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.

This article views the economic development history of New China as a history of openness and constant adjustment. We examine China’s economic development and early open policies from 1953 to 1978, analyze how the nation navigated between planned and open economic models during the formative period. Through a comprehensive review ofthe key Chinese and Western scholarship, investigates major initiatives including the Soviet-assisted 156 Projects, First Five-Year Plan, The policy of Eight Characters and the later “Four Three Plan” of the Western engagement. The study highlights both achievements and challenges, particularly in industrial growth and technology transfer, while assessing the impact of critical events like the Sino-Soviet split. Statistical analysis and quantitative models demonstrate how these early experiments with economic openness, despite ideological constraints and operational difficulties, established crucial institutional and technological foundations for China’s subsequent reform and modernization. The findings offer valuable insights into China’s unique development path and its implications for emerging economies.

We study whether commodity risk is efficiently priced in the cross-section of US equities. We first provide novel evidence on firm-level risk exposure to up to 42 individual commodities. We then construct a mispricing measure as the realized return less the commodity-risk-implied return, and find that it strongly predicts next-month return reversal beyond the traditional short-term reversal. This commodity-risk-mispricing reversal is substantially stronger among small, less analyst- or media-covered stocks, is weakly associated with investor sentiment, and is less prevalent among firms that engage in commodity hedging. In particular, underpricing among these hedgers often remains persistent and even intensifies after the 2004 financialization of commodity markets. This implies that despite the overall decline in mispricing, financialization has likely introduced more costs than benefits for corporate risk management.

This paper examines the intricate relationship between China’s First Five-Year Plan (1953–1957) and the extensive Soviet aid that played a pivotal role in shaping early industrialization and economic policy in New China. Drawing upon both Chinese and Western literature, the study reviews the evolution of planned economy practices and Soviet economic assistance, analyzes the process of plan formulation and the formulation of key industrial targets, and assesses the quantitative and qualitative impact of Soviet aid on the successful implementation of the plan. By employing a multi-perspective literature review, archival research, and statistical data analysis, the paper identifies that Soviet technology, machinery, and planning expertise contributed significantly, estimates suggest that Soviet aid accounted for 30-40% of the capital inputs in key sectors and that this collaboration was instrumental in achieving heavy industry targets before the advent of reform and opening-up policies. Furthermore, the paper explores the subsequent divergence in the economic models of China and the Soviet Union, offering lessons on dependency, technology transfer, and the political dimensions of foreign aid. The findings not only contribute to our understanding of the early stages of China’s economic development but also shed light on the broader dynamics of Cold War-era international economic cooperation.

Under China’s transition toward high-quality financial development, this study investigates the tail dependence among media sentiment, investor attention, and stock market returns using the M-Clayton Copula. Comparative model fitting tests demonstrate that the M-Clayton Copula outperforms both single Copula models and M-Copula models in characterizing asymmetric negative dependence structures. It is particularly effective in capturing both upper-lower and lower-upper tail dependencies, thereby providing a more comprehensive analysis of their interdependencies. The empirical results reveal three key findings. First, a significant positive tail dependence exists between media sentiment and stock market returns, suggesting that they tend to move together under extreme conditions, with notable asymmetry in the strength of co-movements. Second, media sentiment and investor attention exhibit negative tail dependence, with the lower-upper tail dependence coefficient exceeding its upper-lower counterpart, suggesting higher probability of rising investor attention following media sentiment decline than vice versa. Third, a pronounced negative tail dependence emerges between stock market returns and investor attention, particularly showing strong lower-upper tail correlation, implying substantial likelihood of increased investor attention subsequent to market downturns.

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.

This paper studies whether and how policies that promote a currency’s use in trade invoicing can also strengthen its role as an anchor currency in other economies’ exchange rate baskets. We exploit the establishment of RMB swap lines by the People’s Bank of China as a natural setting to examine this mechanism. We first estimate countries’ implicit currency baskets and the weights assigned to the RMB, and then use a staggered difference-in-differences design to assess the effect of initiating swap line agreements on the RMB’s weights in these baskets. Our results indicate that RMB weights increase by approximately 5% about nine months after a swap line is introduced and remain persistently higher thereafter. Finally, we develop a three-country DSGE model to interpret these findings, showing that by promoting RMB invoicing, swap lines reinforce the RMB’s role as an anchor currency for exchange rate stabilization.

The robustness of the securities market is a necessary condition for ensuring the stable operation of the financial market, and stock price fluctuations have always been a major concern for academia and investors. One of the main influencing factors of stock price fluctuations is macroeconomic monetary policy. As one of the important control tools of macroeconomic monetary policy, the impact of benchmark interest rates on stock price fluctuations cannot be ignored. This paper takes Chinese A-shares as the research object, analyzes the impact of benchmark interest rate changes on stock price fluctuations, and further introduces investor sentiment as a mediating variable to analyze its role in the transmission process of monetary policy. This paper selects monthly data of Chinese A-share listed companies from 2018 to 2024 and conducts empirical tests by constructing direct effect models and mediating effect models. The research results show that: First, benchmark interest rates have a significant negative impact on stock price fluctuations; second, benchmark interest rates can indirectly affect stock price fluctuations by influencing investor sentiment, with investor sentiment playing a partial mediating role. The research conclusions of this paper help to deepen the understanding of the transmission mechanism of monetary policy's impact on securities prices, and provide micro-evidence for monetary policymakers to assess the impact of policy adjustments on capital market stability, while also providing a reference for investors to understand the risk characteristics of the securities market under changes in the interest rate environment.

This paper revisits two widely studied predictors of commodity futures returns, basis and basis momentum, whose conventional measures using first-nearby futures as proxies for spot prices may limit their ability to capture fundamental spot-market risks. Motivated by this limitation, we construct two spot-based signals from observed spot and futures prices, which are theoretically shown to contain incremental information beyond conventional measures. Using 41 Chinese commodity futures, we find that these signals robustly predict first-nearby contract returns and remain significantly priced in time-series and cross-sectional tests, even after controlling for their conventional counterparts. We then develop a spot-enhanced three-factor model, including the market factor and the two spot-based factors, which consistently outperforms three widely used benchmark models in pricing competing factors and explaining return anomalies.

Technology firms are often financed on narratives about products, contracts, customers, and technological progress well before these developments appear in accounting statements. We ask when such narratives become economically informative. Our central idea is that narratives should matter more once they can be linked to later verifiable outcomes rather than treated as stand-alone text.Using listed Chinese technology firms, we develop a validated corporate narrative framework for bank-affiliated investment, a setting in which investors must screen with soft information ex ante and then monitor hard realization and downside risk ex post. We use GPT-5.1 to extract business claims from management discussion, investor-relations records, exchange Q&A, and earnings-roadshow materials, and to label later claim–evidence pairs as support, partial support, conflict, duplicate, or irrelevant. We then connect these labels to official announcements, procurement awards, permits, project updates, and negative-event disclosures to construct a validated firm-month signal. The broad merged panel contains 592 firms and 30,169 firm-month observations; the main return tests use 576 firms and 18,230 firm-month observations over 2022–2024. A simple production rule that combines a low-narrative-premium component with hard-narrative and hard-event anchors, together with a separate downside-risk gate, delivers an implementable annualized long-short return of 8.93% in bank-invested firms after trading costs. The signal is much weaker in non-bank firms, predicts future gross-margin improvement more strongly than future ROE, and improves downside screening.