Excess Returns

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

Subscribe to the Jim Paulsen Show on Spotify

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In this episode of the Jim Paulsen Show, Jim joins Jack Forehand and Justin Carbonneau to break down the macro forces shaping today’s markets and economy. Jim explains why the economy may be far weaker than headline GDP numbers suggest, how technology and AI investment are masking weakness in the broader economy, and why leadership in the stock market may be shifting. The conversation also explores the market implications of geopolitical conflict, the relationship between policy and market leadership, and how investors should think about AI’s long-term economic impact.
Topics covered in this episode
How geopolitical events like the Iran conflict affect markets, volatility, oil prices, and investor sentiment

Why market reactions to geopolitical shocks often fade once the situation is “vetted” by investors

The relationship between oil prices, the US dollar, and global financial markets

Why Paulsen remains constructive on international stocks and emerging markets despite recent volatility

Why energy and food now represent a much smaller share of consumer spending than in past inflation cycles

The argument that inflation fears may be overstated given structural disinflationary forces in the economy

How AI and technological innovation can destroy some jobs while simultaneously creating new economic demand

Why technological progress often lowers costs and expands markets rather than simply eliminating work

The concept that the “new economy” driven by technology investment is now large enough to influence overall GDP growth

Paulsen’s analysis showing that roughly 11 percent of the economy tied to new-era investment is growing rapidly while the remaining 89 percent is barely growing

Why the broader economy may resemble a recession even while headline GDP remains positive

How the dominance of large technology companies in indexes like the S&P 500 may be masking weakness in the broader market

The historical “toggle” between technology leadership and broader market leadership in equity markets

Why policy conditions like the yield curve and monetary easing often drive leadership shifts toward value, small caps, and cyclical stocks

Whether the Federal Reserve could begin easing policy without a traditional recession

Why policy support may eventually broaden the bull market beyond technology stocks

Timestamps
0:00 Jim Paulsen on geopolitical volatility, oil prices, and market reactions
2:50 How investors should think about the Iran conflict and market implications
10:50 The relationship between oil prices, the US dollar, and safe-haven flows
12:20 Why Paulsen likes international and emerging market stocks
14:30 Why higher oil prices may not lead to sustained inflation
18:40 AI disruption and the economic debate around jobs and productivity
23:00 How innovation historically creates new demand and economic growth
29:40 Technology is the tail wagging the economic dog
33:30 Why the “new economy” is growing far faster than the rest of the economy
37:00 Evidence that most of the economy may already resemble a recession
41:00 Profit growth disparity between technology and the rest of the economy
45:40 Why the stock market can mask weakness in the broader economy
46:30 The historical leadership toggle between tech and the broader market
49:00 Valuation differences between technology and other sectors
50:30 How policy conditions influence market leadership
55:00 Signs that leadership may already be shifting beyond tech
57:00 Could the Fed ease without a traditional recession
59:00 What a policy shift could mean for the next phase of the bull market

Rob Arnott returns to Excess Returns to discuss the biggest questions facing investors today, including the impact of geopolitical conflict, the valuation gap between U.S. and international markets, the long-term investment implications of artificial intelligence, and why extreme spreads between growth and value may present major opportunities. Arnott, founder of Research Affiliates and pioneer of fundamental indexing, explains why AI itself is not necessarily a bubble but many AI stocks may be priced for implausible growth. He also discusses why small cap and value stocks may offer some of the most compelling long-term opportunities in decades, how market narratives drive valuations, and why diversification beyond the U.S. could be critical for investors. Throughout the conversation, Arnott draws on decades of market history to explain how bubbles form, why profit margins tend to mean revert, and how investors should think about positioning portfolios for the next market cycle.
Topics covered in this episode:
• Why Rob Arnott believes AI is real but many AI stocks may be in a bubble
• How market narratives can push valuations far beyond fundamentals
• Why U.S. stocks trade at roughly twice the valuation multiples of international markets
• The widening valuation gap between growth and value stocks
• Why small cap stocks may be one of the most attractive opportunities today
• The massive capital spending required to build the AI ecosystem
• How technological revolutions historically destroy jobs but create new opportunities
• Why investors should learn to use AI tools to remain competitive
• The definition of a market bubble based on implausible growth expectations
• Lessons from the dot-com bubble and the history of dominant technology companies
• Why profit margins tend to mean revert over time
• The long-term outlook for international stocks and diversification
• How fundamental indexing works and why it can create rebalancing alpha
• The concept of the “Trifecta” approach combining value, core indexing, and growth
• The risks of conglomerate premiums and the diversification discount
• Why the largest companies in the market rarely remain dominant over long periods
• How investors should think about balancing growth exposure with cheaper opportunities
Timestamps:
00:00 AI vs AI Stocks: Why Arnott Sees a Bubble
00:01 Introduction to Rob Arnott and Research Affiliates
02:13 The Iran Conflict and How War Impacts Markets
06:41 U.S. Valuations vs International Opportunities
08:50 The Extreme Spread Between Growth and Value
10:00 The Small Cap Opportunity and Index Effects
13:08 The Citrini AI Paper and Long-Term Technology Shifts
14:09 How Technological Revolutions Destroy and Create Jobs
16:00 How AI Is Already Changing Investment Research
20:00 Why AI Tools Are Still Losing Money
23:40 How Investors Should Think About AI Exposure
25:21 Arnott’s Definition of a Market Bubble
27:41 Lessons from the Dot-Com Bubble
28:34 Profit Margins and Mean Reversion
30:34 Technology Moats and Competitive Disruption
32:12 Will Mean Reversion Still Work in Markets?
36:02 The Case for International Stocks
41:39 The Trifecta: A New Framework for Indexing
51:15 Why Expensive Slow-Growth Companies Underperform
56:25 Conglomerate Premiums and Mega Cap Tech
57:00 The Long-Term Case for Value and Small Caps
01:00:00 Why Market Leaders Rarely Stay on Top