Our ideas typically comprise companies exposed to big-picture secular themes around which we have built conviction and/or companies with business models that we are familiar with from prior analysis. Some of these include the transition to the public cloud, the expanding need for and use of data, the continued transition of commerce/advertising online, the increasing reliance on bandwidth and internet infrastructure, the diminishing use of physical cash in society, rising disposable income and consumption in China, and increasing access to global travel. We prioritise companies where we have preliminary indications of business quality and where we think our existing work might help maximise our return-on-effort. It is a bonus if we suspect the valuation will be attractive, but this is not imperative — we are happy doing our work and then being patient for future valuation opportunities.

Like most primary research processes, we seek to understand the investment landscape and competitive position. We speak with various elements of the value-chain but are also careful not to draw strong conclusions from small sample sets. We prioritise the research process around the areas that are most impactful and in which we have lower conviction. However, all of this is simply “table stakes”.

What makes our process unique to Kalakau Avenue is the synthesis of this research into our business quality framework. We score all companies across this common framework to arrive at an overall business quality score that determines its cost of capital. This is not to make the process quantitative but rather to promote consistency of decision-making across the portfolio and over time.

In addition to our business quality framework, we attempt to understand why the business needs to exist and the few things that really matter. We narrow down the key risks and unknowns, including the regulatory environment, and try to understand their likelihood and impact.

All our research, investment frameworks, investment decisions, meeting notes, team priorities, and contacts etc are logged in our custom-built research management system in real time for easy access and recall. Our research management system is a key facilitator of shared learnings among the team and represents a key piece of our infrastructure.

We see valuation first and foremost as a risk mitigant rather than a return driver. That is, we are not trying to capture the reversion of mispricing in the market. Our returns mostly come from the long-term compounding of intrinsic value. We use a variety of methods to value our portfolio companies, all aimed at answering one question, “does a margin-of-safety exist?”.

In general, we model our companies to the point they are likely to stabilise (typically 5 years but this could be longer) and assess the IRR over a range of scenarios, always thinking probabilistically. We strive to build solid forecasts within each scenario and to understand the broad probability of each scenario. However, we also try hard to avoid false precision; valuation as a tool is a sledgehammer not a scalpel. We have more confidence in our views of the business quality — that is, the characteristics we see today that increase the odds of success no matter what the future holds.

We assign a valuation / risk-reward score by assessing the range of returns versus the cost of capital. Again, this is not to make the process quantitative but to help promote consistency and tracking of decision-making. If a company passes our quality filter but is too expensive or not more attractive, risk-adjusted, than the current portfolio then it simply goes on our investable list.

Positions are sized based on conviction and risk-reward. Conviction is developed through our research and the risk-reward is determined with our valuation score, by comparing the range of potential returns versus the cost of capital. Further, sizing can never be decided in isolation from the rest of the portfolio, there is always a relative trade-off. We maintain a sizing framework that outlines suggested sizing ranges based on our quality and valuation scores. As before, the purpose of this framework is not to make the process quantitative and in any case, the framework is only a general guide. Rather, it’s purpose is to eliminate bias and inconsistency in our decision-making across the portfolio and over time.

The portfolio is adjusted only when there are very material changes in the risk-reward profiles. Positions are sold entirely if the investment is unlikely to compensate for the risks even over the long-term, if the quality thesis deteriorates or is proven wrong, or if the portfolio is fully invested and a competing idea takes precedence.

Once we find the assets we want to own, we avoid the need to feel productive through action. We are unlikely to add value from excessively trading around our positions. Rather, our focus is on assessing whether our investments remain good economic machines by regularly assessing the business performance (not the stock price performance) and any potential disruptive threats. Valuation is only a concern when the margin-of-safety is no longer adequate. We want to allow our investments time to compound over the long-term, maximising our return on effort.

Our primary risk-mitigant is the quality of the businesses we own. Conviction in the quality is built through our research process and business quality framework. This includes analysing and understanding the known unknowns. The business resilience of high-quality companies is what helps mitigate the unknown unknowns. Our second risk-mitigant is to own businesses with an appropriate margin-of-safety. Our final risk-mitigant is to maintain humility in concentration. Concentration is required in our strategy, but some diversification is also useful.

As portfolio manager, I am the final decision-maker for our portfolio and investable list. All decisions are recorded in our research management system to ensure we capture our current mindset and thinking. This is critical if we are to analyse our decisions in the future and learn from our mistakes. Equally important is what we consider to be decisions. The action of buying or selling a stock might intuitively equate to a decision. However, we must also consider our more implicit decisions and make them explicit. For example, material changes in position size due to market movements are decisions equally as critical to the action of buying or selling.