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Luca Migliorati

on 2 August 2015

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Transcript of PRESENTATION

A.C. Milan Initial Public Offering

Widely used multiples do not work
For each one of the competitors we gathered data from Bloomberg, Orbis and Factiva.
Considering a time span of seven years, from 2006 to 2012, we therefore computed their specific annual multiple.
Our Multiple
Main issues
Our approach
SALES x (1+g)
Our main goal was to get to a forward ratio, so we took Sales from 2006 to 2012 without estimating g because we used their actual growth rate

Sales of 2012 were multiplied for the (1+CAGR), where the CAGR was calculated on the previous 6 years of data
Fading period & specific weights
Valuing firms with negative earnings
Earnings growth rate is difficult to estimate

Financial structure

Is it a sustainable business model?
Relative valuation

Range estimation
Our results
Computed as a percentage of liabilities on the total sum of liabilities and equity

We used this in order to find the average financial structure of the industry

Created to forget past data giving more importance to recent values
λ calibrated to 0.9
The result is an average that fades to the 81% in 2011, 72.9% in 2010..
Weights were fixed subjectively trying to take into account particular characteristics of the comparables


EV/Sales could provide a consistent result, BUT:

Sales are too general as an indicator of profitability

No financial structure taken into account

No cost & amortization related to industry specific accounts
This is an example of how we applied the simulation on each single specific part of sales that we tried to explicitly forecast over the future four years
Estimating sales trend
We supposed the sales to moving according to a Log Random Walk under a non-standardized Gaussian distribution.

The mean is obtained from the CAGR
The implicit assumption is that the company will need to approach a new financial structure close to that of the industry average
We decided to use weighted levered betas of comparables as the current financial structure of AC Milan doesn't allow an IPO
Bier Gabriele
Caturano Cristiana
Galateo Nicholas
Migliorati Luca
Monteporzi Federico
Appendix I
EV/Sales results
Appendix II
Choosing comparables criteria & specific weights
Borussia Dortmund
AIK Fotbol
Absolute valuation

Punctual estimation
Taking into account our initial assumptions and the firm's 2012 sustainability report, we aggregated the single Montecarlo estimated sales trying to recreate the trend of the past seven years
Forecast moving from decomposed sales is more precise and detailed

More Montecarlo were launched in order to take into consideration the trend of each specific account

Appendix III
Appendix V
Sales 2010 - 2012
Appendix VI
Weighted Average Cost of Capital
Appendix IV
Montecarlo Inputs (Variance)
Appendix VII
Capex analysis and estimate
Weights were fixed subjectively trying to take into account particular characteristics of the comparables that has also been used for the picking up; for example, importance of the national championship, participation to international competitions, core business and financial structure

In order to benefit from diversification, we also included a comparable that is not directly linked to football, but has a similar business model and is also included by the main data providers in the leisure and entertainment list: Disney.
Appendix VIII
Full transcript