Frontline Analysts Blog

Training cross asset analysts


As we start expanding our service range to cover equity, derivatives and risk as well as credit research, we have needed to expand our training and development programs to dvelop the skills of our analysts. Within the next couple of weeks we will be launching equity research coverage of some financial and technology stocks, written by two of our credit analysts; we’ve also produced a Thematic Alert to clients on all the investment opportunities turned up by the recent upheaval in the European banking sector. So for the last few months, I’ve been learning a lot about how you train people to do cross asset research.
All of the staff we recruit to Frontline are either top-class MBAs from the Indian Institute of Management or equivalent schools, or quantitative PhDs who have been through our own finance boot camp. So I had the advantage of having good quality raw material to start with; there was no need to explain what a DCF model was or how to derive cash flows from an income statement and a balance sheet.

What I did learn is that when you’re thinking about securities in a cross asset context, everything starts from a good old fashioned review of accounts. People from a credit background tend to be strong on ratio analysis and footnote analysis, which is a great place to start from when you’re analysing an equity story. Where you need to guide them is to start thinking about the accounts as a description of the underlying business, as well as a record of financial performance. So you need to get them calculating multi-year sales and margin trends, debtor days and learning how to track capex and its marginal return. When you care about upside as well as risk, you just need to spend more time on modelling than a credit analyst, other than HY or distressed debt, is ever realistically going to be able to allocate. One also needs to learn the skill of recognising when a piece of analysis isn’t going to lead to an interesting investment conclusion and let it drop.

The next stage is all about learning to tell stories. This seems to be under-emphasised in modern business education, but it’s the basis of equity research in my view. The analysts who I’ve been doing cross-asset training with at Frontline are smart and creative people, but you need to build their confidence up a bit. People buy or sell stocks and equity derivatives because they’ve got a view about the future, and the only way you can have a confident view about the future is to have a story which makes sense of the recent past. So a lot of my training has just been about asking very open questions like “What kind of a company is this?” or “What is this management team trying to do?”. When you get an answer like “It’s a set of mediocre franchises, but they’re all cash generative and the management knows that what they need to do is nail down costs”
Then you know that you’re getting somewhere.

Finally, there’s all the nuts and bolts of research coverage – the things that people usually have to learn on the job. Things like making your model resemble the quarterly results presentation, so you can update it quickly on an earnings announcement day. Understanding the basis on which consensus numbers are collected – it was quite a battle to explain to our guys that although the “non-GAAP EPS” measure made a lot of adjustments we regarded as fundamentally unsound, they still had to forecast it in order to know whether the company was beating or missing expectations. We even had a few useful conversations about the correct measurement of beta.

But my overall takeaway from the process is that this is very much a learning-by-doing industry. There is, not to put too fine a point on it, not very much that you can learn about cross asset research by sitting in a classroom and taking a course. The only way you can pick it up is to initiate equity and/or credit coverage on a company. And the only way you can teach it is by sitting down, reviewing drafts and having phone calls until what you’ve got in front of you is a piece of research you’re willing to publish. The difference is that our analysts go through this process in a structured way, dealing with someone whose job is to train them, rather than being expected to pick it up by osmosis from someone who is trying to do live stock coverage himself.