For this Investment Insight, we took a slightly different approach. After listening to two recent investor interviews with Nick Griffin of Munro Partners and Seth Klarman of Baupost, we used the transcripts to draft a commentary on growth and value investing.
The following article outlines two thoughtful but contrasting investment disciplines and asks what each can teach us in an AI-led market.
Two disciplines, one objective
Investors often divide the market into opposing camps. Growth investors, such as Nick Griffin, are seen as optimists, willing to pay for future earnings. Value investors like Seth Klarman, are seen as sceptics, concerned first with price, downside and preservation of capital. The contrast between Griffin and Klarman shows that this division is useful, but incomplete. Both are trying to find mispriced opportunity. Both are bottom-up investors. Both understand that artificial intelligence may be a defining force in markets for years to come.
Where they differ is in temperament, starting point and the level of uncertainty they are prepared to accept.
Nick Griffin’s growth case
Griffin’s case for growth begins with a simple proposition: earnings growth drives share prices. If a company can make materially more money each year, its share price should, over time, follow. Munro’s task is therefore to identify structural changes that can create sustained earnings growth and then find the small number of companies capable of winning from those changes. This is an important distinction. It is not enough to identify a large theme. Investors must also own the right company within that theme.
History is full of examples. Search was a major opportunity, but Google was the winner rather than Yahoo. E-commerce was a profound shift, but Amazon became the defining company rather than eBay. Smartphones created enormous value, but Apple endured while BlackBerry faded. Griffin’s point is that equity-market returns are usually driven by a small number of exceptional businesses. The investor’s job is to find the structural tailwind, then identify the company with the quality, management, customer loyalty and earnings durability to compound through it.
This explains Munro’s focus on businesses growing revenues at least twice as fast as GDP, with earnings growing faster than sales, and with that growth visible over a three-to-five-year horizon. It also explains the emphasis on qualitative characteristics.
A great growth company is not just a company in the right sector. It is a company customers love, management understands, and competitors struggle to displace.
In Griffin’s framework, the aim is to own the few winners early enough, and for long enough, for compounding to matter.
AI as an infrastructure cycle
Artificial intelligence is the current expression of that framework. Griffin sees the AI capital-expenditure cycle as still young. The spending is no longer confined to semiconductor designers or cloud platforms. It is spreading through power infrastructure, electrical equipment, commodities, engineering, construction and data-centre supply chains. His phrase is to follow the capex dollars, because those dollars become revenue for the companies enabling the build-out. This is growth investing with an industrial lens. AI is not only a software story; it is also an infrastructure cycle.
The attraction of this approach is not simply the pursuit of growth, but the potential to access growth through a differentiated portfolio construction process. That distinction is reflected in the fund’s return profile.
Since its inception in July 2018, Munro’s Flagship Global Equity Fund, has delivered similar returns to the MSCI World Gross Index. It is not easy to outperform a market which has such a high concentration in a few super high growth businesses. The fund’s return stream has a correlation of 0.69 and a beta of 0.75, which offers some diversification benefits if you invested in both the MSCI World and Munro. In our view, Munro is a high-quality manager with better downside risk metrics than the market.
Seth Klarman’s value case
Klarman approaches the same environment from a very different angle. Baupost was built to produce good returns with limited downside, not to capture every market advance. His process begins with capital preservation: meticulous fundamental research, cash when opportunities are scarce, no portfolio leverage, senior securities where appropriate, structured investments and macro hedges.
In a market excited by AI, that caution can appear unfashionable. Yet it is precisely when markets are excited, that the value investor’s discipline becomes most useful.
Klarman does not dismiss AI. On the contrary, he accepts that it could be game-changing. His concern is the market’s confidence in pricing it. Investors are being asked to pay high multiples for outcomes that are distant, uncertain, and potentially dependent on continuous investment. Will today’s winners remain the winners? Will the economics accrue to model builders, chip companies, cloud platforms, application businesses, or users? Will AI be inflationary in the short term because of the build-out, but deflationary over time because of productivity? These are not easy questions to answer.
For Baupost, uncertainty should normally require a larger margin of safety. In parts of today’s market, the opposite appears to be happening, greater uncertainty is being met with higher valuations. That is why Klarman sees bubble-like characteristics, even while acknowledging that the technology itself may prove extremely important. His value investing is not a mechanical search for the lowest multiple stocks. A cheap business can still be a poor investment if it is melting away. Equally, a growing company can be attractive if the price does not require heroic assumptions.
Two ways to handle uncertainty
The most useful contrast is therefore not growth versus value, but two different ways of dealing with the unknown. Griffin accepts that many investments will be wrong and uses a sell discipline to review mistakes early. Falling share prices force the team to ask what they have missed, and repeated weakness requires repeated review. The aim is to keep losses small while allowing genuine winners to become large. Klarman places more of the discipline at the point of purchase. He wants the price, structure and balance sheet to absorb disappointment before it arrives.
Their opportunity sets naturally differ. Griffin is leaning into the AI build-out because he believes it will shape the composition of future equity returns. Klarman is spending time on AI-agnostic companies, perceived AI losers, distressed credit and commercial real estate, where investor neglect or forced selling may create better risk-adjusted opportunities. Griffin wants to own the companies carried forward by structural change. Klarman wants to buy assets mispriced because investors have become too focused on that change.
What investors can take from both
For investors, the conclusion is not that one style should replace the other.
Growth investing explains how wealth is created by owning exceptional companies through long structural cycles. Value investing explains how wealth is preserved by refusing to overpay for futures that cannot be known.
That distinction also informs how we think about manager selection. At Saxe Coburg, we don’t approach manager selection based on their style, be it “growth” or “value”, we focus on their results. A growth strategy implemented with skill, with an eye on downside protection or a value strategy which factors growth into the value proposition are equally interesting, if implemented well.
Ultimately, our role is not to dictate where managers invest, but to partner with those whose process demonstrates both conviction and discipline. Whether they lean towards growth, value, or a combination of the two, what matters most is a repeatable framework for allocating capital in an uncertain world.