<paper_abstract>This paper revisits the calendar–vertical–basket (CVB) consistency problem for finite call quotes under bounded bid–ask spreads, correcting a sign mis-specification between printed and executable bids and showing that even after base and one-maturity conditions, sufficiency fails in a minimal two-date setting due to a stock-flip arbitrage. It provides an explicit two-date counterexample panel for any ϵ>0, proves minimality, and derives a closed-form two-date basket operator via a convex-envelope representation that characterizes the model-independent arbitrage cone. The result implies robust hedging and no-arbitrage tests must rely on more than a finite list of CVBs. [page::1]
In 2019, a fire at a natural gas plant and historically low temperatures caused an emergency shortage of natural gas in Michigan. A statewide emergency text alert asked households to turn thermostats down to 65◦F. We analyze the effectiveness of this request using high-frequency smart-thermostat data from Michigan and four neighboring states. Using a difference-in-differences research design, we find that Michigan households reduced thermostat settings by 1.1 degrees on average. Our results suggest that the use of the wireless emergency alert system was critical in creating an effective emergency response. We examine heterogeneity in responsiveness by whether a household’s baseline thermostat setting was above or below the compliance target of 65◦F and by Democratic Party gubernatorial vote share. [page::0]
Benchmark macroeconomic models require additional frictions to explain the sluggish response of aggregate variables to shocks. Cai shows that standard heterogeneous-agent (HA) models—the Blanchard (1985) perpetual youth and Bewley (1986) incomplete markets models—can replicate observed aggregate consumption inertia without habit formation or any specific expectation underreaction model. He achieves this by directly substituting survey expectations of income and interest rates into a semi-structural HA framework and by embedding an unobserved components model of expectations into a tractable HA equilibrium. Inertia arises when expectations imperfectly account for the equilibrium amplification of shocks, which is large in HA economies, causing beliefs to gradually unanchor as agents misattribute large equilibrium responses to larger shocks. The analysis also shows that inertial monetary policy rules and delayed fiscal financing induce longer transmission lags. Core mechanisms include a belief multiplier χ, the role of extrapolation biases in survey expectations, and the endogenous amplification of shocks through heterogeneous-agent dynamics. The paper provides a unified evaluation of impulse-response evidence and policy counterfactuals, highlighting when gradual policy worsens stabilization under learning frictions and how delayed deficits interact with expectation dynamics [page::0][page::1][page::2][page::3].
This work proposes a minimal, non-linear exponential random graph model (fit2SM) that can reproduce both the first and second moments of empirical degree distributions within a canonical framework [page::0]. By replacing linear two-star constraints with fitness-induced components, the model avoids the degeneracy of the mean-field two-star approach and successfully matches the sample variance of degree distributions [page::3][page::4]. Empirical validation on the eMID interbank network across daily to yearly aggregations shows that fit2SM outperforms the traditional UBCM and the density-corrected gravity model (dcGM) in reproducing variance, degree sequence, and spectral properties, particularly in sparser configurations [page::2][page::5][page::17]. Moreover, when treated as a generative model, fit2SM supports robust early-warning signal analyses, aligning well with ground-truth indicators even when the true topology is not available [page::8].
This article introduces an unconventional model for price processes in finance that emerges from the classical Heston model under Mechkov’s ‘fast-reversion limit’. This new fast-excursion Heston model exhibits instantaneous (i.e. fast) ‘excursions’ through an interval of prices at each time, which are invisible to vanilla options but critical for hitting probabilities and continuously monitored exotics. Theoretically, the model provides a rare example of a non-degenerate limit of stochastic volatility models that escapes the Skorokhod topologies. This leads to a class of interval-valued processes which exist as lifts of subordinated Lévy processes, through the concept of selections in the theory of random closed sets. On the practical side, we show how the model can be simulated using price-time parametric representations, and utilise a purpose-built classical Heston simulation scheme in order to visualise convergence. Finally we demonstrate how this model raises hitting probabilities for barrier options considerably (of order 10% for one-month EURUSD options), due to taking ‘excursion risk’ into account. [page::0]
This paper shows that the complexity of multi-attribute preferences and the language used to report them critically shape the performance of strategy-proof assignment mechanisms [page::21]. The authors find that lexicographic (LEX) reporting yields the highest accuracy across treatments, while additive (SEP) and non-separable (COMP) structures reduce reporting accuracy with no robust difference between SEP and COMP [page::21][page::22]. Under direct serial dictatorship (SD-DIRECT), misreporting rises compared with a non-allocative accuracy benchmark (ACCURACY), indicating incentive- and framing-driven reporting frictions beyond mere list length [page::25]. Attribute-based simplifications (SD-LEX, SD-WEIGHT) do not improve accuracy relative to full ranking, due to substantial representational losses that offset any burden reduction; however, sequential choice (SD-CHOICE) achieves the highest accuracy and the lowest efficiency loss and justified envy, with part of its advantage attributable to menu reduction and part to strategy-proofness and simpler decision framing [page::27][page::28][page::30][page::32][page::34]. The findings imply that reducing the length of a report alone is not sufficient and that menu-pruning or staged/dynamic designs can meaningfully improve allocation outcomes [page::38].
This work introduces K-line–Quantile Sequential Projection (KQSP), a parameter-free, training-free reconciliation method that enforces both quantile monotonicity and OHLC consistency for probabilistic K-line forecasts (OHLC). KQSP operates in two sequential stages (K-line projection followed by quantile projection) and is model-agnostic, requiring no retraining or extra hyperparameters. Empirical results across an ANN and eight zero-shot foundation models show KQSP reduces both quantile crossing and K-line crossing to zero without degrading predictive accuracy, and often improves metrics such as Average Quantile Loss (AQL), MAE, and RMSE. Comparisons with multiple baselines indicate KQSP achieves equivalent or better correction performance while applying smaller adjustments to the original forecasts. The method demonstrates robustness across architectures and forecast sources, highlighting that probabilistic K-line consistency can be achieved independently of the underlying forecast model [page::1][page::2][page::3].
本研究提出并测度一个新的团队层面潜在能力，称为注意力定向能力（ADA），用于描述团队成员通过日常互动信号（如提及、第一直接互动、引导性信息等）引发下游参与与协同响应的效率差异。以OpenCovid19全球协作为研究场景，覆盖2,233名参与者、79个自组织团队、165个Slack频道以及超过3万条信息，通过分布滞后模型估计行动-反应之间的因果关系，并以主成分/探索性因子分析提取单一ADA分数。结果表明：ADA是一个稳定的潜在能力，与团队是否提交提案及提交后的评审分数显著相关；在对提交进行选择性校正后，ADA对提交概率和评审分数的正向影响仍然显著。进一步的因果中介分析显示，ADA通过提升整体沟通努力（信息量）来推动产出，表明 ADA 是一个上游的协调能力，能够将微观信号转化为持续的集体投入与进展。这些发现扩展了对集体注意力与团队协作的理解，强调互动信号的结构性响应性而非单纯的注意力量。 [page::0]
