This paper identifies a predatory trading mechanism in Korea where daily LETF rebalances create a self-reinforcing loop that elevates the close and then reverses, amplifying volatility and transferring wealth from retail holders. The loop is captured by the scalar ℓ = ΛcK, the product of price impact and rebalancing capital, which governs how much the closing print is distorted. In the Korean episode the loop added roughly 47 percentage points of annualized volatility to SK Hynix and transferred about KRW 3.96 trillion to holders of the affected products over eight weeks, with the effects concentrated at the reference print and unwinding overnight. Korea’s regulators proposed remedies that alter the reference mechanism (e.g., averaging across two prints) to damp the loop, a design shown to materially reduce both the price distortion and the toll in counterfactuals. The paper develops a formal model distinguishing anticipation from manipulation and demonstrates how the public-channel toll operates at any positive loop gain, while the private (manufacturing) channel depends on market depth and competition. [page::0][page::9][page::4][page::5][page::23]
Digital State Capacity (DSC) is defined as the ability of governments to deploy ICT infrastructure and information systems for administration, monitoring, enforcement, coordination, and service delivery. The paper introduces a registry-based measure based on public IPv4 address space held by government organisations, covering roughly 150,000 government-identified country-entity records across 150+ countries (2019–2024) with Admin-1 subnational granularity. Validation shows DSC correlates with existing state-capacity and digital-government indicators, yet remains distinct from them. Illustrative country-year analyses find that higher DSC is associated with lower perceived corruption and higher vaccination coverage, among other outcomes; however, these associations are descriptive, not causal, and reflect capacity rather than use. The measure expands analysis to subnational, functional, and agency-level dimensions, while acknowledging limitations such as IPv4 focus, IPv6 considerations, and historical data gaps. [page::1]
Automated market makers (AMMs) can be viewed as verifiable portfolio devices that enforce a target-weight mandate via the G3M invariant. The paper introduces a multi-asset fee structure that yields a band-rebalancing no-arbitrage region, enabling mandatemg compliance to be verified from observable pool holdings. Empirically, G3M portfolios are compared against VBIAX, EQL, and EDOW, showing dominance in certain fee ranges on both annualized returns and tracking error. The findings suggest AMMs can operate as verifiable portfolio infrastructure beyond traditional liquidity provision [page::2][page::4][page::9].
ARBO-DART jointly optimizes day-ahead (DA) commitments and real-time (RT) recourse for standalone battery energy storage (BESS) by wrapping Bayesian optimization around a closed-loop RT solver with exogenous DA prices and a mean-reverting RT price process. It uses a blockwise, adaptive refinement of the DA profile guided by RT feedback, achieving substantial speedups (2–4x) over full-dimension BO while recovering economically meaningful DA schedules that leverage intraday price volatility [page::2][page::3][page::4]. ARBO-DART demonstrates robustness across price-curve shapes and DART spread structures and yields interpretable, parsimonious DA profiles with limited nonzero blocks that efficiently coordinate DA and RT actions [page::2][page::3][page::4].