Excess Returns

Biotech is one of the few areas in investing where specialized knowledge may still generate persistent alpha. In this episode of Excess Returns, D.A. Wallach, venture capitalist and co-founder of Time BioVentures, joins us to explain how biotech investing works, why development-stage drug companies behave like portfolios of options, and why specialist investors play such a large role in this market. We also explore the cycles that have driven biotech performance, the impact of interest rates and capital flows, and how AI and global competition may reshape the industry in the years ahead.
D.A. Wallach – Twitter
https://x.com/DAWallach
Topics covered include
• Why biotech may be one of the last areas where specialist investors can generate persistent alpha
• The “bag of options” framework for valuing development-stage biotech companies
• How probabilities of drug success and clinical base rates drive biotech valuations
• Why rising interest rates hit biotech stocks harder than many other sectors
• How capital flows and investor narratives create boom-and-bust cycles in biotech
• What happened to biotech during the pandemic surge and the post-COVID downturn
• Why AI and tech narratives compete with biotech for investor attention
• The role of specialist biotech hedge funds in the public markets
• How large pharmaceutical companies drive returns through biotech acquisitions
• Differences between biotech venture capital and traditional tech venture investing
• How venture investors evaluate drug development programs and scientific evidence
• Portfolio construction and diversification when investing in highly uncertain biotech companies
• The emerging role of China in clinical trials and global drug development
• Whether AI can improve drug discovery, clinical trials, and pharmaceutical R&D productivity
• Why investors should avoid rigid value vs growth ideologies and stay adaptable
Timestamps
00:00 Why biotech investing requires specialized knowledge
01:40 Is biotech one of the last places for persistent active alpha?
02:45 The “bag of options” model for valuing biotech companies
05:00 Drug development phases and probabilities of success
07:00 Using base rates to estimate clinical trial success
09:20 Estimating total addressable markets for new drugs
11:10 Why rising interest rates hurt biotech valuations
13:00 Capital flows and why biotech underperformed in recent years
15:30 The biotech boom and bust around the COVID pandemic
18:00 How AI and tech compete with biotech for investor capital
22:20 The role of specialist biotech hedge funds
24:00 How pharmaceutical acquisitions drive biotech returns
25:20 How biotech venture capital differs from tech VC
30:50 Why biotech investors must evaluate complex scientific data
34:20 Where AI may improve drug discovery and R&D productivity
42:00 Portfolio construction and diversification in biotech venture investing
44:30 Volatility, valuation marks, and private market pricing
48:00 Managing risk across different drug technologies and disease areas
49:30 Why China is becoming important for clinical trials
53:00 Why biotech investing must be viewed as a global industry
54:30 The importance of flexibility between value and growth investing
58:50 Will investing become more systematic and quantitative over time

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In this episode, we break down the most important insights from the week on Excess Returns,, with insights from Vitaliy Katsenelson, Jim Paulsen, and Joseph Shaposhnik. Markets today are being shaped by powerful crosscurrents including AI disruption, defense spending, macro policy shifts, and historically high valuations. In this episode, we highlight the biggest ideas from our conversations and explore what they mean for investors trying to navigate an uncertain world. Topics include the importance of humility in investing, the potential disruption of software by AI, the growing divergence within the economy, and why long-term structural trends like defense spending may create new opportunities.
Topics Covered
• Why humility may be the most important trait for investors in a rapidly changing world
• How uncertainty around AI, geopolitics, and macro policy is widening the range of possible market outcomes
• Why some investors are reducing exposure to software businesses amid AI disruption
• The importance of management teams that can adapt and evolve in periods of technological change
• Jim Paulsen’s framework for understanding the “new era” economy versus the rest of the economy
• Why a small portion of the economy may now be driving overall GDP growth
• The idea that successful investing may be about being “least wrong” rather than perfectly right
• How long-term structural trends like defense spending could create a multi-year investment tailwind
• Why experienced investors focus on analyzing businesses rather than reacting to headlines
• The potential deflationary impact of AI and how lower prices could shift spending across the economy
• Why high market valuations may act as a headwind for future returns
• The importance of deep research and preparation when unexpected events hit markets
• Jim Paulsen’s concept of “policy juice” and how fiscal and monetary policy drive bull markets
• Whether a new wave of policy support could broaden the current market rally beyond mega-cap tech
Timestamps
00:00 Introduction
02:00 Why humility matters more than ever in investing
08:50 AI disruption and the future of software businesses
18:07 The growing gap between the “new era” economy and the rest of the economy
25:00 Surviving first and being the least wrong as an investor
31:43 The potential defense spending supercycle
37:44 AI’s deflationary impact and how innovation reshapes economies
44:42 Why valuations act as a long-term headwind for stocks
50:56 How investors should respond to geopolitical events
56:49 Jim Paulsen on policy juice and the future of the bull market

On this episode of Excess Returns, Matt Zeigler and Bogumil Baranowski speak with Rainwater Equity ETF portfolio manager Joseph Shaposhnik about how long-term investors should think about markets in an era defined by geopolitical shocks, AI disruption, and unprecedented capital investment cycles. The conversation explores how disciplined investors can stay focused on durable businesses and long-term free cash flow rather than reacting to short-term headlines. Joseph explains how his team evaluates companies during major events, why the AI boom may create both massive disruption and opportunity, and where he believes the most attractive investment opportunities exist today.
Topics covered in this episode
• Why most macro headlines and geopolitical events rarely have lasting impacts on great businesses
• How long-term investors should analyze conflicts and market shocks without overreacting
• The defense spending supercycle and why aerospace and defense may benefit from rising geopolitical tensions
• How Joseph evaluates the AI investment cycle across semiconductors, software, and hyperscalers
• Why semiconductor companies may offer a lower-risk way to benefit from AI growth
• The risks created by massive AI infrastructure CapEx and concentration around specific AI models
• Why some software companies may face significant disruption from AI tools and LLMs
• How AI could reshape business models that rely on packaging public or commoditized data
• The potential rotation from the Magnificent Seven to the other 493 companies in the S&P 500
• Why capital intensity may change the long-term attractiveness of some technology companies
• The role of management quality and capital allocation in navigating technological disruption
• Fragile vs anti-fragile business models in an AI-driven economy
• Where AI may create unexpected winners across industrial and traditional industries
• Why long-term investors should still prioritize durable cash flow compounding businesses
Timestamps
00:00 Introduction and why most headlines have limited long-term impact on businesses
02:00 How experienced investors think about geopolitical shocks and market headlines
04:00 Defense spending tailwinds and the aerospace and defense supercycle
06:45 How investors should react when major market news breaks
11:10 How Joseph evaluates the AI boom and which companies benefit most
14:15 The case for opportunities outside the Magnificent Seven
17:15 How rising AI CapEx is changing the economics of major tech companies
21:25 Why hyperscalers face increasing concentration risk
23:00 Why semiconductor suppliers may be the best positioned AI investments
27:15 Why Joseph reduced exposure to software companies
33:00 The importance of learning organizations and adaptive management teams
37:00 AI, labor markets, and whether high-income jobs face disruption
41:00 Fragile vs anti-fragile companies in the age of AI
46:00 Where AI could create unexpected business winners
52:00 How great management teams adapt during technological disruption
57:00 How AI may accelerate entrepreneurship and innovation
59:00 Why investors should remain focused on sustainable cash flow
01:02:00 What the next generation of long-term compounders may look like

In this episode of Excess Returns, Matt Zeigler and Bogumil Baranowski speak with Vitaliy Katsenelson, CEO of Investment Management Associates and author of Soul in the Game. The conversation explores how value investing is evolving in a world shaped by artificial intelligence, rapidly changing economic dynamics, and historically high market valuations. Vitaliy discusses why humility and diversification are increasingly important for investors today, how to balance quality and valuation when selecting stocks, and what he has learned about selling decisions, portfolio construction, and long-term investing discipline. The discussion also moves beyond markets into deeper ideas about passion, creativity, and why investing, like art, is ultimately a creative pursuit driven by curiosity and lifelong learning.
Topics covered in this episode
Why high stock market valuations may create a headwind for future returns

The math behind long-term stock market returns and the role of earnings growth versus valuation changes

Whether the dominance of mega-cap technology companies represents a structural shift in markets

Why AI investment could lead to both massive innovation and large amounts of wasted capital

The importance of humility in investing during periods of rapid technological and economic change

Why Vitaliy increased the number of stocks in his portfolio due to greater uncertainty

How investors can think about what will not change in a rapidly evolving world

The evolution from statistical value investing to focusing on business quality and management

Why cheap stocks are often expensive and how narrative bias can trap value investors

The importance of evaluating management integrity and avoiding companies with questionable leadership

How Vitaliy thinks about selling decisions and recognizing when an investment thesis is broken

Why many investors make their biggest mistakes by selling winners too early

The concept of being a value buyer but a growth holder when fundamentals improve

Why updating valuation models as businesses improve is critical to capturing long-term upside

Lessons learned from great investors and the importance of surrounding yourself with thoughtful peers

The idea of building a personal operating system for investing and life

Passion, patience, and process as the three pillars of long-term investment success

Why investing is fundamentally a creative pursuit similar to art and music

The deeper motivations behind investing and why for many great investors it is not ultimately about money

Timestamps
0:00 Vitaliy on humility and why the range of outcomes in investing is expanding
2:00 The math behind long-term stock market returns
4:00 Why high valuations can become a headwind for future returns
6:00 Big tech growth and whether large companies now have structural advantages
8:00 AI investment and the risk of massive capital misallocation
10:30 Learning AI and why investors must adapt to rapid technological change
14:00 Why humility leads to diversification and larger portfolios
20:00 The evolution from cheap stocks to quality investing
25:30 Selling discipline and recognizing when a thesis is broken
34:30 Letting winners run and avoiding the mistake of selling too early
42:00 Learning from other great investors and building your own framework
44:30 Passion, patience, and process in investing
52:00 Why great investors are motivated by more than money
1:01:40 The connection between investing, creativity, and classical music

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In this new weekly Excess Returns recap, Jack Forehand and Matt Zeigler highlight the most important investing insights from recent conversations across the Excess Returns podcast network. Drawing on discussions with Andy Constan, Rob Arnott, Kai Wu, Ben Hunt, Rupert Mitchell, Meb Faber and others, the episode connects ideas across macro, markets, AI, credit cycles and valuation. The conversation focuses on timeless investing principles investors can apply today, including how to evaluate expert opinions, how AI may reshape markets and jobs, what defines a true market bubble, why international stocks may be benefiting from global fiscal spending, and why the best opportunities in markets often come after long periods of underperformance.
Topics covered in this episode
How to evaluate expert opinions during major market events and filter signal from noise

Andy Constan’s framework for judging credibility based on experience and confidence

Why charts showing markets rising after wars are often misleading data mining

The difference between believing in AI technology and believing AI stocks are good investments

How AI could both replace and augment human work through the task based structure of jobs

Rob Arnott’s definition of a market bubble using implausible growth assumptions

Why many technology leaders ultimately fail to justify the expectations priced into their stocks

The difference between software companies whose moat is code and those with durable intangible advantages

How brand, switching costs, distribution and network effects protect enterprise software companies

Why AI may be one of the most disruptive technologies in history and what that means for markets

Meb Faber on the myth that the easy money has already been made in international and value stocks

The behavioral challenge of holding unpopular strategies through long periods of underperformance

Rob Arnott on why small cap value could outperform large cap growth over the next decade

Ben Hunt on the point in every credit cycle when lenders say no more

How rising costs of capital can trigger boom bust credit cycles

Rupert Mitchell on why global equity markets often follow government fiscal spending

The growing role of international fiscal policy and capital flows in global market leadership

Timestamps
00:00 Introduction and the idea behind the weekly Excess Returns recap show
03:00 Andy Constan on how to evaluate experts and filter market commentary
11:40 Why charts showing markets rising after wars can be misleading
17:00 Kai Wu on AI technology versus AI investments and the future of work
25:37 Rob Arnott on how to define a market bubble using valuation assumptions
29:35 Kai Wu on software moats, intangible assets and enterprise software durability
35:31 Rob Arnott on how disruptive AI could be for the global economy
39:54 Meb Faber on why the easy money has never been made in markets
43:57 Rob Arnott on small cap value versus large cap growth opportunities
48:39 Ben Hunt on credit cycles and the moment lenders pull back
55:56 Rupert Mitchell on fiscal spending and global equity market performance