第七届智能金融国际会议议程发布，

邀您参会！

【会议背景】

智能金融（Smart Finance）是数据驱动技术（人工智能、区块链、大数据分析和数据科学）与新金融（加密货币、众筹、供应链金融和电子支付）交叉领域的研究和开发。智能金融国际会议（ICSF）的目标是为相关领域的专家学者和行业领袖提供一个高水平的交流平台，促进理论创新与实践创新，推动产、学、研深度融合。ICSF曾在广州、深圳、北京、北戴河等多个城市举办。今年，会议将由香港大学经管学院的数字经济与创新研究所和金融创新及发展研究中心联办并于线上举行。

主办单位

港大经管学院数字经济与创新研究所

港大经管学院金融创新及发展研究中心

时间

2022年8月19日 08:40 至 17:40

2022年8月20日 09:00 至 16:40

参会方式

线上以Zoom进行

【会议亮点】

主题演讲

The Effects of News Media Type and

News (Re)distribution on Information Efficiency

of the Financial Market

Professor Bin Gu

Everett W. Lord Distinguished Faculty Scholar,Professor and Department Chair of Information Systems at the Questrom School of Business,Boston University

In this paper, we investigate the differential effect of traditional news media and online-only news media on firm-specific information diffusion in the financial market. We distinguish original news distribution from news redistribution in our analysis. Using news and stock data from the Chinese stock market, we find that original news distribution on both traditional news media and online-only news media has a significant and positive impact on information efficiency of the stock market. The positive effect is stronger for online-only news media. We also find that news redistribution on both types of news media is not conducive to information efficiency of the stock market. The negative effect is stronger for online-only news media. Further, we find that selectivity in news redistribution can mitigate the negative impact of redistribution. The effect is stronger for online-only news media. Our finding suggests that original news creation and distribution by online-only news media shall be encouraged while caution and selectivity need to be exercised in news redistribution.

Investing in Lending Technology:

IT Spending in Banking

Professor Zhiguo He

Fuji Bank and Heller Professor of Financeand Jeuck Faculty Fellow,Booth School of Business, University of Chicago

This paper studies the economics behind the investment in information technologies (IT) by U.S. commercial banks in the past decade. By linking banks\' IT spending to their lending technologies, we analyze the distinctive natures of banks\' dealings with information across various lending activities. Investment in communication IT is shown to be associated more with improving banks\' ability of soft information production and transmission, while investment in software IT helps enhance banks\' hard information processing capacity. We exploit polices that affect geographic regions differentially to show causally that banks respond to an increased demand for small business credit (mortgage refinance) by increasing their spending on communication (software) IT spending. We also find that the entry of fintech induces commercial banks to increase their investment in IT -- more so in the software IT category.

Media Sentiments,

Investor Behaviors

and Stock Price Plunges

Professor Fan Wang

Assistant President of

Sun Yat-sen University

In order to explore the impact of negative media reports of listed companies oninvestor behaviors and stock prices, we use natural language processing method to classify risks in negative media reports into five categories and construct a comprehensive negative media sentiment index. We find that negative media reports contain objective negative information and subjective sentiment. Negative information can cause stock prices to decline in the short term but cannot predict them in the long term, which is consistent with theories of media content as a proxy for new information about fundamental asset values. Moreover, repeated media reports will arouse investors\' strong attention and high pessimism, which will cause investors to overreact and cause stock prices to crash.

Revealed Wisdom of the Crowd:

Predictive Value of Bids

Professor D. J. Wu

Ernest Scheller Jr. Chair in Innovation,Entrepreneurship and Commercialization, Professor of IT Management, Scheller College of Business, Georgia Institute ofTechnology

Despite the popularity of the phrase "wisdom of the crowd," not all crowds are wise because not everyone in a crowd acts in an informed, rational manner. Identifying informative actions, therefore, can help to isolate the truly "wise" part of a crowd. Motivated by this idea, we evaluate the informational value of investors\' bids using data from online, debt-based crowdfunding, where we were able to track not only investment decisions, but also the ultimate repayment status, for specific loans. We propose several easily-scalable variables based on the heterogeneity of investors\' bids interms of their size and timing. We first show that loans funded with large bids (compared to the typical bid amount in the market, or relative to an individual investor\'s historical baseline), especially those receiving large bids early in the bidding process, are less likely to default. More importantly, incorporating these variables improves the predictive performance of state-of-the-art models that have been proposed for this context. Even during the fundraising process, these variables improve the predictive performance of funding likelihood and loan quality. We discuss the implications of these variables, including loan pricing in secondary markets, crowd wisdom under different market mechanisms, and financial inclusion. Platforms can easily implement these variables to improve market efficiency without compromising investor privacy.

The Big Tech Lending Model

Professor Wei Xiong

Trumbull-Adams Professor of Finance and Professor of Economics, Princeton University;Academic Dean of School of Management and Economics, Chinese University of Hong Kong, Shenzhen

By comparing uncollateralized business loans made by a big tech lending program with conventional bank loans, we find that big tech loans tend to be smaller and have higher interest rates and that borrowers of big tech loans tend to repay far before maturity and borrow more frequently. These patterns remain forborrowers with access to bank credit. Our findings highlight the big tech lender\'s roles in serving borrowers\' short-term liquidity rather than their long-term financing needs. Through this model, big tech lending facilitates credit to borrowers underserved by banks without experiencing more-severe adverse selection or incurring greater risks than banks (even during the COVID-19 crisis).

圆桌论坛

Security Token Offering (STO) asSubstitute or Prelude of IPO:Opportunities and Challenges

主持：

Professor Leon Zhao

Chinese University of Hong Kong, Shenzhen

Professor Juan (Jane) Feng

Tsinghua University

Dr. Guangzhi Shang

Florida State University

Dr. Paul K. H. Sin

New World Development

Dr. Pengfei Sui

Chinese University of HongKong, Shenzhen

Security Token Offering (STO) is a new financial approach for companies to acquire funding for product and service innovation. STO is different from ICO because the former requires asset backup while the latter does not, thus STO is fundamentally different from ICO in terms of financial valuation and risks. STO has been viewed by many as the digital version of IPO since both IPO and STO are identical in their objective and effect. Most recently, a Chinese company called Trucpal is going for STO with US$20,000,000.00 via INX, a Cryptocurrency Trading Platform & Digital Securities in the US. Trucpal is the first Chinese company to do STO in the US, signaling the birth of a new phase in digital finance and raising tons of questions for people to ponder with. In this panel, we will discuss the impacts, opportunities, and challenges for Chinese companies to explore with STO. Sample questions we will discuss include, but not limited to:

Could Chinese companies in the Greater Bay Area start thinking about doing STO in the US,HK, or Singapore, given that Trucpal is already doing it in the US?

What are potential theoretical and practical benefits and risks of taking STO instead of IPO as a new financial innovation?

How should Chinese companies interpret the Hong Kong regulations on STO? What might be the future opportunities of doing STO in Hong Kong?

Supply Chain Finance &

Blockchain Technology

(以普通话进行)

主持：

Dr. Alvin Leung

City University of Hong Kong

Dr. Sheng He

Kingdee International Software Group Co., Ltd

Professor Jiewu Leng

Guangdong University of Technology

Professor Jian Li

Beijing University of Technology

Dr. Leo Yeung

OpenText

Connecting buyers and sellers with financial institutions, supply chain finance (SCF) plays an important role in local and cross-border trading. SCF covers a wide spectrum of services which include payment and collection, risk mitigation, trade finance, verification of client identity (a.k.a., know-your-customer procedure), and cash management and projection. The advancement of blockchain technology facilitates industrial monitoring and information distribution. Financial assets such as equity, bonds, and fund shares, can be combined and stored in blockchain blocks; smart contracts can automate transactions and enable pre-shipment SCF. In 2020, blockchain in SCF market size was valued at USD 245.41 million, which is expected to reach USD 6,853 million in 2028 with a compounded annual growth rate (CAGR) of 51.62%. In this panel discussion, we shall explore the market of SCF and discuss opportunities and challenges posed by blockchain technology. Sample questions we shall discuss include, but are not limited to:

What is the outlook of SCF in the time of pandemic outbreak?

How do blockchain and Internet of Things (IoT) technologies facilitate SCF?

What are the prospects of blockchain in the global SCF market?

编辑：梁萍