Excess Returns

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