SME-SFI 学术讲座预告 20260309 - 20260316

掰直风暴

来源：深圳高等金融研究院
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套利者参与下的颗粒化国库券需求
: }5 B% F9 ]9 gGranular Treasury Demand with Arbitrageurs
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讲座信息
主讲人
Kristy Jansen 教授
" c1 a7 q7 g- u7 k6 x( Q; v南加州大学
日期和时间
2026年3月13日（周五）
: L( |9 o+ N0 ~0 Y8 Z2 @, ~10:30-12:00
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综合教学楼D904会议室
+ U1 e9 A) h  P, y讲座概述
# L( k! q- ^3 P8 k, {1 vWe construct a novel dataset of sector-level U.S. Treasury holdings, covering the majority of the market. Using this dataset, we estimate maturity-specific demand functions and elasticities of different investors and the Fed, and integrate them into a dynamic equilibrium model of the Treasury market with risk-averse arbitrageurs. Quantifying the model reveals that (1) there is a steep downward-sloping term structure of Treasury market elasticity; (2) monetary tightening raises term premia due to arbitrageurs interacting with investors exhibiting high cross-elasticities; (3) QE has limited impact unless the Fed credibly commits to sustained balance sheet expansion.
Keywords: Treasury demand; financial intermediaries; arbitrage; monetary policy; quantitative easing.
主讲人简介
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Kristy Jansen 教授
5 b0 ^& }$ o$ H$ Y8 _南加州大学
6 N6 o: |3 U3 U! Q9 m9 m4 M3 sKristy Jansen 现任南加州大学马歇尔商学院金融与商业经济学助理教授，同时担任欧洲经济政策研究中心研究员，并为荷兰中央银行的外部研究员。她的研究方向主要集中于非银行金融中介、资产定价以及宏观金融，重点探讨机构投资者资产需求的驱动因素及其在金融市场中的作用机制。其近期研究的核心主题之一是分析资产需求以及政策与监管干预如何影响美国及全球国债市场的动态演变。此外，她还将养老金基金作为重要的机构投资者类型进行研究，系统考察现金约束加剧如何影响其投资行为，并进一步反馈至整体金融市场结果。
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% ]: J* h1 [) U" a5 Z0 T平衡竞争环境：
  r& u1 V" f, i生成性人工智能对中小企业的影响
, }# [2 v$ o( I* E' o8 b! @7 DLeveling the Playing Field:
The Effect of Generative AI on Small and Medium-Sized Firms

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# ]( w/ L/ M) W' z9 u/ L# n' F讲座信息
主讲人
% W+ D1 r2 m" d% P袁哲博士
% U$ A; [" Z7 {1 I浙江大学
; I2 K7 \5 V* @" O9 j  ]+ Y日期和时间
8 {& T% \7 ?! \2026年3月13日（周五）
10:30-12:00
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8 B) r9 f; T7 q1 F& E综合教学楼D504会议室
讲座概述
4 c+ {3 r; L5 K' i' Y& TThis paper examines whether platform-enabled AI tools can enable small firms to narrow the capability gap with larger incumbents in digital marketplaces. We study the staggered adoption of an AI tool — automated content generation and data analytics — launched in April 2024 on a leading Chinese e-commerce platform. Leveraging a proprietary firm-level panel of over 4.9 million firm-month observations from October 2023 to July 2025, we combine propensity score matching with difference-in-differences estimation across twelve adoption cohorts. We find that AI adoption increases average sales by 69.9%, driven primarily by a 63.2% rise in order volume, with broad improvements across discoverability, quality, and innovation. These gains are sharply heterogeneous by firm size: bottom-quartile firms experience 75.8% sales growth — nearly four times the 19.9% gain of top-quartile firms — with disproportionate improvements in other dimensions of firm performance. Mechanism analyses reveal that AI reduces labor costs, alleviates information asymmetries, and facilitates skill acquisition, with all three effects concentrated among smaller firms. Results are robust to instrumental variable, staggered DiD, and synthetic DiD approaches. Overall, the evidence suggests that when made accessible with low adoption costs, AI can narrow pre-existing capability gaps rather than exacerbate them, fostering upward mobility among small firms and enhancing market dynamism.
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袁哲博士
2 [1 }* W  p$ ~  }3 c9 o4 W! r浙江大学
袁哲博士，浙江大学经济学院百人计划研究员、博士生导师。先后在北京大学获得学士学位、多伦多大学获得博士学位，并在哈佛大学与威斯康辛大学开展学术访问。他的研究专注于产业组织和数字经济，主要关注人工智能的经济学（消费者行为、数据价值与隐私、劳动与企业生产力、商业增长以及算法歧视）、平台治理（信息设计、搜索与推荐系统以及平台机制设计）和网络行业（航空、网约车和电信网络）。其研究成果发表于《Rand Journal of Economics》、《American Economic Journal: Microeconomics》、《Management SCIence》、《Information Systems Research》、《Manufacturing & Service Operations Management》等国际顶级经济管理类期刊。他同时担任《Decision Science》副主编。
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基于利润与价格数据的匹配博弈估计
Estimating Matching Games with Profit and Price Data
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主讲人
唐勋教授
莱斯大学
日期和时间
( k' |) c/ l! X. p/ v2026年3月16日（周一）
10:30-12:00
地点
综合教学楼D904会议室
$ e2 K- v9 G0 z7 r) g讲座概述
  \- u3 H7 }2 j6 C! P7 GEmpirical methods for transferable-utility matching games have previously been developed using the matches formed in equilibrium. We explore identification and estimation of match surplus and agent valuation using two additional sources of data from such matching games: monetary transfers (prices) and profits of the match parties. We provide identification and estimation results for nonparametric and semiparametric models. Importantly, our results and estimators allow agents to have valuations defined over the unmeasured characteristics of potential partners. We apply our method to estimate the matching surplus and individual valuations from CEOs and listed companies, taking into account both measured and unmeasured characteristics on both sides.
主讲人简介


唐勋教授
莱斯大学
唐勋博士现任美国莱斯大学经济系 Henry S. Fox Sr. 经济学讲席教授。他于2008年获美国西北大学经济学博士学位，曾任宾夕法尼亚大学助理教授。唐勋博士的研究领域包括计量经济学与产业组织理论，其研究重点是在存在或不存在战略性互动的情形下，对经济主体行为进行结构化与非结构化分析。