns and that only systematic risk factors should enter pricing equations.

Single factor models like the CAPM, while widely used for private asset pricing are not robust and fail to capture risk and return dynamics.

Multi-factor models offer a more suitable approach. They posit the existence of several priced risk factors, the aggregation of which explains the risk premia required by investors.

The risk factor exposures (or loadings) of individual assets are typically denoted as betas () and risk factor prices or premia as lambdas ().

While the measurement of risk is not an objective of the fair-value framework, from the point of view of finance theory, the **starting point of any asset-pricing approach is to postulate the existence of a trade-off between risk and returns.** From this initial postulate, the main question is to determine the appropriate measure of risk, from which a corresponding measure of expected returns, that is, the appropriate risk-adjusted discount rate, can be derived.

A second tenet of modern finance theory is that idiosyncratic or company-specific risks cancel each other out in a well-diversified portfolio, and therefore **only systematic risks should enter into pricing equations.**

Hence, academic finance provides **a framework for estimating investors' expected rates of return given common sources of risk found in financial assets**. Expected returns predicted by statistically robust risk-factor models, taking into account current market conditions, provide a basis for the 'fair' discount rate that should prevail in the principal market.

Below, we briefly discuss standard factor models of expected returns, academic guidance to determine which factors should be used in such models, how they are estimated for assets traded in liquid markets where time series of prices and returns are readily available, and how this approach may be applied to seldom-traded private assets like unlisted infrastructure.

In other research, we also discuss the relevance of risk factors identified in the academic literature (Blanc-Brude & Tran, 2019) to the valuation of infrastructure companies, and the statistical approach taken to estimate the value of factor prices in unlisted infrastructure.

_{Blanc-Brude, F. & Tran, C. (2019). Which factors explain unlisted infrastructure asset prices? Evidence from 15 years of secondary market transaction data. }_{EDHEC Infrastructure Institute}_{. }_{https://publishing.edhecinfra.com/papers/2019_blanc-brude_tran.pdf}