We are developing a new fundamental investment support framework to make a shortlist of in-depth research candidates. But why equity research? Because it is quite beneficial for professional practitioners of fundamental investing. This framework is exactly what I had wanted to have desperately.
Backdrop
Experience helps an investment manager raise the success rate for a case within the manager’s field of expertise. The most challenging part is the early stage of stock selection. Experience helps but less than the mid to final stage of the stock selection process. Another issue is that there is a contextual gap between the early-stage process and the last point of decision. It is not unusual to apply price multiples or other price valuation measures to narrow the list down, but what if the actual investment judgment does not use such criteria. The process is then inconsistent from start to end.
I had many hands-on experiences associated with the lack of real coherency of the process. In fact, this is not just me. Many large mutual fund companies like T Rowe Price, Capital, and Fidelity all use more or less use a similar structure of front-end research process.
In the world of active equity investing, at large fund management firms, there is a wall in the organizational dividing between a fundamental equity team and a quantitative equity team. They tend to compete with each other and get compared and contrasted internally, and so genuinely amicable collaboration looks like a dream.
That said, the front-end shortlisting process of fundamental equity cannot be done without in-depth quantitative research and tools. Also a fund management firms do not allow portfolio managers to do R&D of the investment process. They are responsible for implementing the process and delivering return.
However, you cannot find a better source of significant insights other than the incumbent professional portfolio managers. Those insights are real differentiating knowledge, which helps to give many unique ideas of trial & error as to how to train and develop machine learning and neural network.
However, from the fundamental manager’s standpoint, they are usually not familiar with advanced data process technology. While they invest in companies that are growing business of data analytics, they cannot spend time to learn software skills and understand the data structure of programs for the sake of fundamental equity investing. They also have a structural and disruptive conflict because transferring know-how to shortlisting analysis software may significantly reduce the alpha that was supposed to get delivered by unique professional skills. It may be a suicidal project for them, as it will lead to the creation of new exotic beta that can be generated systematically via rule-based ETF investing. How can it be avoided? The short answer is that both the team and the organization have to originate from a human pro and machine hybrid philosophy and process from the start.
Actual Fundamental Research Process
First, the mid-final stage of fundamental analysis takes time.
It requires a mix of detailed financial analysis and company/industry research to find and set the critical investment thesis with a conviction for security.
Second, it is also crucial for an investment team to have the right shortlist as it determines research & investment process productivity.
If analysts are given a list of research candidates that are not well organized and under-defined, the analyst is sure to face many challenges to avoid a low approval rate of research and recommendation.
Third, we are now living in the new normal of agility, change, and innovations to improve our work productivity, including investment management. I think it should apply even to a successful investment manager responsible not only for a routine but also for moving one and a half steps forward by developing new ideas for process and challenging it uniquely. Primarily if the manager invests in such companies, the company he works for has to head toward the same direction to prove the organization is consistent from top to bottom.
Rule-based investing, including ETFs and passive investments, has disrupted one end of the active investing business, but another end is also interrupted by private and venture investing. I think it is worth considering if real R&D is too small for active public equity investing to remain competitive, as R&D is defined as the expense for investment research of the portfolio, which is, in fact, COGS of service.