Fintech and AI in Business

The efficient processing of payments is crucial in transaction systems, particularly in those reliant on key cryptocurrencies like Bitcoin (BTC). However, the decentralized nature of these systems, coupled with the algorithmic incentives and competition among multiple cryptocurrencies for miners, poses significant challenges in analyzing transaction speed ... 閱讀更多

The integration of algorithmic trading with reinforcement learning, termed AI-powered trading, is transforming financial markets by reshaping how trading works. This study constructs a theoretical laboratory where financial markets function as information aggregation mechanisms, compelling investors to trade cautiously on private signals to preserve ... 閱讀更多

We develop FinBERT, a state-of-the-art large language model that adapts to the finance domain. We show that FinBERT incorporates finance knowledge and can better summarize contextual information in financial texts. Using a sample of researcher-labeled sentences from analyst reports, we document that FinBERT substantially outperforms the Loughran and McDonald ... 閱讀更多

We examine the evolutionary effects of sentiment words in financial text and their implications for various business outcomes. We propose an algorithm called Word List Vector for Sentiment (WOLVES) that leverages both a human-defined sentiment word list and the word embedding approach to quantify text sentiment over time. We then apply WOLVES to investigate ... 閱讀更多

一家公司披露重要的公司資訊之後，分析師們通常會及時地對所披露的內容發佈追蹤報告。一項新的研究已經證實，這些報告對投資者而言具有重要的作用，因為它們對公司管理人員的聲明進行解釋、豐富和確認。 由黃昊，Reuven Lehavy，臧蘊智和鄭嶸所做的這項研究，使用了一種演算法模型來分析討論的語言和主題，這些討論與公司電話會議談話中的季度收入，以及分析師對這些通話內容做出的報告相關，之後分析師們會對投資者的回應進行觀察。他們的資料集包括標準普爾500強公司從2003年至2012年的17,750次電話會議和159,210份有關這些電話會議的分析報告。 作者發現，分析師扮演了投資者高度重視的兩個關鍵角色。一方面，他們是資訊發現的代理人，通過私人研究，例如與公司高層和中層管理人員的私人互動，收集了與這家公司相關的資訊 ... 閱讀更多