Asset prices are computed each quarter by EDHECinfra using a discounted cash flow approach and discount rates calibrated from secondary market infrastructure equity transactions over time. 

The EDHECinfra Broadmarket Unlisted Equity Index is a calculated index. The prices used in the index are computed directly from available cash flow and market data, using a unified asset pricing methodology. 

The market value of the constituents included in the index are computed using a discounted cash flow (or income) methodology, using company-level information to forecast dividend payouts and shareholder loan repayments. A factor model of expected returns is calibrated to reflect the latest market price of risk and to determine the appropriate discount rate.

Thus, at any time t we have:

P_i=\frac{\sum_{t=1}^T CF_t}{\big(1+(R_f+E(\tilde{R_i}))\big)^t}

P_i is the price of asset i, paying CF_t until time T. R_f+E(\tilde{R_i}) is the approximate expected internal rate of return (IRR) at time t.

Cash Flow Data

For each company included in the index, the minimum required data described in the Data Collection Standard is collected and aggregated are categorised according to the TICCS® classification.

This data is then used to produce several forecasts: 

  • A Revenue Forecast is determined by human analysts and cross-validated; 
  • A Total Debt Service Forecast is determined by human analysts and cross-validated;
  • A Cash Flow Available for Debt Service (CFADS) forecast is made using a statistical model that takes the revenue and debts service forecasts a inputs
  • A Free Cash Flow to Equity Retention Rate (RR) forecast is made using a statistical model that take into account future debt service and the lifecycle of the company

Future dividends are derived as follows

Dividend_t = FCFE_t \times (1 - {RR}_t) = max(0, CFADS_t - DS_t) \times (1 - {RR}_t)

Each company's dividend forecast at time t is then used to compute a price using a discounted cash flow model taking two other inputs: a term-structure of interest rates and a risk premia.

Market  Rates Term Structure Data

Interest rate data for each available horizon are interpolated using a standard methodology (see Asset Pricing Methodology) to derive a term structure of risk-free rates on each relevant future valuation date.

Interest rate data: Datastream®

Risk Premia Data 

The mark-to-market risk premia applicable to each company to be priced, on each valuation date, is estimated by observing secondary market internal rate of return (IRR) and statistically estimating the effect of certain systematic risk factors e.g. size, leverage, profits, etc. as well as TICCS® sector and business model control variables. 

E(\tilde{R_{i}})-R_f=\lambda_{1} \beta_{i,1}+\dots+\lambda_{K}\beta_{i,K} + \omega_i

where \lambda_k is the price or premia of each K risk factor, \beta_{i,k} is the factor loading or exposure of company i to factor k, and  \omega_i is the measurement noise introduced when estimating E(\tilde{R_i}).

Once these risk premia have been estimated over time, each one is used to derive a mark-to-market risk premia for each individual company i.e. given its size, leverage, profits, TICCS® classification, etc. at the time of valuation.

E(\hat{R_{j}})-R_f=\sum_k \hat{\lambda_{k}} \beta_{j,k}

The prices of all infrastructure equity stakes obtained using this approach are then used to compute the asset-level performance and risk metrics

Index data and analytics are then computed using these results.

More details are available below and in the supporting documentation.

  • No labels