Forsidebilde av showet Expanding Frontiers

Expanding Frontiers

Podkast av kathrynj2

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Les mer Expanding Frontiers

Alternative investments, frontier research, and the ideas reshaping both. Expanding Frontiers explores alternative investments and the frontier research reshaping how they're built, evaluated, and accessed. Each episode engages with academic papers, industry research, and emerging frameworks across hedge funds, private equity, private credit, real assets, structured products, digital assets, and the data science transforming investment management. Hosted by Kathryn Wilkens, PhD, CAIA, adjunct professor at Rutgers Business School's Master of Financial Analysis program and author of the graduate textbook Alternative Investments: Expanding Frontiers, the show is for practitioners, allocators, students, and curious investors who want substance over surface. New episodes weekly. Production note: Episodes are produced with the help of AI tools, including NotebookLM, for research synthesis and audio generation. All content is reviewed by the host for accuracy. This podcast is independent and not affiliated with any organization unless explicitly stated. Content is for educational purposes only and does not constitute financial, investment, legal, or professional advice.

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50 Episoder

episode Sui Live 2026: The Future of Agentic Finance cover

Sui Live 2026: The Future of Agentic Finance

This episode discusses a major financial technology event showcasing the Sui blockchain as the foundational infrastructure for a future dominated by AI agents. Industry leaders explain how Sui’s unique architecture, featuring parallel execution and an object-centric model, enables high-speed, programmable transactions that traditional systems cannot support. Key announcements include the launch of Sui Dollar, which allows for zero-cost stablecoin movement, and Sui Card, a tool designed to integrate digital assets into real-world commerce. The speakers also introduce Hashi, a decentralized protocol intended to unlock Bitcoin liquidity for use within decentralized finance. Ultimately, the sources frame the network as a highly scalable coordination layer capable of powering a global "machine economy." References Sui Live: The Future of Finance | Miami 2026 | Including Adeniyi Abiodun, Raoul Pal, Guy Wuollet on Real Vision YouTube channel at https://www.youtube.com/watch?v=Y7D8ezalAuY Episode Note This episode draws on the sources listed above and incorporates AI-assisted research synthesis. All content has been reviewed and curated by the host. It is intended for educational purposes only and does not constitute investment or financial advice.

27. mai 2026 - 27 min
episode Smart Contracts on Web 3.0 cover

Smart Contracts on Web 3.0

This episode examines the technological infrastructure, diverse use cases, and inherent security challenges of blockchain-based smart contracts. The first text discussed focuses on the Chainlink Network, detailing how decentralized oracles solve the "oracle problem" by securely connecting on-chain code to real-world data for industries like banking, insurance, and gaming. In contrast, the academic literature review investigates the vulnerability landscape of the Ethereum ecosystem, providing a systematic taxonomy of nearly 200 security flaws. This research categorizes over 200 automated detection tools and benchmarks used to identify critical errors like reentrancy attacks and integer overflows. Together, the materials analyzed illustrate the transition of smart contracts from theoretical concepts to functional applications while highlighting the ongoing need for rigorous auditing and verification. The combined overview emphasizes that while hybrid smart contracts offer immense potential for global trade and finance, their success depends on bridging the gap between external data connectivity and robust programmatic security. References "77+ Smart Contract Use Cases Enabled by Chainlink" [https://blog.chain.link/smart-contract-use-cases/] "A Blockchain-Based Smart Contract System for Healthcare Management" [https://www.mdpi.com/2079-9292/9/1/94] — University of Galway Research "Blockchain and Smart Contracts for Royalty Distribution" [https://www.rangerminerals.com/blockchain-and-smart-contracts-for-royalty-distribution/] — Ranger Land and Minerals "Blockchain and smart contracts for supply chain transparency and vendor management" [https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2024-2262.pdf] — Written by Praveen Kumar, Divya Choubey, Olamide Raimat Amosu, and Yewande Mariam Ogunsuji; published in the World Journal of Advanced Research and Reviews, 2024. "How Blockchain May Disrupt the Automotive Industry – An Insider's View" [https://standards.ieee.org/wp-content/uploads/import/documents/other/e2e-presentations/2019/S2-1_Busch-Bosch.pdf] — A presentation by Peter Busch for Bosch Engineering GmbH, November 2019. "How Smart Contracts Are Transforming Real Estate in 2026" [https://bridge.broker/home-buying-guide/smart-contracts-real-estate-blockchain/] — Bridge Broker "Peer-to-Peer Energy Trading in a Microgrid Leveraged by Smart Contracts" [https://eprints.soton.ac.uk/448422/2/Peer_to_peer_energy_trading_in_a_microgrid_leveraged_by_smart_contracts.pdf] — ePrints Soton "Smart Contract Vulnerabilities, Tools, and Benchmarks: an Updated Systematic Literature Review" [https://arxiv.org/abs/2412.01719] — Written by Gerardo Iuliano and Dario Di Nucci from the University of Salerno; accessed via arXiv. "Smart contracts could improve efficiency and transparency in financial transactions" [https://www.spglobal.com/en/research-insights/featured/special-editorial/smart-contracts-could-improve-efficiency-and-transparency-in-financial-transactions] — S&P Global Episode Note This episode draws on the sources listed above and incorporates AI-assisted research synthesis. All content has been reviewed and curated by the host. It is intended for educational purposes only and does not constitute investment or financial advice.

20. mai 2026 - 26 min
episode Explainable Machine Learning for Investing cover

Explainable Machine Learning for Investing

This episode explores the growing importance of Explainable Artificial Intelligence (XAI) in modern finance, specifically focusing on its role in asset allocation and risk management. Researchers demonstrate how machine learning, such as hierarchical clustering, can identify distinct economic regimes by integrating macroeconomic data with investor sentiment, offering more transparency than traditional "black box" models. This shift toward interpretability allows portfolio managers to understand the underlying drivers of a model's decisions, which is essential for maintaining fiduciary duties and ensuring model robustness. Case studies, including ESG portfolios and regime-based allocation, highlight how XAI enhances performance by capturing market shifts that traditional quantitative methods often miss. Ultimately, the documents emphasize that balancing algorithmic flexibility with human-readable explanations is vital for building trust and reliability in financial applications. References Grevenbrock, N., Zhao, Z., & Patel, N. Model Risk Management in the Age of AI. Moody's. Japinye, A. O., & Adedugbe, A. A. (2025). Explainable AI for credit scoring with SHAP-calibrated ensembles: A multi-market evaluation on public lending data. SSR Journal of Artificial Intelligence (SSRJAI), 2(3), 5-24., Kocaarslan, B. (2026). What Do We Know about Value-Oriented ESG Portfolio? An Explainable AI Application. The Journal of Alternative Investments. Ledoux, A., Forseth, E., & Tricker, E. (2019). Model Interpretability in Machine Learning. Graham Capital Management. Li, Y., Simon, Z., & Turkington, D. (2022). Investable and Interpretable Machine Learning for Equities. The Journal of Financial Data Science., The Ohio State University. SyMANTIC – Novel Symbolic Regression to Discover Accurate Models from Data | Available Technologies | Inventions. Wilson, C.-A. Explainable AI in Finance: Addressing the Needs of Diverse Stakeholders. CFA Institute Research and Policy Center. Ye, R., & Chen, J. (2025). Unlocking the Black Box: A Five-Dimensional Framework for Evaluating Explainable AI in Credit Risk. arXiv:2511.04980. Zhang, R., Yi, C., & Chen, Y. (2020). Explainable Machine Learning for Regime-Based Asset Allocation. IEEE. Episode Note This episode draws on the sources listed above and incorporates AI-assisted research synthesis. All content has been reviewed and curated by the host. It is intended for educational purposes only and does not constitute investment or financial advice.

13. mai 2026 - 25 min
episode 2026 Global Digital Asset Adoption Index cover

2026 Global Digital Asset Adoption Index

In this episode we discuss the 2026 Global Digital Asset Adoption Index, which provides a comprehensive evaluation of how different regions are integrating blockchain technology and cryptocurrencies into their financial systems. Asia leads the world in overall activity due to its massive stablecoin flows and diverse retail and institutional use cases. North America ranks second, serving as the primary hub for institutional capital and regulated investment products like ETFs following landmark legislative shifts. The European Union offers the most advanced regulatory framework via MiCA, though it currently faces challenges with market liquidity and declining exchange registrations. Latin America and Africa demonstrate the highest utility-driven adoption, where digital assets provide essential solutions for inflation hedging and remittances. Ultimately, the report highlights a shifting landscape where stablecoins have become a universal infrastructure for global commerce and finance. References CoinDesk Research. (2026). The 2026 Global Digital Asset Adoption Index. CoinDesk. Episode Note This episode draws on the sources listed above and incorporates AI-assisted research synthesis. All content has been reviewed and curated by the host. It is intended for educational purposes only and does not constitute investment or financial advice.

6. mai 2026 - 23 min
episode Tokenization In Big Banks cover

Tokenization In Big Banks

Tokenization as Structural Shift: An IMF Note and an Academic Counterpoint Tokenization is no longer just an efficiency story. It’s becoming a structural shift in financial architecture. A recent note from the International Monetary Fund, authored by Tobias Adrian, argues that tokenization reshapes settlement, liquidity, and systemic risk through atomic settlement, programmable assets, and embedded compliance. By contrast, research by Alexandru-Stefan Goghie in Finance and Society suggests that bank-led tokenization platforms may not disintermediate finance at all—but instead allow incumbents to reassert control across private credit, repo, and asset management. Taken together, these perspectives raise a deeper question: Is tokenization redistributing power in financial markets?  Or reinforcing it in new form? This is one of the questions I’ll be bringing to Consensus Conference next week. If you’ll be there May 3–5, feel free to connect. If not, I’d still welcome your perspective. References IMF Note: https://www.imf.org/en/publications/imf-notes/issues/2026/04/01/tokenized-finance-574921 [https://www.imf.org/en/publications/imf-notes/issues/2026/04/01/tokenized-finance-574921] Goghie paper: https://journals.sagepub.com/doi/10.1177/10245294261424301 [https://journals.sagepub.com/doi/10.1177/10245294261424301] Episode Note This episode draws on the sources listed above and incorporates AI-assisted research synthesis. All content has been reviewed and curated by the host. It is intended for educational purposes only and does not constitute investment or financial advice.

29. april 2026 - 24 min
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