Rationally, clients know you can’t see into the future. And I’m sure no-one wishes that wasn’t the case more than you. But as you don’t have a crystal ball or accurate set of tarot cards, the reality is that when clients ask you what will happen—which can be anything from a broad ambit of corporate finance topics—you have to give some kind of answer.
Every time a client asks you a question, your answer places your reputation, and any established trust on the line. So when asked about future stock price performance, the outcome of a merger, or other forward-looking activity, how can you provide an answer that is helpful to your client and doesn’t risk your role as a trusted advisor?
Whatever you do, don’t pull an answer out of thin air and hope your client will move on to the next topic or forget they ever asked you. A guess, even if based on years of experience, is still a guess. Any response you give is a page in the book of relationship history between you and your client. And if your client persists on the topic and asks follow-up questions or requests supporting materials that you can’t produce, well, it could be a rather short book.
Irrespective of confidence or experience, there is a limit to a banker’s knowledge. If a client's question requires more than you can reasonably say, the only thing to do is admit you can’t answer with accuracy, but you can offer an informed perspective by performing what a client of mine refers to as a “rearview mirror analysis”. You probably know it as backtesting or event studies.
Think back to when you were learning to drive. While you (hopefully) drove the car forward, you were also taught to check the rearview mirror to see what was happening behind you. All of your miles of accident-free driving are in part due to mastering the art of driving forward with quick glances in the rearview mirror to see what you left behind.
Backtesting is your rearview mirror and an unsung and underutilized hero in investment banking. The buy-side has long understood the appeal of this analysis and frequently puts its money where its mouth is based on the results.
How can bankers use backtesting? Say you are asked, “What’s likely to happen to my share price if I announce a share repurchase?” A quick (and common) response would be, “It will go up”—an unsatisfactory answer to all but the most forgiving of clients. But looking in the rearview mirror would produce something like this sample analysis:
In conducting an analysis of historical share repurchase announcements, you have a wealth of information available for clients. You can share the average announcement reaction, the number of announcements, the percentage of announcements resulting in negative share price movements and so forth.
"Ignoring backtesting is like driving around without your rearview mirror; it’s an unnecessary danger and leads to nothing but trouble."
History doesn’t repeat itself, but it often rhymes. The buy-side know this, and asset managers regularly risk their careers on the outcome of a backtesting analysis. I think it would be a positive trend if more bankers also added this type of historical analysis to their repertoire, expanding the usual approach of including case studies by providing small, anecdotal chunks of information.
Ignoring backtesting is like driving around without your rearview mirror; it’s an unnecessary danger and leads to nothing but trouble. The benefits of backtesting are pretty clear, and pitchbooks could benefit immensely from their inclusion. Answers about future events would no longer be a best guess and topic to quickly abandon, but something to revisit at length with a prepared, insightful analysis.
So why are so many investment bankers driving around without looking behind them?
Technology. Or more accurately, the technology skills of the buy-side, who are more likely to be able to code than investment bankers.
The role of computers on the buy-side has grown substantially, so too have the skills needed to succeed. It's for this reason that the buy-side can corral large sets of data, manipulate them, and then examine the robustness of a trading strategy, becoming equal parts data scientist, computer engineer, and financial analyst. However, the skills required to be a great investment banker and to perform a backtesting analysis are different. Goldman Sachs has been building out its Strats team with abilities such as writing code in its crosshairs, and this is an example of something the rest of the industry will emulate (if not already). The ability to program a backtesting analysis is just one example of how investment banking needs to incorporate and adopt a systematic approach to evolving the competencies of the industry, leveraging technology and data analysis to provide better client advice.
In my view, it’s something that should be addressed sooner rather than later. Clients expect a trusted advisor to do more than guess. With the amount of data available, it’s expected that answers should be driven by analytical insight and not by a knee-jerk response.
Have you used backtesting to answer a client question? What difficulties did you encounter? Let me know at firstname.lastname@example.org.
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