Empowering the human potential through education and technologies

Across ten major cryptocurrencies from 2019 to 2024, periods of U.S. excess liquidity coincide with monthly returns about 12 percentage points higher. Rising policy uncertainty cuts that premium roughly in half, and in China it more than offsets it.

Why it matters: regulators can watch stablecoin issuance, leverage and funding conditions to anticipate liquidity-driven speculation.

doi.org/10.1016/j.jfs.2026.101587

Examines how liquidity is interconnected across DeFi lending platforms and identifies what drives their funding liquidity risk, the decentralised equivalent of a bank run.

Why it matters: points protocol designers to the levers, such as interest-rate design, that keep open lending markets stable.

doi.org/10.1016/j.gfj.2024.101055

Among the five largest stablecoins, instability in USDT and USDC significantly drives instability in the others, with weaker evidence for the reverse.

Why it matters: shows users and regulators which coins to watch to protect confidence in digital money.

doi.org/10.1007/s40812-022-00207-3

Examines whether cryptocurrency investors abandoned their own information and followed the crowd around a major political event, building on earlier evidence of herding during the Russia–Ukraine conflict.

Why it matters: shows how political events can turn independent investors into a herd, with consequences for market stability.

doi.org/10.1016/j.najef.2026.102663

Reviews the history of monetary technologies from commodity to fiat money, assesses the challenges and opportunities of adopting programmatic cryptocurrencies as legal tender, and compares proof-of-work and proof-of-stake issuance.

Why it matters: asks how new forms of money would affect growth, inflation and the concentration of wealth.

doi.org/10.2139/ssrn.4407460

Sentiment indicators built with ChatGPT from Bitcoin-industry posts on X significantly explain Bitcoin returns, even after controlling for established sentiment measures.

Why it matters: everyday AI tools can help financial professionals detect signals that earlier indicators missed.

doi.org/10.1108/cfri-05-2024-0278

AI agents can research and decide, but cannot act on their decisions because they lack access to contracts, financial services and marketplaces. Viewed as an institutional technology, blockchain can provide digital-native institutions that let them do so.

Why it matters: agents that can transact on our behalf could greatly augment human productivity.

doi.org/10.3390/jrfm17020054

Programmed scarcity is a major determinant of excess returns for proof-of-work cryptocurrencies.

Why it matters: gives investors an economic basis, rather than hype, for understanding digital-asset value.

doi.org/10.1016/j.iref.2024.103733

Constructs an uncertainty measure specific to real estate. It explains about twice as much of the variation in housing prices and starts as a leading macroeconomic uncertainty measure, and it affects prices as well as construction.

Why it matters: better measurement of uncertainty helps households, developers and policymakers time major decisions.

doi.org/10.1111/1540-6229.12270

A framework based on Bloom's taxonomy tests ChatGPT-4, ChatGPT-3.5, Bard and Bing on economics assessments. They excel at lower-order tasks but are weakest at creating, building theory-based arguments and referencing.

Why it matters: tells educators which higher-order skills to cultivate as AI handles the rest.

doi.org/10.14742/ajet.8902

Develops an AI-assisted learning flow that helps learners and lecturers bring ChatGPT-3.5 into an engineering course, using it to test exercises, tutorial tasks and assessment-style questions, with a self-rating system for judging the AI’s answers. ChatGPT shows significant potential to assist students, but students need training and guidance to use it well.

Why it matters: a practical, tested route to AI-assisted learning in technical disciplines.

doi.org/10.14742/ajet.8825

Team-based authentic assessment strengthens students' sense of their own leadership, especially when combined with extra-curricular activity. Female students report higher leadership confidence, contrary to conventional expectations.

Why it matters: assessment design can develop leadership, a skill AI cannot supply.

doi.org/10.1108/jarhe-02-2024-0060