学术论文
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Does Liquidity Management Induce Fragility in Treasury Prices? Evidence from Bond Mutual Funds
Does Liquidity Management Induce Fragility in Treasury Prices? Evidence from Bond Mutual Funds
Mutual funds investing in illiquid corporate bonds actively manage Treasury positions to buffer redemption shocks. This liquidity management practice can transmit non-fundamental fund flow shocks onto Treasuries, generating excess return volatility. Consistent with this hypothesis, we find that Treasury excess return volatility is positively associated with bond fund ownership, and this pattern is more pronounced among funds conducting intensive liquidity management. Causal evidence is provided by exploiting the U.S. Securities and Exchange Commission’s 2017 Liquidity Risk Management Rule. Evidence also suggests that the COVID-19 Treasury market turmoil was attributed to intensified liquidity management, an unintended consequence of the 2017 Liquidity Risk Management Rule.

The Interactions of Customer Reviews and Price and Their Dual Roles in Conveying Quality Information
The Interactions of Customer Reviews and Price and Their Dual Roles in Conveying Quality Information
Customer reviews help communicate product information, but their effectiveness may suffer from selection bias (i.e., depending on factors, such as the individual experience and price, not all consumers may voluntarily write reviews). Consequently, a seller may have to resort to additional means (e.g., signaling through price in the context of an experience good) to convey its quality. This paper develops an analytical model to investigate the interaction of customer reviews and price with the presence of selection bias in marketing an experience good with uncertain quality to consumers. Our analysis reveals the dual roles played by both customer reviews and price in communicating quality information. On one hand, customer reviews may either directly convey product information with unbiased distribution of reviews or facilitate price signaling when reviews are biased because of selection. On the other hand, price may be adjusted to mitigate the selection bias of reviews to make them more informative, and it may also signal quality directly in the presence of review bias. As a result, we show that bias in reviews may actually benefit consumers without compromising information communication as the incentive to reduce review selection bias makes it credible and profitable for the high-quality seller to signal its type by undercutting the price that would be set if it is of low quality. We then extend our analysis to examine the information, profits, and welfare impacts of several important design elements of a review system as well as the impact of consumers’ aversion to risk. Finally, the implications of our findings on the management of user-generated content and pricing are discussed.

Manipulation, Panic Runs, and the Short Selling Ban
Manipulation, Panic Runs, and the Short Selling Ban
Short selling regulation has been a longstanding topic of debate in financial markets, particularly during times of crisis. While proponents argue that short selling aids in price discovery and market efficiency, critics raise concerns about manipulative short selling practices that can destabilize markets. This paper presents a theoretical model to analyze the impact of short selling, specifically manipulative short selling (MSS), on bank runs and efficiency. The model demonstrates that MSS can emerge as an equilibrium outcome driven by uninformed speculators seeking to profit from artificially depressing stock prices. The prevalence of MSS is influenced by the level of informed trading and coordination friction among creditors. We find that short selling bans can enhance welfare by mitigating the negative effects of MSS, particularly in scenarios with high coordination frictions. We also provide policy and empirical implications.

Corporate Lobbying of Bureaucrats
Corporate Lobbying of Bureaucrats
Executive agencies play a pivotal role in shaping the regulatory environment by crafting rules, enforcing regulations, and overseeing government contracts—all of which can have a profound impact on businesses. For firms, this potential impact creates a clear incentive for firms to influence these agencies, particularly during the critical stages of rulemaking and enforcement. In this context, lobbying emerges as a key tool that companies use to mold the regulatory landscape to their advantage. Unlike politicians, whose decisions are often swayed by electoral cycles and campaign contributions, agency officials are not elected, serve longer terms, and are less susceptible to direct political pressures. As a result, engaging in lobbying efforts with executive agencies is both more complicated and strategically crucial for firms operating within heavily regulated industries. However, the dynamics of such lobbying remain underexplored in the literature.
春节幸福感和疫情感知风险调查:来自机器学习的洞察
春节幸福感和疫情感知风险调查:来自机器学习的洞察
2023年刚结束的兔年春节内地民众过得怎样?调查显示,兔年春节期间,民众的幸福感平均值为5.47,介于“比较开心”与“开心”之间(1为最低值,7为最高值),“比较开心”以上人群占比为83.1%。
How to Recover from Work Stress, According to Science
How to Recover from Work Stress, According to Science
To combat stress and burnout, employers are increasingly offering benefits like virtual mental health support, spontaneous days or even weeks off, meeting-free days, and flexible work scheduling. Despite these efforts and the increasing number of employees buying into the importance of wellness, the effort is lost if you don’t actually recover. So, if you feel like you’re burning out, what works when it comes to recovering from stress? The authors discuss the “recovery paradox” — that when our bodies and minds need to recover and reset the most, we’re the least likely and able to do something about it — and present five research-backed strategies for recovering from stress at work.

研究企业之间的协调行为 – 郝宇博士
研究企业之间的协调行为 – 郝宇博士
计算机编程听起来好像和经济风马牛不相及,但拥有出色的编程技术,不但能帮助个人进行经济学学术研究,更能助你在商界捉紧更多就业机会。

构想虚拟货币的未来 – 游杨博士
构想虚拟货币的未来 – 游杨博士
作为教师,在鼓励同学努力学习之余,我亦会主动了解本地市场运作以及邀请雇主来到课堂分享业界经验。

从量子物理学到计量市场学—党矗博士
从量子物理学到计量市场学—党矗博士
理科出身的我,非常欣赏同学们的商业触觉。作为他们的师长,在教导他们使用数理工具作出科学判断的同时,我亦希望能够鼓励他们爱上学习,保持对未知事物的好奇心,应用课堂所学到的知识为社会做出贡献。

AI加速时代下的量化基本面投资
AI加速时代下的量化基本面投资
Quantamental investing—a strategy that melds traditional fundamental analysis with data-intensive quantitative methods—has surged in popularity over the past decade. Today, it stands on the cusp of a transformative era: advanced AI models, once prohibitively expensive, are becoming more capable, affordable, and widespread. This technological leap is poised to redefine how we identify and exploit market inefficiencies. Imagine a team of tireless, ever-alert junior analysts who can analyze millions of corporate filings, news articles, and social media chatter in seconds—that's essentially what these next-generation AI systems offer.
超级80/20法则: AI时代下知识创作
超级80/20法则: AI时代下知识创作
19世纪末,经济学家维尔弗雷多·帕累托(Vilfredo Pareto)观察到意大利80%的财富集中在20%的人手中。这一现象后来被美国管理学者约瑟夫·朱兰(Joseph Juran)进一步发展,推论出著名的“80/20法则”:80%的结果(输出)往往归于20%的投入(输入)。
破解拼车盈利难题:绿色出行背后的网络效应与策略选择
破解拼车盈利难题:绿色出行背后的网络效应与策略选择
随着科技和网络发展,拼车服务势必向自动化及智能化方向迈进。笔者透过研究不同定价模式和匹配机制,为网约车平台建议提升拼车盈利的策略。
大国人工智能竞技场上的激战
大国人工智能竞技场上的激战
美国OpenAI 公司自2022 年推出ChatGPT以来,就一直雄踞生成式人工智能(Generative AI )市场领导地位。AI 创新领域早已成为兵家必争之地,美国为了限制中国在此一领域的发展,禁止高端晶片出口中国,并限制中国用户使用ChatGPT,香港用户因而需透过虚拟专用网络( VPN )才能使用。2024 年,中国一间初创公司推出了深度求索(DeepSeek)生成式AI模型,却彻底扭转局势,剑指ChatGPT 的霸主宝座。
特朗普高关税反噬北美汽车产业链
特朗普高关税反噬北美汽车产业链
美国总统特朗普近期宣布对加拿大和墨西哥进口商品大幅加征关税,汽车及零部件税率更高达25%。此举据称旨在促进美国制造业回流,同时减少贸易逆差,但实际上却可能引发一连串深远的负面影响。
打造卓越数据分析团队的方略
打造卓越数据分析团队的方略
在大数据与人工智能深度融合的今天,数据已成为企业发展的核心资产。随着人工智能技术的不断突破与广泛应用,数据的价值上升至前所未有的高度,几乎所有企业都致力于利用数据分析来获取有价值的商业洞见。
大国人工智能竞技场上的激战
大国人工智能竞技场上的激战
美国OpenAI 公司自2022 年推出ChatGPT以来,就一直雄踞生成式人工智能(Generative AI )市场领导地位。AI 创新领域早已成为兵家必争之地,美国为了限制中国在此一领域的发展,禁止高端晶片出口中国,并限制中国用户使用ChatGPT,香港用户因而需透过虚拟专用网络( VPN )才能使用。2024 年,中国一间初创公司推出了深度求索(DeepSeek)生成式AI模型,却彻底扭转局势,剑指ChatGPT 的霸主宝座。
特朗普高关税反噬北美汽车产业链
特朗普高关税反噬北美汽车产业链
美国总统特朗普近期宣布对加拿大和墨西哥进口商品大幅加征关税,汽车及零部件税率更高达25%。此举据称旨在促进美国制造业回流,同时减少贸易逆差,但实际上却可能引发一连串深远的负面影响。
AI加速时代下的量化基本面投资
AI加速时代下的量化基本面投资
Quantamental investing—a strategy that melds traditional fundamental analysis with data-intensive quantitative methods—has surged in popularity over the past decade. Today, it stands on the cusp of a transformative era: advanced AI models, once prohibitively expensive, are becoming more capable, affordable, and widespread. This technological leap is poised to redefine how we identify and exploit market inefficiencies. Imagine a team of tireless, ever-alert junior analysts who can analyze millions of corporate filings, news articles, and social media chatter in seconds—that's essentially what these next-generation AI systems offer.