The emphasis on environmental sustainability outcomes (ESO) in emerging economies has increased recently, requiring in-depth research to manage the complex interplay between socioeconomic and sociopolitical factors. With a particular focus on China, this study describes this significant relationship using a good technique that comprises standardized questionnaires administered to a large sample of different organizational levels. This research examined several factors and their effects on ESO. First, the results show that the kind of economic system (EST) directly affects ESO; no direct relationship was discovered between ESO and the industrialization level (LI). Furthermore, it was demonstrated that government funding for eco-sustainability projects (GFESP) and community engagement and eco-education initiatives (CEEEI) had a direct impact on ESO. Secondly, the results demonstrated that implementing eco-policies and regulations (IEPR) had a full mediating effect between EST and ESO. Third, political instability (PI) and corruption level (CL), which are essentially the outcome of China's current political and environmental issues, diminish the correlation between EST and ESO. These findings demonstrate that China's environmental sustainability has to be improved using a multimodal approach. The public is encouraged to push legislators to bolster eco-laws and policies in order to emphasize environmental preservation. Initiatives to reduce corruption and maintain political stability may also bolster the beneficial effects of economic frameworks on ESO.

Taking China’s environmental “fee-to-tax” reform as a quasi-natural experiment, this paper employs a difference-in-differences (DID) approach to examine the impact of the green tax reform on firms’ cost of equity on a sample of A-share listed firms from 2012 to 2023. The results show that the implementation of the Environmental Protection Tax Law significantly reduced the cost of equity for heavily polluting firms. This finding remains robust after a series of robustness checks. Analyses of the underlying mechanisms reveal that the green tax reform lowered the cost of equity primarily through the channel of “Porter effect.” Moreover, the effect is more pronounced among firms located in the eastern China, those with stronger internal governance, and those operating in a stricter external monitoring environment.

This paper investigates the outstanding economic and scientific-technological achievements of the Soviet Union during the 1945–1953 period and analyzes how these successes influenced New China’s decision to adopt the Soviet development model. Drawing upon a review of the key Chinese studies and the influential Western works, this study synthesizes diverse research methods,including historical institutional analysis, archival research, and econometric modeling, to examine the driving forces behind Soviet economic development, its quantitative achievements, and its evolving international status relative to the United States. Moreover, the paper reviews the development of Sino-Soviet relations during both the Kuomintang era and the early years of the People’s Republic of China, and it provides a comprehensive factor analysis of why New China chose to introduce the “Soviet model.” The paper also discusses recent quantitative research that employs statistical models to assess the impact of Soviet achievements on China’s economic planning. The findings underscore that the rapid reconstruction and modernization of the Soviet economy not only set new benchmarks in industrial output and scientific progress but also provided a persuasive example that shaped China’s early development strategy.

Firm characteristics help estimate conditional factor loadings. Larger libraries contain new and overlapping information. We use the cross-sectional distribution of firm characteristics as a ruler to evaluate IPCA loading spaces. With factor counts fixed, expanding from 36 to 153 characteristics can improve in-sample fit while representing momentum and size positions less fully. Reallocating shared exposures changes attribution without changing joint fitted returns. With coefficients fixed, exposure references alter holdings, trading, and subsequent risk at the same characteristic target. Statistical factor models should be evaluated not only by return fit, but also by the exposures they represent and the investment decisions they support.

Traditional portfolio optimization typically relies on a single fitted return distribution, thus ignores non-normality and uncertainty across distributional states. Mean–variance–ambiguity (MVA) models, motivated by the smooth-ambiguity preferences of Klibanoff, Marinacci, and Mukerji (2005) and the KMM-to-MVA Arrow–Pratt reduction of Maccheroni, Marinacci, and Ruffino (2013), extend conventional risk penalties to account for distributional uncertainty, but they missed how state-conditional return distributions affect portfolio optimization stability. We develop Deep Mean–Variance–Ambiguity (Deep MVA) to resolve this gap by learning state-conditional return distributions and embedding the resulting conditional information loss into the ambiguity penalty. The resulting local certainty equivalent combines reduced-law mean–variance risk with a quadratic penalty for second-order disagreement. Conditional-mixture state resolution yields a Deep ambiguity covariance equal to the Traditional ambiguity covariance plus a positive-semidefinite state-feature increment. This increment is the conditional L2 loss from averaging state-specific distributions before optimization. On compact convex feasible sets, we show that the state-resolving program has stronger ambiguity-relevant curvature, lower mean-input sensitivity, and a unique global solution under restricted positive curvature or a common ridge; its projected iterations converge linearly. An LSTM-MDN learns state-conditional distribution densities from 60-minute bars, and Probability and VoV scores enter weekly MVA, with GARCH_Resid as a comparator. Tests on the SSE 50, CSI 300, and CSI 500 universes from 2017–2025 find statistically significant Sharpe out-of-sample improvements over Traditional MVA and MVO across all three universes and ambiguity specifications.

This study investigates the relationship between the number of stock concepts and future returns, as well as the economic mechanisms underlying this association. Using novel collected data, we find that stocks with a greater number of concepts earn significantly higher returns in the subsequent month, generating a six-factor adjusted annualized alpha of approximately 9.6% for a long-short portfolio. Although these stocks exhibit higher turnover, return volatility, and investor attention - features commonly associated with speculative concept-driven trading - an analysis of cross-listed AH twin stocks reveals that concept counts do not widen the AH premium. Moreover, the return premium persists for up to 15 months without significant reversal, whereas firms that engage in opportunistic concept-chasing exhibit pronounced long-run reversals, suggesting that the positive concept-return relation is not driven by speculative motives. The higher returns are primarily attributable to strong industrial policy support and sustained above-expectation operating performance. Firms with more concepts are more likely to receive government subsidies and deliver positive earnings surprises, effects that are amplified when their core concepts receive stronger national policy backing. In contrast, firms that pursue concepts lacking substantive business relevance are significantly less likely to obtain government subsidies and fail to achieve above-expectation growth. Regarding investor composition, institutional ownership of high-concept stocks increases modestly, while ownership by government-guided funds rises substantially - particularly for stocks whose core concepts are strongly supported by national industrial policies. Conversely, concept-chasing behavior by listed firms significantly reduces the ownership ratio of government-guided funds. Overall, our findings indicate that concept stocks in China’s capital market are not purely speculative but signal underlying national policies.

This paper examines whether subjective macroeconomic expectations predict equity risk premia in China. Using professional macro forecasts from the Wind database over 2011- 2023, we construct a composite macroeconomic expectation index via PLS. We find that the index significantly and positively predicts future equity premia both in-sample and out-ofsample, implying a countercyclical equity premium. The predictive power is robust to a wide range of macro-financial controls and delivers economically meaningful gains in portfolio allocation. Further analysis shows that controlling for forecast errors does not attenuate predictability, and the subjective index largely subsumes the information in realized macro variables, suggesting that it captures forward-looking macroeconomic conditions rather than belief bias. Cross-sectional and long-horizon results reinforce this interpretation.

On October 10, 2025, Bitcoin fell 9.1% in thirty minutes on Binance following a geopolitical shock, contributing to a 16.0% peak-to-trough drawdown over 33 hours. Using minute-level Binance and Bybit data across spot, perpetual futures, and mark price feeds for BTC, ETH, and SOL, this paper situates the event within an empirical distribution of 62 BTC drawdowns exceeding 3% over 30 minutes during 2024–2026. October 10 ranks first of 62 on every microstructure metric simultaneously: a SOL futures-spot drawdown gap of 11.0 percentage points (z = +7.65), a BTC basis swing of $1,367 (z = +6.18), and a mark to-spot undershoot of $2,507 (z = −4.21). It also ranks first on multivariate anomaly measures (Mahalanobis distance 7.70; sum of absolute z-scores 45.9, 2.4 times the runner-up). A parsimonious conceptual cascade model identifies the mark price oracle as the crypto-specific amplifier.

Firms frequently overstate digital transformation in public disclosures while committing less in observable investment, a phenomenon known as digital catering. We examine whether digital public financial infrastructure can discipline such symbolic behavior. Using a staggered difference-in-differences design on Chinese A-share listed firms over 2014--2024, we find that exposure to China's e-CNY pilot reduces digital catering by roughly 14% relative to the sample mean. The decline is driven almost entirely by reduced rhetorical digital transformation, while balance-sheet-based digital commitment rises only marginally: the e-CNY pilot is associated with substantially less digital talk, but not with a commensurate increase in digital walk in the short run. The effect operates through lower agency costs and reduced information asymmetry, and follows an amplification--substitution pattern---stronger among digital-sector and accounting-opaque firms, weaker where internal controls and institutional ownership are already strong. The evidence identifies financial-transaction verifiability as a novel source of discipline over corporate cheap talk: CBDC-related infrastructure constrains unsupported symbolic claims without immediately accelerating substantive digital investment.

Against the backdrop of systemic financial risk prevention and the pursuit of a virtuous cycle in the real economy, whether Local Government Financing Vehicles (LGFVs) shareholding alleviates maturity mismatch of corporate investment and financing activities is a question of critical importance, not only for the development of individual firms but also for high-quality macroeconomic growth. Using a sample of A-share listed firms in China’s Shanghai and Shenzhen stock exchanges from 2009 to 2021, this paper theoretically analyzes and empirically tests the impact of LGFVs shareholding on corporate maturity mismatch. The empirical results indicate that LGFVs shareholding can significantly alleviate corporate maturity mismatch and the finding is still robust across a series of empirical checks. Mechanism analyses show that LGFVs shareholding improves firms’ long-term financing capacity through a resource provision channel and restrains overinvestment through a governance optimization channel, thereby collectively mitigating corporate maturity mismatch. Further analysis indicates that the mitigating effect of LGFVs shareholding is more pronounced in firms with concentrated LGFVs shareholding, firms controlled by non-state-owned capital and firms under higher economic policy uncertainty. Our findings provide valuable theoretical insights for policy design aimed at optimizing corporate financial behavior and curbing corporate financial risks.