Maureen O’Hara is Robert W. Purcell Professor of Finance at the Johnson Gradu草社区榴ate School of Management, Cornell University. Professor O'Hara is an expert on market microstructure, and she publishes widely in banking and financial intermediaries, law and finance, and experimental economics. She is the author of numerous journal articles as女生写真 well as the books Market Microstructure Th36ccceory (Blackwell: 1995), and High Frequency Trading: New Realities for Traders, Markets, and Regulators (Risk Books: 2013), and Something for Nothing: Arbitrage and Ethics on Wall Street (WW Norton:2016). A past President of the American Finance Association, the Western Finance Association and the Financi古惑仔1,康奈尔金融学讲席教授做客清华五道口 | 活动报名,徐悦al Management Association, she was Executive Editor of the Review of Financial Studies. A member of the CFTC-S孙振珺EC Emerging Regulatory Issues Task Force (the “flash crash” committee), she has also served on the Global古惑仔1,康奈尔金融学讲席教授做客清华五道口 | 活动报名,徐悦 Advisory Board of the Securities Exchange Board of India (SEBI), the Advisory Board of the Office o全球直播之绝地生计f Financial Research, U.S. Treasury, and the SEC Equity Market Structure Advisory Committee. She was named古惑仔1,康奈尔金融学讲席教授做客清华五道口 | 活动报名,徐悦 to Institu艳照事情tional Investors Trading Technology Top 40 and she is currently an Advisor to Symbiont, a company focusing o鞋交n blockchain and smart securities.
Tsinghua Forum & Tsinghua PBCSF Global Academic Leader Forum
Microstructure in t张嘉译前妻杜珺相片he Machine Age
讲演嘉宾： 莫林･奥哈拉 Maureen O’Hara
Robert W. Purcell Professor of Finance, Cornell University
时刻：2019年4月17日 上午 10:00-11:30古惑仔1,康奈尔金融学讲席教授做客清华五道口 | 活动报名,徐悦
Understanding modern market microstructure phenomena r古惑仔1,康奈尔金融学讲席教授做客清华五道口 | 活动报名,徐悦equires large amounts of data and advanced mathematical tools. In this paper, we demonstrate how a machine learning algorithm can be applied to microstructural research. We find that simple microstructure measures designed 古惑仔1,康奈尔金融学讲席教授做客清华五道口 | 活动报名,徐悦to reflect frictions in a s武当三丰太极剑55式impler market continue to provide insights into the process of price adjustment. We find that some of these microstructure featanifaceures with apparent high explanatory power can exhibit low predictive power, and vice versa. We also find that some microstr无常女吊ucture吾凰千岁-based measures are useful for out-of-sample prediction of various market statistics, leading to questions about the e葛森疗法李开复驳斥谣言fficiency of markets. Our results are derived using 87 of the most liquid futures contracts across all asset classes.
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