548 episodes
- In this episode of The Jim Paulsen Show, Jim explains why weakening labor data, softening inflation, and lagged policy tightening could shift markets from inflation fears toward growth and recession fears. He also breaks down why the AI productivity boom may be overstated, how AI capital spending is supporting the economy, why Treasury yields look too high, and why investors may want to rebalance from new era technology stocks toward old era stocks and bonds.
Subscribe to the Jim Paulsen Show on Spotify
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Topics Covered
Why weak jobs data and benign inflation have changed the outlook for the Federal Reserve
Labor force contraction, stalled job growth, and the risks facing consumer spending
Housing affordability, services activity, real income, savings, and signs of economic weakness
How the stock-bond correlation can reveal a shift from inflation fears to growth and recession fears
Why Jim expects Fed rate cuts before year-end and sees downside risk for Treasury yields
How higher oil prices, bond yields, and the dollar can hit stocks and the economy with a lag
Why today's AI productivity boom may be a mirage rather than a repeat of the 1960s or 1990s
How AI CapEx, core capital goods orders, and technology stocks are linked
Why the 10-year Treasury yield may be mispriced relative to growth and inflation
The widening divide between new era and old era stocks and what it could mean for portfolio allocation
Timestamps
00:00 Jim's outlook: weak jobs, benign inflation, and growth fears
04:11 Labor force rollover and consumer warning signs
09:06 Real income collapse and economic surprise data
13:06 Why bond yields could fall below 4 percent
17:45 Why Jim expects Fed cuts instead of hikes
22:07 How policy tightening hits the economy with a lag
26:16 Why productivity gains can be a recession mirage
30:20 What a true productivity boom looks like
34:38 AI stocks as a leading signal for capital spending
39:08 Why Treasury yields may be mispriced
44:31 Oil, core inflation, and the case for easing
48:32 New era versus old era correlation as a warning
52:54 Why today's AI economy may be more vulnerable than dot-com
57:22 Portfolio allocation takeaways: bonds, old era, and tech
Learn more about the Excess Returns podcast network:
https://excessreturns.co
No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients. We Asked T. Rowe's $8 Billion Tech Manager Why We Are in 1998 — And Why Software Is in Trouble
11/08/2026 | 1hT. Rowe Price technology portfolio manager Dom Rizzo joins Jack Forehand and Kai Wu to break down the AI investment cycle, hyperscaler capital spending, semiconductor demand, and why the recent tech selloff may look more like 1998 than the end of the boom. They discuss AI return on investment, OpenAI and Anthropic, open versus closed models, financing the data center buildout, the future of software, labor productivity, and how to construct a global technology portfolio.
Topics covered
Why Dom sees similarities between the 2026 semiconductor correction and the 1998 selloff
Why hyperscaler AI CapEx could accelerate from already historic levels
What cloud revenue growth and operating margins say about AI return on invested capital
Why end-user productivity is the key test for sustainable AI demand
Open-weight models versus frontier labs and where AI economic value may accrue
Why chips, memory, logic semiconductors, TSMC and ASML sit at critical points in the AI value chain
How equity, debt and operating cash flow could finance the next stage of the data center buildout
Why semiconductors remain cyclical even in a structurally capital-intensive AI boom
Why AI agents could turn traditional enterprise software into data pipes
AI productivity, labor displacement and the case for faster GDP growth
How Dom thinks about technology portfolio construction, risk factors and global stock selection
Timestamps
00:00 AI, the tech correction and the 1998 comparison
04:07 Why the AI capital spending cycle may only be halfway
12:33 The real test for AI demand: end-user ROI
17:00 Why frontier models may capture most of the economic value
21:23 Where the biggest AI moats and profit pools could emerge
28:12 Financing the AI buildout with equity and debt
36:03 Are semiconductors in a supercycle or still cyclical?
41:43 What AI agents mean for traditional software companies
46:03 AI productivity versus labor displacement
51:01 Building a portfolio for a technology revolution
56:06 Global tech opportunities and Dom's stock-picking framework
Learn more about the Excess Returns podcast network:
https://excessreturns.co
No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.David Rosenberg and Rich Bernstein on What Ends the AI Trade — And What They Own Instead
08/08/2026 | 1h 3 mins.Richard Bernstein and David Rosenberg reunite to debate the Federal Reserve, inflation, the AI investment boom, market bubbles, gold and the case for international diversification. The former Merrill Lynch colleagues examine whether the Fed should raise rates, how AI CapEx is reshaping the U.S. economy, why credit markets may lead the AI trade, what is driving gold, and where investors may find opportunities outside the mega-cap U.S. market.
Topics covered
Why the Taylor Rule points toward higher rates and why Rosenberg thinks the Fed should not hike
What slowing GDP growth, productivity and labor costs suggest about underlying inflation
How AI CapEx and data center spending may be misallocating capital away from housing and the broader economy
Why the current AI boom differs from the late-1990s technology bubble
How credit spreads, CDS markets and financing costs could signal trouble in the AI trade before equities do
What real interest rates, the U.S. dollar and central bank demand mean for gold
Why Bernstein views gold as a portfolio spare tire rather than a short-term trade
Why non-U.S. stocks and international markets may offer a better valuation and growth opportunity
How AI exposure extends beyond the Mag Seven into financials, industrials and utilities
Why CAPE valuations, leverage, sentiment and market positioning point to a highly speculative U.S. market
Why diversification becomes most unpopular when investors may need it most
What Bob Farrell's market rules say about crowded positioning and consensus forecasts
Timestamps
00:00 Introduction
08:31 Why Rosenberg thinks the Fed should not hike
16:02 AI, data centers and capital misallocation
25:08 What is driving gold: real rates, the dollar and central banks
36:11 Why Bernstein sees a secular shift toward non-U.S. stocks
41:41 How AI concentration extends beyond the technology sector
48:31 International diversification as protection from AI concentration
54:06 Bob Farrell's Rule 9 and the danger of consensus
1:00:06 The housing-cycle warning Bernstein and Rosenberg saw before the financial crisis
Learn more about the Excess Returns podcast network:
https://excessreturns.co
No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.4% Inflation. Stretched Valuations. Why Is the Market Still Risk-On? | Tian Yang
06/08/2026 | 59 mins.Tian Yang, head of research at Variant Perception and portfolio manager of the VPX ETF, explains how investors can use adaptive leading indicators, capital cycle analysis and behavioral signals to navigate a market shaped by AI spending, inflation and government intervention. He breaks down why the macro backdrop remains risk-on, what would signal a true market top, why a Federal Reserve rate hike may still be unlikely and how AI could reshape profits, jobs and portfolio construction.
Variant Perception
https://www.variantperception.com/
Variant Perception Cycle Aware US Equity ETF
https://etf.variantperception.com/
Topics covered
How first-principles thinking separates causal signals from noisy data
Why static recession indicators and consumer sentiment have become less reliable
How Variant Perception combines growth, inflation, policy and liquidity into a Macro Risk Indicator
Why AI capital spending and low savings rates are supporting economic resilience
How AI profits could broaden from hardware bottlenecks to adopters and complementary assets
Why the sovereign technology race may extend the AI investment cycle
What savings rates, liquidity, leverage and cash settlement reveal about recessions and market tops
How potential SpaceX, Anthropic and OpenAI supply could affect public equity markets
What capital cycle and crowding signals say about semiconductors and hyperscalers
Why headline inflation may stay high without creating persistent core inflation
How the K-shaped consumer, labor market and Federal Reserve reform shape the policy outlook
How AI could widen economic inequality, compress wages and change investment research
How the VPX ETF uses adaptive sector tilts, stock selection and active risk
Timestamps
00:00 First principles, causal data and leading indicators
04:48 Why traditional recession indicators stopped working
09:00 Building the Macro Risk Indicator
13:02 How AI CapEx is keeping the economy resilient
17:18 Is the AI boom different from past bubbles?
21:32 Why rising savings rates often precede recessions
26:11 Why the market-top warning is amber, not red
30:58 Are semiconductors still cyclical?
36:22 Why an oil shock may not force the Fed to hike
42:12 How Kevin Warsh could reform the Federal Reserve
46:50 The increasingly bifurcated economy
51:11 How AI is changing investment research
55:38 Active risk, playing the game and avoiding forced errors
Learn more about the Excess Returns podcast network:
https://excessreturns.co
No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.The Biggest Leak in Finance | Brent Donnelly on Why You're Probably Too Bearish
04/08/2026 | 1h 1 mins.Brent Donnelly joins Matt Zeigler to explain how professional traders build a durable edge through risk management, trading psychology, probabilistic thinking, and creative market analysis.
Drawing from his new book, Trade Outside the Box: Advanced Thinking for Professional Traders, Brent breaks down why trading strategies decay, why rationality beats intelligence, how to avoid risk of ruin, and how lessons from poker, behavioral finance, and real-world experience can improve decision-making.
Trade Outside the Box: Advanced Thinking for Professional Traders
https://amzn.to/4h9bi3e
Brent Donnelly on X
https://x.com/donnelly_brent
Spectra Markets
https://www.spectramarkets.com
Topics covered:
Why fundamentals, technical analysis, behavioral finance, and quantitative methods are necessary but not sufficient for trading success
How traders can develop an edge by connecting markets to poker, psychology, biology, auto racing, and video games
Why profitable trading strategies decay as more investors discover and copy them
How changing volatility regimes force traders to adapt their style and avoid becoming a one-trick pony
Why mismatching a long-term investment thesis with a short-term stop loss can destroy a good idea
How trading journals and P&L data help separate normal variance from a broken process
Why the house money effect can make traders more reckless after large gains
Why rationality, flexibility, and expected value matter more than credentials or raw intelligence
How Bayesian thinking helps traders update probabilities and fight confirmation bias
The difference between independent thinking and blind contrarianism
Why avoiding risk of ruin, protecting family and health, and defining success beyond money are essential to a sustainable trading career
Timestamps:
00:00 Introduction to Brent Donnelly and Trade Outside the Box
04:00 Why smart analysts often produce fully priced trade ideas
08:00 Poker discipline and avoiding boredom trades
12:00 How lead-lag correlation trading lost its edge
16:35 Matching a trade's stop loss to its time horizon
21:00 What trading data reveals about win rates and expected value
25:00 The house money effect and the danger of overearning
29:00 Why rational traders beat smarter traders
33:00 Strong opinions weakly held and Bayesian updating
37:00 Curating a balanced diet of bullish and bearish information
41:00 Using creativity and outside disciplines to find market edge
45:11 Avoiding risk of ruin and the lessons of Jesse Livermore
50:29 The Serenity Prayer and focusing on what traders can control
55:00 Choosing family and health over markets
59:00 Why your first thought may not be your own
Learn more about the Excess Returns podcast network:
https://excessreturns.co
No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms, or their clients.
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Excess Returns is dedicated to making you a better long-term investor and making complex investing topics understandable. Join Jack Forehand, Justin Carbonneau and Matt Zeigler as they sit down with some of the most interesting names in finance to discuss topics like macroeconomics, value investing, factor investing, and more. Subscribe to learn along with us.
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