Analyst of the Month
February 29, 2024

David Alderman: Analyst of the Month

Meet Davld Alderman: Research Analyst at Franklin Templeton

Jon Ma
Co-Founder / CEO

Welcome to the 8th edition of the Analyst of the Month

This month we highlight David Alderman, Research Analyst at Franklin Templeton where he is responsible for conducting fundamental research and analysis on the Firm's digital asset strategies.

We're excited to share David's story as we've been fans of his research on time to profitability of chains and reducing the cost of trust.

Read on to learn more about his journey from investment banking with a focus on energy to studying financial economics in grad school to helping shape the digital assets investment strategy at Franklin Templeton!

P.S If you're at ETH Denver 2024, David is giving a talk on Friday, March 1st at 3:15pm and 3:30pm about L2s, AltDA, ETH Profitability: TradFi Goes Deep on Tokenomics and After the ETF: What Will It Take to Get Wall Street Onchain?

What is your story? What was your journey into investing and into crypto?
Since childhood, I've been intrigued by the world of global markets. Despite this interest, I went to study engineering in college, but of course I remained interested in markets alongside my studies. Eventually, I made the choice to pursue a career in finance and entered the banking industry, with a focus on the energy sector in Houston. Energy was a great industry to focus on because it tapped into my interest in global markets and very few industries are more global than oil. 

Just as I started my banking career in 2017, bitcoin (BTC) was going parabolic. I remember many people calling it a tulip mania at $3,000, but I was curious so I bought it though I had no idea what I was doing. I sold it once I was up 50%, but of course I watched it keep going up all the way to $20,000 making me think I was ridiculous for having sold it. 

I decided if I really wanted to buy bitcoin again, I needed to understand it and crypto markets generally. With my fascination in macroeconomics, I started to explore the concepts of central banking, commodities, fiat, gold, BTC, and how they all tie together. Subsequently in 2019, I decided I should pursue a career in macro investing and went to Columbia Business School to study Financial Economics. Still, I didn’t think that crypto could be a viable career path. 
In 2020, I started grad school which just so happened to coincide with the COVID-19 pandemic and BTC crash. As I followed the news I decided BTC was a good long term asymmetric investment, and as crypto activity in 2020 accelerated, I found myself curious about the rest of the crypto market. Before I knew it, I was deep down the rabbit hole of crypto in everything from DeFi (Decentralized Finance) to NFTs (Non-Fungible Tokens). Ultimately, I decided that rather than pursue macro investing, the best and most promising path forward for me was crypto. 

Presently, I work at Franklin Templeton Digital Assets as a research analyst on the Digital Asset Investment Strategies team. I find myself in a position where my personal passion projects are intertwined with my professional pursuits, perhaps more than I could have anticipated.
You started your career in IBD focused on the energy sector. How did working with energy businesses influence your mental models on valuing and investing in L1/L2s? 
Starting my career in the energy sector continues to have a large impact on the lens through which I see crypto. Just like traditional commodity industries, the energy sector follows cyclical patterns. Similarly, the crypto market has historically exhibited cyclical patterns in 4 year periods. Though these industries are quite different, I do find similarities in cyclical patterns between them. I should note that the crypto market is in the early stages compared to established markets, and it’s difficult to gauge if these noted cyclical patterns will endure over longer time periods.

While my time in energy banking only spanned a three-year period, I experienced nearly a complete cycle over that timeframe where the market went through a recovery phrase, peaked, and ended in a downward trajectory as Covid began. Energy stocks followed similar patterns. In crypto, it seems very similar. The L1 tokens reflect all the boom/bust activity in crypto. The applications built on top of them follow suit, just like energy companies. The price of oil goes up, incentivizing more drilling, global events push prices back down, and the market ends up in a global glut of oil. In crypto, an increase in prices results in a lagging positive effect in on-chain activity. Price leads chain activity, just as the price of oil leads more drilling activity.  

I believe the best analogy for crypto today is found in the early days of the oil market, where massive boom bust cycles characterized the landscape. The book, “The Prize” by Daniel Yergin, has one of the best historical descriptions of that time. Just as the oil industry was birthed and boom-bust cycles ensued, we are seeing similar movements in crypto since Bitcoin launched.
What framework do you use for valuing L1/L2s?
There always seems to be this big debate on how to characterize L1 and L2 tokens. They have both equity and commodity characteristics. An asset like Ethereum (ETH) is used for staking and governance but is also used to pay for transaction fees. We could debate one way or the other all day long, but frankly I don’t think it matters much which way to look at these assets.

If we take the traditional discounted cash flow (DCF) valuation method or build a supply / demand model, we find very similar insights associated with relative value across a basket of L1 and L2 tokens. I find the absolute valuation to be difficult; however, the exercise is very informative and revealing when you compare different networks.

Underlying the value of these assets has to do with the net demand of the asset, relative to supply. If we model growth in demand (or fees) and factor in the expected new supply inflation, we can better understand the expected imbalances in the future. It’s easy to understand this in extreme cases. If inflation is 1,000% and demand stays flat, I might expect price will go down over a long enough time horizon.

I see this as an approach to assess relative value of crypto assets given expectations of future demand and the known supply headwinds. And if anything, this helps determine the growth assumptions one needs to believe in to justify an investment.
You and Christopher highlight Years-to-Profitability for L1s in your Coindesk piece. What implications do you think this has for how L1 should think about designing their tokenomics?
Similar to how doing fundamental valuation helps determine relative value, Years-to-Profitability (YTP) is a way to compare L1 tokenomics and give insight into relative value. If we can assume a constant fee growth percentage across all chains, we can see how far away each chain is from reaching profitability. Or from a supply-demand perspective, how long until equilibrium between demand and supply is reached.

This analysis is useful to compare different blockchains because each chain has unique tokenomic characteristics. Some have fixed supply. Some inflationary. And factors such as investor unlocks and foundation holdings should be considered.

L1s may find this analysis especially useful when they are in the early stages of growth and ecosystem development. It may be a good gauge to check that they are on track to similar chains that are further in their development.
What applications do you think will drive long-term recurring value to networks?
Achieving long-term recurring value necessitates real-world use cases that are not solely driven by speculation, a landscape that has yet to materialize substantially in crypto, except for stablecoins. However, drawing context from previous cycles and narratives, excess returns hinge on the introduction of a new primitive that sparks the imagination of crypto users, akin to the dynamics observed with ICOs in 2017, DeFi in the summer of 2020, and NFTs in 2021.

Speculation is best found where the imagination is allowed to run free and where I see potential of this is in Decentralized Physical Infrastructure Networks (DePIN), Payments, and Social. Unlike prior categories that have taken off (DeFi, NFTs), these categories have a stronger relationship with the real world. And as blockchains are improving capabilities, the ability for the mass adoption of these types of real world use cases is more likely.

From my perspective, I see applications in these areas with the highest potential to drive network adoption because they are new primitives, primed for speculation, and are closer to real world use cases than we have currently.
In your research piece “Reducing the cost of trust”, you highlight Tokenized Real-World Assets and DePin as promising projects that exhibit high potential. What are some other projects and categories of apps that you think have long term value?
Payments represent a classic example where the primary use case involves diminishing the role of intermediaries of peer-to-peer transaction. This area seems to be one of the most fitting categories to leverage the strengths of crypto. The disruption it brings to the existing payment infrastructure is evident, and it’s noteworthy that major payment companies are actively engaged in the crypto space. Whether through beta testing or stablecoins, these industry leaders recognize that decentralized blockchains are the future of their sector, and they are exploring ways to best use this technology in their current businesses.
What are some theses in crypto that you’re currently researching or excited about? 
There are three different theses I am currently exploring and excited about. Those include (i) value accrual in the EVM / modular stack, (ii) Ordinals & BTC L2s, and (iii) DePIN.

Value accrual and distribution in a modular stack.
The stack comprises four distinct elements: execution, consensus, data availability, and settlement. Presently, the significance of network effects is paramount in the process of value accrual. Much like the construction of moats in Web2, network effects in Web3 hold substantial importance. The central question to address is how each component of the stack contributes to the development of network effects, if they do so at all. Additionally, the relevance of Miner Extractable Value (MEV) must be considered, with a potential limitation to capturing it solely at the execution layer.

Ordinals & Layer 2 solutions
on Bitcoin shouldn’t be ignored. These are vital to solving Bitcoin’s economic security problem and increasing BTC’s utility as a Store of Value (SoV). I see a lot of opportunity in this area if Bitcoin can become a more integrated and connected asset.

presents a tangible use case that, as previously mentioned, has the potential to ignite the next wave of adoption in the crypto space. It exemplifies the influence of crypto on a global scale, showcasing its power and reaching diverse corners of the world. The project holds the capacity to disrupt traditional business models, aligning seamlessly with the inherent use case of crypto by diminishing the reliance on intermediaries.
How does the rapid emergence and fading of narratives impact your approach to crypto assets?
A narrative dies as fast as it spawns. 
How have you been able to use Artemis in your fundamental research? 
Artemis has proven to be a valuable tool for my fundamental research. I find the Excel plug-in very useful because it allows me to pull in multiple data sources into Excel without having to go to each of these sources’ websites for the data. Generally, it’s one of the tools I use day-to-day, and I am impressed by the team and constant improvement of the platform. 

You can find or reach out to David on Twitter or LinkedIn

Franklin Templeton Disclosures

There are also risks in investing. The initial potential of any asset class may not carry over to any specific company or the entire asset class chosen for investment, over any time period. Any of the stated assumptions may or may not come to fruition, and any companies referenced may or may not have future successes. Investors should be prepared for potential losses as well as the possibility of investment gains. Ideas, products, companies, themes or entire asset classes with positive attributes are not indicative of future results. Discussions should not be regarded as any type of trading recommendation, or as a signal about any past, current or future trading activity in any fund or strategy, by Franklin Templeton and its affiliates.


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