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Xin Wang Assistant Professor Division of Banking & Finance Nanyang Business School Nanyang Technological University Contact: Email: xin.wang [AT] ntu.edu.sg Address: S3-B1B-60, 50 Nanyang Ave, Singapore 639798 Phone: +65-6790-5706 Research Interests: Market Microstructure, Financial Intermediation, Macro-Finance and FinTech Curriculum Vitae (June 2020) |
Xin Wang joined Nanyang Business School in NTU as an Assistant Professor of Banking & Finance division in 2018. His research interests are in the areas of theoretical and empirical Market Microstructures, Financial Intermediation, Macro-Finance, and FinTech. His current research looks at how recent financial technology innovations affect trading in the secondary market, existing intermediaries of credit, and the transmission of monetary policy. He received his Ph.D. degree from the University of Illinois at Urbana-Champaign.
Publications
Forthcoming, Journal of Financial Economics
2nd SAFE Market Microstructure Conference (Goethe University Frankfurt), 2018 Stern Microstructure Conference, 11th Financial Risks International Forum (Paris), 2018 NTU Finance Conference, 2018 Front Range Finance Seminar*, UCLA Anderson*, Telfer Annual Conference on Accounting and Finance 2018*, University of Florida*, University of Rochester*, Carlson Junior Conference at the University of Minnesota*, Wabash River Conference at the Indiana University*, Smokey Mountain Conference* (* indicates presentation by co-author)
Abstract: We model competition for liquidity provision between high-frequency traders (HFTs) and slower execution algorithms (EAs) designed to minimize investors’ transaction costs. Under continuous pricing, EAs dominate liquidity provision by using aggressive limit orders to stimulate HFTs’ market orders. Under discrete pricing, HFTs dominate liquidity provision if the bid-ask spread is binding at one tick. If the tick size (minimum price variation) is not binding, EAs choose between stimulating HFTs and providing liquidity to non-HFTs. Transaction costs increase with the tick size but can be negatively correlated with the bid-ask spread when all traders can provide liquidity.
Working Papers
EFA 2018, Finance Down Under 2018, 16th Annual International Industrial Organization Conference
Abstract: This paper shows that a key driver of stock exchanges' competition on order-processing speeds is the Order Protection Rule, which requires an exchange to route its customers' orders to other exchanges with better prices. Faster exchanges attract more price-improving limit orders because the probability of being bypassed by trades with inferior prices on other exchanges is reduced. When all exchanges speed up, the bypassing probability can increase, potentially harming the welfare of investors. In contrast, increasing connection speeds between exchanges raise investor welfare by reducing the bypassing probability. Nevertheless, no exchange wants to improve connection speeds because this will reduce its trading volume. I provide empirical evidence supporting these predictions. Overall, my findings suggest that exchanges do not necessarily compete on liquidity-enhancing dimensions.
Abstract: To reduce high-frequency trader’s speed advantage, new stock exchange designs such as frequent batch auctions and several order delay designs have been proposed to slow down trading speed and eliminate the speed arms race among high-frequency traders. In this paper, I investigate how newly designed exchanges with these ‘speed bump’ features would compete against traditional exchanges. I find that among order delay proposals, the most effective design is to delay only liquidity taking orders as proposed by the Chicago Stock Exchange. Frequent batch auctions are shown not to improve liquidity when the degree of private information is high enough. Moreover, when frequent batch auctions are implemented, exchanges have incentives to compete on the frequency at which batch auctions take place. Finally, I show that even when sniping is a significant problem for some stocks, exchanges with large market share of total trading volume may lack incentives to implement frequent batch auctions or order delays even when these innovative designs could improve long-term investor welfare. Therefore, the interests of exchanges may not be aligned with those of long-term investors with regard to how they value designs that alleviate sniping.
Work in Progress
Teaching
Publications
- Who Provides Liquidity, and When? with Mao Ye and Sida Li
Forthcoming, Journal of Financial Economics
2nd SAFE Market Microstructure Conference (Goethe University Frankfurt), 2018 Stern Microstructure Conference, 11th Financial Risks International Forum (Paris), 2018 NTU Finance Conference, 2018 Front Range Finance Seminar*, UCLA Anderson*, Telfer Annual Conference on Accounting and Finance 2018*, University of Florida*, University of Rochester*, Carlson Junior Conference at the University of Minnesota*, Wabash River Conference at the Indiana University*, Smokey Mountain Conference* (* indicates presentation by co-author)
Abstract: We model competition for liquidity provision between high-frequency traders (HFTs) and slower execution algorithms (EAs) designed to minimize investors’ transaction costs. Under continuous pricing, EAs dominate liquidity provision by using aggressive limit orders to stimulate HFTs’ market orders. Under discrete pricing, HFTs dominate liquidity provision if the bid-ask spread is binding at one tick. If the tick size (minimum price variation) is not binding, EAs choose between stimulating HFTs and providing liquidity to non-HFTs. Transaction costs increase with the tick size but can be negatively correlated with the bid-ask spread when all traders can provide liquidity.
Working Papers
EFA 2018, Finance Down Under 2018, 16th Annual International Industrial Organization Conference
Abstract: This paper shows that a key driver of stock exchanges' competition on order-processing speeds is the Order Protection Rule, which requires an exchange to route its customers' orders to other exchanges with better prices. Faster exchanges attract more price-improving limit orders because the probability of being bypassed by trades with inferior prices on other exchanges is reduced. When all exchanges speed up, the bypassing probability can increase, potentially harming the welfare of investors. In contrast, increasing connection speeds between exchanges raise investor welfare by reducing the bypassing probability. Nevertheless, no exchange wants to improve connection speeds because this will reduce its trading volume. I provide empirical evidence supporting these predictions. Overall, my findings suggest that exchanges do not necessarily compete on liquidity-enhancing dimensions.
- Can Stock Exchanges with 'Speed Bump' Designs Survive?
Abstract: To reduce high-frequency trader’s speed advantage, new stock exchange designs such as frequent batch auctions and several order delay designs have been proposed to slow down trading speed and eliminate the speed arms race among high-frequency traders. In this paper, I investigate how newly designed exchanges with these ‘speed bump’ features would compete against traditional exchanges. I find that among order delay proposals, the most effective design is to delay only liquidity taking orders as proposed by the Chicago Stock Exchange. Frequent batch auctions are shown not to improve liquidity when the degree of private information is high enough. Moreover, when frequent batch auctions are implemented, exchanges have incentives to compete on the frequency at which batch auctions take place. Finally, I show that even when sniping is a significant problem for some stocks, exchanges with large market share of total trading volume may lack incentives to implement frequent batch auctions or order delays even when these innovative designs could improve long-term investor welfare. Therefore, the interests of exchanges may not be aligned with those of long-term investors with regard to how they value designs that alleviate sniping.
Work in Progress
- Would Mandated Pre-Trade Price Transparency Improve Liquidity in Corporate Bond Markets? with Dan Bernhardt
- Can Stock Exchanges be Allowed to Choose Their Tick Size? With Mao Ye
- Are Stock Markets Rigged from Slow National Best Bid and Offer Price? With Dan Bernhardt and Yashar Barardehi
Teaching
- Financial Economics (Investments) at the University of Illinois at Urbana-Champaign Fall 2015-Spring 2017