In this episode of Excess Returns, we sit down with Neil Howe, author of The Fourth Turning Is Here and co-creator of the Fourth Turning generational framework, along with Ben Hunt of Epsilon Theory, to discuss where we are in the current cycle and what it means for markets, inflation, AI, capital flows, and America’s long-term economic outlook. From the debasement trade and rising gold prices to global capital crowding out and the structural forces shaping productivity and growth, this conversation connects generational theory with real-world investing decisions. If you’re thinking about inflation, deficits, AI capital spending, global diversification, or how to position defensively and offensively in a shifting macro regime, this discussion provides a powerful framework for navigating what may be a historic transition period.

Topics Covered

• The Fourth Turning framework and where we are in the current crisis cycle

• Why inflation is not a problem but a policy solution in major crises

• The collapse in US national savings and long-term deficit risks

• Capital flows, the debasement trade, and the future of the US dollar

• Gold, commodities, and real assets in a regime shift

• Global diversification and opportunities outside the United States

• AI capital spending, productivity gains, and the risk of overinvestment

• Crowding out effects from government deficits and AI hyper scaling

• Trust, geopolitics, and the long-term implications for global markets

• Healthcare, demographics, and structural investment themes

• Defensive and offensive positioning in a Fourth Turning environment

Timestamps

00:00 Inflation as a solution and the generational crisis framework
04:00 Explaining the Fourth Turning and historical crisis cycles
12:55 Narratives, generational archetypes, and market behavior
22:24 Is the Fourth Turning pessimistic or optimistic
34:00 Inflation, gold, and the debasement trade
40:00 Global capital flows and the reversal of US inflows
50:00 AI capital spending and the K shaped capital markets
55:09 Crowding out, deficits, and slow growth risks
01:02:23 Defensive and offensive investment positioning
01:09:31 Final thoughts on diversification, gold, and financials

In this episode of Excess Returns, we sit down with Pete Hecht of AQR to break down portable alpha, capital efficient portfolio construction, and how investors can combine equity beta with truly diversifying sources of alpha. We cover how portable alpha works in practice, how it solves the funding problem for alternative strategies, and why implementation details like leverage, liquidity, and financing costs matter more than most investors realize. If you’re interested in diversification, long short investing, managed futures, equity market neutral strategies, or improving total returns without giving up equity exposure, this discussion provides a practical and detailed framework.

Main Topics Covered

• What portable alpha actually is and how it differs from traditional stock bond alternative portfolios

• How portable alpha combines equity beta exposure with unconstrained long short alpha

• The funding problem with alternatives and how portable alpha solves it

• Turnkey implementation versus separating alpha managers and beta overlays

• The role of equity market neutral, managed futures, and multi strategy approaches

• Why private equity and private credit are poor candidates for portable alpha

• Long short leverage versus long only leverage and how to think about risk

• Target volatility, risk models, and stress testing leveraged portfolios

• Financing costs in futures markets and how higher interest rates affect strategies

• How to evaluate portable alpha using excess returns, tracking error, and tail risk

• Tax aware implementation and after tax returns

• Why mutual funds are not obsolete for active long short strategies

• The importance of asking whether a view is already priced into valuations

Timestamps

00:00 Why you cannot eat a risk adjusted return
02:12 Defining portable alpha and the problem it solves
03:55 Portable alpha versus traditional balanced portfolios
06:54 The funding problem with diversifying alternatives
09:00 How portable alpha works in practice
13:05 What types of alpha strategies work best
16:35 Managed futures and crisis alpha
19:49 Simplicity versus complexity in implementation
21:46 Why private equity and private credit do not work in portable alpha
24:15 Understanding leverage and risk management
29:18 Target volatility and portfolio construction
34:52 Stress testing and lessons from COVID and 2022
35:01 Risks and financing costs of portable alpha
38:50 Interest rates and leveraged strategies
39:07 Identifying hidden beta and volatility laundering
46:08 Introducing AQR Fusion Funds
50:25 Evaluating performance versus the benchmark
53:17 Tax efficiency in long short mutual funds
57:29 Is your view already priced in

In this episode of Excess Returns, Kai Wu of Sparkline Capital returns to discuss his latest research on AI adoption, ROI, and what it all means for investors.

Building on his prior work on the AI CapEx boom, Kai tackles the trillion dollar question at the center of today’s market: Is AI generating real, measurable economic returns across the broader economy, or are we still in an infrastructure-driven bubble?

Using a systematic analysis of earnings calls, patent data, and adoption trends, Kai lays out a framework for identifying which companies are truly benefiting from artificial intelligence and how investors can position portfolios accordingly.

Find the Full Paper Here:
https://etf.sparklinecapital.com/

Main topics covered:

• Satya Nadella’s AI bubble framework and why broad economic diffusion matters

• The AI adoption S-curve and where we are in the technology diffusion cycle

• A new AI ROI taxonomy based on earnings call analysis and quantified economic gains

• Real-world AI productivity, revenue, and cost-saving examples across industries

• Infrastructure vs early adopters vs laggards and how companies were categorized

• AI-driven outperformance and excess returns across different adopter groups

• Valuation dispersion between AI infrastructure stocks and AI early adopters

• The risk of overcapacity and lessons from railroads and the dot-com telecom boom

• Competition among large language models and the durability of AI moats

• S&P 500 exposure to AI infrastructure and hidden concentration risk

• The case for AI early adopters as a middle ground between growth and value

• Intangible value investing and the concept of AI yield

Timestamps:

00:00:00 The trillion dollar question and what “real ROI” means
00:03:19 Nadella’s bubble framework: diffusion vs a narrow CapEx trade
00:06:08 The classic tech diffusion S-curve and where AI is on it
00:32:25 Why infrastructure is being rewarded even if the ROI story is different
00:33:04 The key chart: adoption vs valuation shows “basically no relationship”
00:38:00 Why early adopters and laggards should separate
00:38:26 The “25% ROI” example and how it could show up later in fundamentals
00:39:03 Railroads and fiber: builders go bankrupt, users capture the value
00:39:45 Telecom index fell 95% and never recovered (dot-com bust parallel)
00:40:00 The application layer captures profits; infrastructure becomes a utility
00:41:00 The punchline: transformative tech, but builders can still be bad investments
00:42:57 Overcapacity question: where are we on the line?
00:43:17 The buildout: another $5 trillion of data centers “or whatever the number is”
00:44:00 If there’s no ROI, companies cancel orders
00:45:01 Moat and LLM competition discussion begins
00:49:00 The big one: adding infrastructure names gets the S&P to 46% AI infrastructure
00:50:00 “Alternative indices” swing you to laggard risk
00:51:00 The “false choice” and the “middle ground” framing (early adopters)

In this episode of Excess Returns, we sit down with Bloomberg Opinion columnist Nir Kaissar for a wide-ranging conversation on markets, AI, interest rates, private credit, small caps, and the risks investors may be underestimating. Nir shares his unexpected predictions for 2026, challenges the consensus on Fed rate cuts, explains why high profitability may be putting a floor under valuations, and offers a thoughtful framework for thinking about AI, concentration risk, and the future of public versus private markets. This is a deep dive into today’s most important investing debates, grounded in history and focused on what may come next.

Topics Covered

• Nir’s unexpected predictions for 2026 and why mass adoption of autonomous vehicles may arrive faster than investors expect

• Why the consensus on lower interest rates in 2026 may be wrong and what the two year Treasury yield is signaling

• The impact of tariffs, affordability pressures, and corporate margins on inflation

• Why high corporate profitability may support elevated stock market valuations even if returns slow

• The role of earnings growth in driving S&P 500 returns and why 2015 to 2024 may not repeat

• Is AI more like 1995 or 1999 in the internet cycle and what that means for long term investors

• The convergence of big tech companies around AI and the risks of a more zero sum competitive landscape

• Why companies staying private longer could hurt retail investors and distort public market indices

• Concentration risk in the S&P 500 and what it means for long term portfolio construction

• Opportunities and risks in small cap stocks, including the importance of quality screens

• The growth of private credit markets and the hidden risks investors may not see

• Why Treasuries may still be the cleanest shirt in the laundry during a crisis

• Lessons from 20 years of running strategies and what Nir has changed his mind about

Timestamps

00:00 Nir’s 2026 predictions and the rise of Waymo
05:00 Interest rates, Trump, and the outlook for Fed policy
08:40 Tariffs, inflation, and corporate margins
12:00 Valuations, profitability, and future S&P 500 returns
16:00 AI compared to the internet era and long term investing lessons
19:00 Public versus private markets and regulatory concerns
32:00 Concentration risk and the Magnificent Seven
39:00 Small caps, quality screens, and value opportunities
47:00 Private credit risks and default cycles
54:30 Nir’s investment philosophy and 20 year lessons

David Giroux, CIO of T. Rowe Price and manager of the Capital Appreciation strategy, joins Excess Returns for a wide ranging discussion on market valuation, AI investing, Mag 6 dynamics, utilities, healthcare, fixed income, and how to think independently in volatile markets. David shares his framework for exploiting structural market inefficiencies, why market drawdowns can create opportunity, how he evaluates the S&P 500 at the micro level, and what investors are getting wrong about AI, profit margins, and the current cycle.

Main topics covered in this episode

• Exploiting structural market inefficiencies in GARP stocks, high yield, and double B credit
• Why market drawdowns often lower forward risk and increase expected returns
• Strategic equity allocation during periods of fear and volatility
• Rethinking S&P 500 valuation through 500 company bottom up analysis
• The changing composition of the index and its impact on profit margins
• Where the most overvalued and undervalued areas of the market may be today
• AI investing framework including Nvidia, AMD, cloud providers, and software risk
• How AI could reshape margins, labor productivity, and enterprise software
• Differences between today and the dotcom bubble
• Overweight positioning in utilities and healthcare and the thesis behind each
• Fixed income positioning including the belly of the Treasury curve and fiscal risk
• Commodities, gold, and fiscal sustainability
• Lessons for portfolio managers on independent thinking and making high conviction bets

Timestamps

00:00 Market drawdowns and forward returns
02:09 Exploiting structural market inefficiencies
06:28 Strategic equity allocation during selloffs
11:22 Is the market expensive and how to value the S&P 500
15:00 Profit margins and index composition
17:13 Where valuation excess exists outside the Mag 6
20:38 How to think about AI and enterprise adoption
27:18 AI disruption risk across sectors
39:20 AI versus the dotcom bubble
42:30 Apple versus Meta and capital allocation
46:53 Overweight utilities and healthcare
52:57 Fixed income opportunities and risks
57:32 Commodities, gold, and fiscal concerns
01:00:15 Lessons for new portfolio managers

In this episode of Excess Returns, we sit down with Kevin Muir, author of The Macro Tourist, for a wide-ranging conversation on market sentiment, asset rotation, and the growing signals of stress beneath the surface of global markets. Kevin explains why extreme bullishness can be dangerous, why gold and commodities may be flashing warning signs, and how shifts in currencies, energy, and global capital flows could reshape portfolios in the years ahead. From hedging strategies to volatility, from AI-driven concentration to international diversification, this discussion focuses on how investors can think clearly in an environment where traditional relationships are breaking down.

Topics covered:

• Why extreme bullish sentiment can be a warning sign for markets

• The meaning of “buying straw hats in the winter” and how to think about hedging

• Market breadth, small caps, and whether rotations are healthy or late cycle

• Gold, silver, and what precious metals signal about financial stress

• Cross-asset volatility and why correlations are changing

• Energy markets, commodities, and the long-term impact of underinvestment

• Global capital flows, foreign ownership of US assets, and currency risk

• The US dollar, trade deficits, and implications for international investors

• Portfolio construction lessons from bonds, commodities, and FX

• How macro regime shifts can change risk management and diversification

Timestamps:
00:00 Introduction and market sentiment overview
03:00 Buying protection and the straw hat analogy
07:00 Sentiment indicators and market confirmation
12:00 Market rotations, small caps, and late-cycle risks
18:00 Gold, silver, and precious metals as warning signals
23:00 Bonds, currencies, and broken correlations
29:00 Energy markets and commodity underinvestment
37:00 Global capital flows and foreign ownership of US assets
44:00 The US dollar, trade deficits, and FX volatility
52:00 Macro regime shifts and portfolio construction lessons

In this episode of Excess Returns, we sit down with Victoria Greene of G Squared Private Wealth for a wide-ranging conversation on markets, macro risk, portfolio construction, and how investors should think about 2026 and beyond. Victoria brings a pragmatic, risk-aware framework to investing, blending top-down macro analysis with bottom-up fundamentals, technicals, and a strong focus on cash flow, diversification, and policy risk. We cover everything from the rise of what she calls a badger market, to AI capex, market concentration, inflation risk, and why policy error, not valuation, is what historically ends bull markets.

Main topics covered
• Why valuation is a poor market timing tool and what actually ends bull markets
• The concept of a badger market and how investors should mentally prepare for volatility
• Cash flow never lies and how Victoria evaluates business quality
• Diversification in 2026 and why international, commodities, and value matter more now
• Risks and opportunities in the labor market, AI-driven disruption, and productivity
• The K-shaped economy and what it means for consumers and corporate earnings
• 60/40 portfolios, alternatives, and where commodities fit today
• AI investing from infrastructure to software and cybersecurity
• Yield curve dynamics, inflation risk, and portfolio positioning
• Active vs passive investing in a concentrated market
• How policy decisions and election dynamics influence markets

Timestamps
00:00 Intro and why valuation does not kill bull markets
01:40 Investment philosophy and macro first portfolio construction
06:00 Cash flow never lies explained
07:40 Diversification beyond US large caps
10:00 Market expectations and big tech earnings risk
11:00 What is a badger market
12:40 Is the 60 40 portfolio dead
15:00 Why Victoria remains constructive on markets
18:00 Politics, sentiment, and market noise
21:00 Policy error vs valuation as the real risk
26:40 The K-shaped economy and consumer health
31:10 Hard data vs soft data disconnect
34:10 Labor market risks and data reliability
36:40 Yield curve steepening and inflation risk
41:40 Portfolio positioning in a higher inflation world
43:00 How to invest in AI beyond the Mag 7
47:20 Where we are in the AI cycle
49:30 Active management challenges and opportunities
53:00 Valuation, planning, and long-term return expectations

Follow Last Call on Spotify

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Join Jack Forehand and Matt Zeigler for the premiere episode of Last Call, a new monthly market wrap show where we go beyond the headlines to deliver actionable investment insights — and have a little fun along the way.

Instead of focusing on index performance or short-term moves, we step back and connect the dots between macro instability, narrative shifts, options market signals, private credit risk, AI capital spending, and the changing nature of the Magnificent Seven.

Featuring conversations with Brent Kochuba from SpotGamma, Ben Hunt from Perscient, Kai Wu from Sparkline Capital, and clips from our recent interviews with Liz Ann Sonders and Aswath Damodaran, the episode blends market structure, behavioral finance, valuation discipline, and long-term investing context to help investors understand what is really driving today’s market environment — and how to think about it going forward.

Main Topics:

• Why this is not a traditional market recap and how Last Call is designed to be more useful for investors

• Instability versus uncertainty — and why today’s market feels different• Loss of trust in institutions, policy, and global systems and its impact on markets

• What options market flows reveal about hidden market risks and sudden volatility• How private credit has reached bubble-like conditions and why narrative risk matters

• The debate over retail and retirement account exposure to private credit• Why valuation discipline looks different when correlations rise across asset classes

• Aswath Damodaran on trimming positions, raising cash, and the difficulty of finding uncorrelated assets

• How the Magnificent Seven are changing from asset-light to asset-heavy businesses

• AI capital expenditure, historical spending booms, and why infrastructure builders often underperform

• Whether this AI cycle is truly different from railroads, telecom, and past technology booms

Timestamps

00:00 — Intro and opening clips

01:10 — What Last Call is and why this format exists

04:30 — Instability versus uncertainty in today’s market

09:58 — Loss of trust, gold, and historical parallels

13:18 — Brent Kochuba on options flows and hidden market stress

25:17 — How options dislocations explain sudden market drops

25:40 — Ben Hunt on private credit narrative risk

28:00 — Why private credit exposure is everywhere

32:32 — Retail access versus restrictions in private credit

36:19 — What happens if the private credit bubble breaks

39:28 — Aswath Damodaran on raising cash and trimming positions

47:08 — The changing nature of the Magnificent Seven

47:42 — Kai Wu on AI capex and asset-heavy tech

50:48 — Why high capital spending often leads to underperformance

56:01 — Historical parallels from railroads to the dot-com boom

In this episode of Excess Returns, we’re joined again by Dan Rasmussen of Verdad Advisors for a wide-ranging conversation that challenges some of the most popular narratives in markets today. From private equity and private credit risks to AI-driven capital cycles and overlooked opportunities in biotech and international equities, Dan offers a deeply research-driven perspective on where investors may be misallocating capital and where future returns could emerge. Alongside Justin and special guest co-host Kai Wu, the discussion connects valuation, incentives, and innovation in a market environment shaped by concentration, leverage, and technological change.

Main topics covered
• Why private equity performance continues to disappoint and where the biggest structural risks are emerging
• The growing stress in private credit and what rising bankruptcies signal for lower middle-market deals
• Why democratizing private equity through 401ks, interval funds, and ETFs may create more problems than solutions
• How AI CapEx is changing the economics of Big Tech and why asset-light models may be getting worse, not better
• The case for diversifying away from U.S. concentration toward international markets and international small value
• Why bubbles are often necessary for innovation and how to think about AI through that historical lens
• How investors may be underestimating valuation and growth bankruptcy risk in the Mag 7
• Why biotech is one of the hardest sectors to model and how Verdad rebuilt its framework from scratch
• How intangible value, clinical trial data, specialist ownership, and peer momentum can improve biotech investing
• What capital starvation, M&A dynamics, and global competition mean for biotech’s future returns

Timestamps
00:00 Introduction and market narratives
02:20 Revisiting private equity risks and performance
06:58 Private credit stress and bankruptcy signals
10:58 Private equity in 401ks and interval fund risks
14:52 Private assets in ETFs and liquidity concerns
15:45 Why bubbles drive innovation and capital formation
20:13 AI CapEx, Mag 7 concentration, and valuation risk
25:24 International diversification and market leadership
29:41 Why Verdad turned to biotech research
37:13 Rebuilding biotech valuation and quality metrics
44:26 Clinical trial data and peer momentum insights
49:17 Portfolio construction and long-short biotech strategies
51:00 Capital starvation, AI, and biotech’s setup
53:58 Research culture, humility, and evolving quant models

In this episode of our new show The 100 Year Thinkers, Chris Mayer and Robert Hagstrom explore how the words investors use quietly shape the decisions they make — often in destructive ways. From labels like “cheap,” “expensive,” and “compounder” to debates about valuation, concentration, and AI, the conversation digs into how language collapses uncertainty into false certainty. Drawing on general semantics, mental models, and decades of investing experience, they explain why confusing maps for reality leads investors astray — and how clearer thinking can change how you see markets, risk, and long-term returns.

Topics discussed include:

• Why paying 30x earnings can be rational when return on invested capital stays high

• How the word “is” smuggles hidden assumptions into investment decisions

• The difference between a company being a compounder and having compounded in the past

• Why valuation debates are really disagreements about time horizon

• The “map vs. territory” problem in financial statements and market data

• Market concentration, index construction, and why benchmarks can mislead investors

• How language shapes narratives around value, growth, and risk

• AI investing, capital allocation, and separating durable businesses from hype

• Why many binary true-or-false questions are traps for investors

• How long-term investors think in decades, not quarters