EXECUTIVE SUMMARY CONTINUED 4. Analysts’ models are based on cash flow forecasts for the next 3-5 years. In this report, the core part of the research focuses on the models used by sell-side equity research analysts and credit rating agencies. Our analysis suggests that in both cases, analysts rely on past financial data and forecasts for the next 3 to 5 years. In rare cases for sectors with very stable cash flow profiles this forecast period can extend up to 7-11 years. After this period, the expected future cash flows of issuers are extrapolated. Therefore analysts only price the risks that impacted issuers in the past or are likely to impact them during the forecast period. 5. Long-term financial analysis faces methodological obstacles but also a lack of demand from investors. When interviewed on the drivers behind the short-term focus, analysts highlight the methodological obstacles, attributing the lack of forward-looking data reported by issuers, and justifying the focus on short term by the ability of most companies to adapt to any risk in the longterm (through innovation, divestment and acquisitions, etc.). However, a closer look also reveals that the demand for financial analysis is heavily driven by shortterm traders, and that even long-term investors actually trade their assets with relatively short horizons. A sister study developed in partnership with Mercer shows that long-term equity managers hold assets for 1.7 years on average. During the interviews, most analysts agreed that this lack of demand alone can explain the lack of longterm analysis. 6. Developing ‘alternative’ long-term analysis? We conclude that the methodological obstacles can be better addressed. In sectors with long tem assets like power, avenues include the use of physical asset level data to better assess the locked-in effects, the extension of the forecast period, and a more forward looking approach in the calculation of the risk premium. The climate-related risks are currently the main focus of attention: the Financial Stability Board established a task force to explore options, and the EC finances a research project (led by 2°ii) to develop an open source methodological framework. However, moving forward, the lack of demand from investors will remain a key obstacle. To address it, the report identifies both voluntary measures (e.g. long-term alternative ratings and valuation commissioned by a pool of investors or regulators), and public-policy actions (e.g. mandatory long-term risk analysis and disclosure). Both dimensions are currently discussed or/and experimented for climate-related risks. RESEARCH APPROACH The research is based on a mix of quantitative and qualitative analysis. Most figures are based on third party research, both academic and nonacademic as well as market data from Bloomberg, S&P, Thompson Reuters, etc.. Our own quantitative analysis focuses on the breakdown of equity NPV by time period, and the length of the forecast periods based on Morningstar DCF models and Bloomberg fixed-income data. We also quote the results of a study on equity portfolio turnover, based on Mercer proprietary data and Morningstar funds data. The qualitative analysis is based on a review of sell-side research papers, Credit Rating Agencies’ methodologies, as well as engagement with practitioners (see below, page 6 and p 70). FEEDBACK FROM PRACTITIONERS Based on a discussion paper, our team engaged with sell-side and buy-side equity research analysts as well as credit analysts via a survey, interviews, and workshops. The large majority of feedback confirmed our findings. The three main caveats are: • Some equity analysts blamed us for giving too much credit to DCF models, since in most cases analysts just use DCF to justify a price set based on peers’ estimates and market price. • A strong minority of analysts also questions our optimism regarding the ability to overcome methodological obstacles and uncertainty in general. • Finally, one CRA explained that it seeks to incorporate all risks into ratings, whether long-term or short term, with the most forward-looking view that visibility based on the availability of data into these risks permits. We however did not find enough evidence supporting this view to modify our conclusions. 6
PART I WHITE SWANS MAY LOOK BLACKINTHEDARK SECTION SPOTLIGHT • Equity analysts are very accurate when markets are calm but they tend to miss their price targets by more than 50% in volatile markets. • Credit ratings have historically been very good signals of default; however, ratings must trade-off accuracy and stability, and the trade-off point chosen by credit analysts may not adequately transmit risk signals most relevant to different types of investors. • Credit and equity analysts may be missing long-term, non-linear risks. • Long-term risks, in particular those with non-linear and non-cyclical risk profiles, are likely to get missed by financial analysis due to the short-term focus of current risk and valuation models. • In light of these long-term future risks, long-term investors are potentially exposed to mispriced, financially material threats. • The subprime crisis was a case in point. Disruptive trends such as the transition to a low carbon economy currently raise the attention of financial regulators and intermediaries themselves.