The development of industrialization runs through the history of the People’s Republic of China. In the early years of the founding of the People’s Republic of China, the Soviet Union provided important help for China’s industrialization construction, capital lending, talent training and technology transfer. By analyzing the proportion of China’s industrial output value in the total output value and the output of major industrial products during the period of the Soviet Union, it shows that the assistance of the Soviet Union had a very positive role in promoting the realization of ChinaIs industrialization, and helped China to lay the foundation of industrialization. In addition, some problems in accepting the Soviet Union’s aid to China also deserve our attention when promoting the new industrialization. The research explores both the internal and external factors that led to China’s acceptance of Soviet assistance. The study examines the political, economic, and historical contexts that created a favorable environment for such aid, analyzes the various modes and scales of the assistance implemented, and presents statistical data that underscore the transformative social and economic achievements derived from this partnership. Furthermore, the paper highlights the contributions of quantitative analyses in understanding the aid’s impact, discusses the experiences and lessons learned from the Soviet aid period, and assesses the evolving dynamics of Sino—Soviet relations, particularly the gradual divergence in economic development models. The findings shed light on how Soviet aid laid the groundwork for China’s industrialization while also foreshadowing future ideological and developmental separations.

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.

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.

The global financial system is currently navigating a profound transformation driven by digitalization and the rise of decentralized financial innovations. In response, central banks are increasingly exploring or implementing Central Bank Digital Currencies (CBDCs) as a sovereign digital evolution of fiat money. This study investigates the dual nature of CBDCs, evaluating whether they represent a strategic opportunity to modernize the economy or a systemic threat to existing financial stability. Employing a qualitative methodology, the research analyzes official policy frameworks from the IMF and BIS alongside diverse real-world case studies, including China’s e-CNY, the Bahamas’ Sand Dollar, Nigeria’s eNaira, and the European Central Bank’s Digital Euro. The findings suggest that while CBDCs offer significant benefits—such as enhanced payment efficiency, reduced transaction costs, and improved financial inclusion—they also introduce critical risks. These include the potential disintermediation of commercial banks, heightened cybersecurity vulnerabilities, and concerns regarding individual data privacy and government surveillance. The study concludes that the successful integration of CBDCs is not merely a technical challenge but a social and strategic one. Adoption is heavily dependent on infrastructure, digital literacy, and public trust. Ultimately, the research highlights that there is no "one-size-fits-all" model; the future of money will be shaped by how effectively individual nations balance technological innovation with the preservation of financial architecture.

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.

We examine the relationship between government data opening and corporate leverage manipulation. Leveraging the staggered establishment of province-level open government data platforms in China as a quasi-natural experiment, we find that government data opening significantly reduces corporate leverage manipulation. This policy effect is more pronounced among firms with low capital intensity, firms with limited analyst coverage, and those located in regions with low banking competition. Mechanism analysis suggests that government data opening affects the cost-benefit tradeoff of corporate leverage manipulation by alleviating financing constraints and enhancing corporate governance, thereby mitigating leverage manipulation practices. Our research contributes to the literature on government data opening, highlighting its role in reducing leverage manipulation and offering valuable implications for mitigating significant financial risks.

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.

Partially convertible economies face a market-design problem: trade integration, cross-border investment, and domestic balance-sheet exposure increase the demand for currency hedging before full financial integration is complete. China adopted a distinctive architecture for this problem by fostering a deliverable offshore Renminbi market (CNH) alongside the segmented onshore market (CNY), rather than relying only on non-deliverable forwards. This creates two venues for closely related claims on the same currency. Spot prices are tightly linked, yet CNY and CNH forwards display a persistent and economically large discrepancy. We study that discrepancy in a joint equilibrium model for spot and forward trading with transaction costs and segmented supply. In the benchmark case with common constant supply and deterministic costs, spot parity implies a forward differential with the wrong sign relative to the data. Random offshore stress, modeled as a jump in trading costs, overturns this benchmark while preserving tight spot parity. The model yields a semi-explicit representation in the CNY/CNH application and a calibration of the observed forward discrepancy in terms of the market-implied likelihood and severity of offshore liquidity stress.

This study investigates how the interaction of political accountability and local officials’ career incentives shapes the market for Municipal Corporate Bonds (MCBs) in China, taking the 2017 local government debt personal responsibility rule as a quasinatural experiment. We develop a stylized incomplete-information bargaining model to analyze how the rule reshapes the bargaining equilibrium by rendering officials’ observable characteristics credible signals of bailout incentives. Using a dataset of prefecture-level MCBs from 2008 to 2020, we empirically test the model’s predictions and focus on separating officials’ incentive effects from their inherent ability. Our core findings show that post-announcement of the rule, each additional year of a local party secretary’s remaining time to retirement, a proxy for bailout incentives, reduces MCB spreads by approximately 2.5 basis points and increases issuance volume by about 2.0%. These effects are significantly amplified in fiscally stressed cities. Notably, under the 2017 rule, cities led by party secretaries with stronger bailout incentives can expand MCB issuance, which is contrary to the rule’s original intent to rein in local borrowing.