Excess Returns

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.

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.

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.

On this episode of our new market wrap show Last Call, we examine the hidden rotation beneath calm stock market indexes, including sharp AI and semiconductor volatility, small-cap strength, forced fund liquidations, higher rates and changing Federal Reserve guidance.
Jack Forehand and Matt Zeigler are joined by Jim Paulsen, Ben Hunt, Brent Kochuba, Cameron Dawson and Dave Nadig to discuss stock market correction risk, the economics of the AI data center buildout, options flows, market leverage, regulation and what could drive volatility next.Follow Last Call on Spotify⁠⁠⁠⁠⁠⁠⁠
⁠⁠⁠⁠⁠⁠⁠Follow Last Call on Apple Podcasts⁠

Topics covered
Why market indexes can hide sharp rotation, dispersion and volatility in semiconductors and high-beta technology stocks

Jim Paulsen's Policy Pain framework linking oil, Treasury yields, dollar strength and lagged effects on stocks, bonds and economic growth

Why technology stocks could enter a bear market while old-economy sectors, small caps and value stocks hold up

Ben Hunt's World War AI thesis comparing the AI infrastructure buildout with inflation-adjusted World War II spending

How hyperscalers, equity issuance, private credit and government financing could crowd out consumers and businesses

Why data centers could consume nearly one quarter of U.S. electricity and lead to higher prices, rationing and government intervention

What the Situational Awareness fund liquidation and Citadel portfolio transaction reveal about forced market flows

How options correlations and narrow market breadth can separate a technical rebound from a fundamental AI bottom

Risks from speculative retail investments, weakened regulators, leverage and cyclical semiconductor profit margins

Why reduced Fed forward guidance could create surprise policy decisions and greater algorithmic market volatility

Timestamps
00:00 Market rotation and AI volatility beneath the indexes04:07 Jim Paulsen on Policy Pain and market vulnerability09:23 Why tightening hurts stocks before helping bonds14:23 Tech bear market risk and a possible leadership shift18:23 Ben Hunt on World War AI, private credit and systemic risk26:00 Data center electricity demand and the energy constraint31:29 Brent Kochuba on the Situational Awareness liquidation36:00 The forced buying behind the AI stock rebound40:00 Why the liquidation bounce may not signal an AI bottom44:00 How forced flows distort fundamental market narratives48:00 Retail investing pitches, liquidity and cycle FOMO52:00 Deregulation by destaffing at the SEC and CFTC56:00 Semiconductor operating leverage and fragile S&P 500 margins01:00:07 Jack's grievance with the YouTube algorithm01:04:29 What happens when the Fed stops giving forward guidance01:08:34 How markets could react to a surprise Fed decision
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 are excited to announce the launch of a new podcast, Why Am I Reading This Now? with Ben Hunt. Stories and narratives are increasingly shaping markets, and Ben and his team at Perscient have developed a unique system for measuring how those narratives emerge, spread and change.
In each episode, Ben and Matt Zeigler will examine the major issues facing investors through this narrative lens, helping listeners better understand the stories driving markets and what they could mean for the economy, policy and investment outcomes.
We have included this first episode in the Excess Returns feed. To continue receiving new episodes, subscribe to the Why Am I Reading This Now? podcast on all major podcast platforms using the links below.
Subscribe on Spotify
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Topics covered
Why AI CapEx and data center construction have become critical drivers of US economic growth
How hyperscalers are shifting from cash flow financing to debt, equity issuance and private credit
Why a slowdown in AI infrastructure spending could threaten markets, the economy and the financial system
How trillions of dollars in AI investment may crowd out consumer credit, business investment and government borrowing
Why data centers could consume a dramatically larger share of US electricity production
How energy shortages could lead to higher utility costs, rationing and price controls
Why the Iran war and higher oil prices may create a lasting increase in global energy costs
How Perscient tracks the return of bearish AI narratives and growing political opposition to data centers
Why both political parties may support government ownership, loan guarantees, bailouts and economic stimulus
How competition with China could become the narrative used to justify greater government control of the AI industry
Timestamps
00:00 Introducing Why Am I Reading This Now? with Ben Hunt
04:00 How debt, equity issuance and private credit are financing AI CapEx
08:06 Data center electricity demand and the energy crowding-out problem
13:21 Why an AI bailout may become politically inevitable
17:30 Oil shifts from a temporary shortage to a structural supply reduction
22:00 The bearish AI narrative returns as political opposition grows
26:00 Government ownership, price controls and the AI competition with China