549 lines
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549 lines
40 KiB
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<div class="navbar">
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<a href="#home">Home</a>
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<a href="#teaching">Teaching</a>
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<a href="#research">Research</a>
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<a href="#service">Service</a>
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<div class="main" id="home">
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<p> </p><br>
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</div>
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<h1>YANG, Chen</h1>
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<td class="isPrint" width="160"><img src="ME.jpeg" width="150"></td>
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<td>
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Associate Professor <br>
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<a class="extlink" href="http://www.se.cuhk.edu.hk" target="_blank">Department of Systems Engineering and
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Engineering Management</a> <br>
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<a class="extlink" href="https://www.erg.cuhk.edu.hk/erg/">Faculty of Engineering</a> <br>
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The Chinese University of Hong Kong <br><br>
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<i class="fas fa-map-marker-alt"></i>
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<span class="links"> </span>Room 511A, William M.W. Mong Engineering Building <br>
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<span class="links"> </span>The Chinese University of Hong Kong <br>
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<span class="links"> </span>Shatin, N.T., Hong Kong<br>
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<i class="fas fa-envelope"></i> cyang at se.cuhk.edu.hk <br>
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<i class="fas fa-phone-alt"></i> +852 3943-8322 <br>
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</div>
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<br><br>
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<hr id="teaching" class="style-one">
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<p>
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<h3>Teaching <br> <a id="blackboard" class="extlink" href="https://blackboard.cuhk.edu.hk" target="_blank">[Blackboard@CUHK]</a></h3>
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Undergraduate Courses
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<ul class="notATable">
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<li><label><b>Spring 2020-2025 </b></label>
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<div>SEEM3580 Risk Analysis for Financial Engineering</div>
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</li>
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<li><label><b>Fall 2019-2025 </b></label>
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<div>SEEM3590 Investment Science</div>
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</li>
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</ul>
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Postgraduate Courses
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<ul class="notATable">
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<li><label><b> Spring 2025 </b></label>
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<div>SEEM5410 Optimal Control</div>
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</li>
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<li><label><b> Spring 2023 </b></label>
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<div>SEEM5670 Advanced Models in Financial Engineering</div>
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</li>
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<li><label><b> Fall 2021 </b></label>
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<div>SEEM5340 Stochastic Calculus</div>
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</li>
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</ul>
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</p>
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<hr id="research" class="style-one">
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<p>
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<h3>Research Interest</h3>
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<ul style="list-style-type:square">
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<li> Portfolio Selection </li>
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<li> Market Frictions and Microstructure (Capital Gains Tax, Price Impact, Transaction Costs) </li>
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<li> FinTech (Decentralized Exchanges, Stablecoins, DeFi Lending) </li>
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<li> Stochastic Control </li>
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</ul>
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</p>
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<hr class="style-one">
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<p>
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<h3>Selected Publications</h3>
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<ol>
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<li>Arbitrage on Decentralized Exchanges (with <a class="authorlink" href="https://sites.google.com/site/xuedonghepage/home"
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target="_blank">Xuedong He</a> and <a class="authorlink" href="https://hk.linkedin.com/in/yutian-zhou-555870189" target="_blank">Yutian Zhou</a>).<br>
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Working Paper. <span class="links">[<a class="paperlink" href="" onclick="toggleAbstract('abs_arbDEX');return false">Abstract</a>|<a class="paperlink"
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5347630" target="_blank">SSRN</a>|<a class="paperlink" href="https://arxiv.org/abs/2507.08302" target="_blank">arXiv</a>]</span><br>
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<div class="fade-in" style="display:none" id="abs_arbDEX">
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<hr>
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Decentralized exchanges (DEXs) are alternative venues to centralized exchanges (CEXs) for trading
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cryptocurrencies and have become increasingly popular. An arbitrage opportunity arises when
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the exchange rate of two cryptocurrencies in a DEX differs from that in a CEX. Arbitrageurs can then
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trade on the DEX and CEX to make a profit. Trading on the DEX incurs a gas fee, which determines the
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priority of the trade being executed. We study a gas-fee competition game between two arbitrageurs
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who maximize their expected profit from trading. We derive the unique symmetric mixed Nash
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equilibrium and find that (i) the arbitrageurs may choose not to trade when the arbitrage
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opportunity is small; (ii) the probability of the arbitrageurs choosing a higher gas fee is lower;
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(iii) the arbitrageurs pay a higher gas fee and trade more when the arbitrage opportunity becomes
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larger and when liquidity becomes higher. The above findings are consistent with our empirical
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study.
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</div>
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</li><br>
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<li>Periodic Evaluation with Non-Concave Utility (with <a class="authorlink"
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href="https://scholar.google.com/citations?user=OzeF8T0AAAAJ&hl" target="_blank">Cong Qin</a> and <a class="authorlink"
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href="https://www.ma.ic.ac.uk/~hz/"> Harry Zheng</a>).<br>
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<b>submitted</b>. <span class="links">[<a class="paperlink" href=""
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onclick="toggleAbstract('abs_periodicEvaluation');return false">Abstract</a>|<a class="paperlink"
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5305617" target="_blank">SSRN</a>]</span><br>
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<div class="fade-in" style="display:none" id="abs_periodicEvaluation">
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<hr>
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A fund manager's performance is often evaluated annually and compared with a benchmark, such as a
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market index. In addition, the manager may be subject to trading constraints, such as limited use of
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leverage, no short-selling, and a forced liquidation clause. We formulate this as a periodic
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evaluation problem with a non-concave utility, a stochastic reference point, and trading
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constraints. The value function is characterized as the unique solution to a Hamilton-Jacobi-Bellman
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equation with periodic terminal and boundary conditions, which must be imposed carefully due to
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possible discontinuities at the terminal time and/or on the liquidation boundary. We find that, at
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the evaluation time, future investment opportunities induce a discontinuity in the value function on
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the liquidation boundary, leading to a substantial change in local risk-aversion. More importantly,
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this local concavity/convexity weakens and shifts inward from the liquidation boundary to the
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interior region as the evaluation horizon increases. As a result, the joint effect of periodic
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evaluation and forced liquidation can generate highly nonlinear investment strategies, which is
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helpful in understanding the complexity of trading strategies in the loss region.
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</div>
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</li><br>
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<li>Pricing Model for Data Assets in Investment-Consumption Framework with Ambiguity (with <a class="authorlink"
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href="https://scholar.google.com/citations?user=os0TtfkAAAAJ&hl=en" target="_blank">Xiaoshan Chen</a>
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and <a class="authorlink" href="https://www.researchgate.net/profile/Zhou-Yang-9" target="_blank">Zhou Yang</a>).<br>
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<b>submitted</b>. <span class="links">[<a class="paperlink" href="" onclick="toggleAbstract('abs_dataAsset');return false">Abstract</a>|<a class="paperlink"
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5263455" target="_blank">SSRN</a>|<a class="paperlink"
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href="https://arxiv.org/abs/2505.16106" target="_blank">arXiv</a>]</span><br>
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<div class="fade-in" style="display:none" id="abs_dataAsset">
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<hr>
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Data assets are data commodities that have been processed, produced, priced, and traded based on
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actual demand. Reasonable pricing mechanism for data assets is essential for developing the data
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market and realizing their value. Most existing literature approaches data asset pricing from the
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seller's perspective, focusing on data properties and collection costs, however, research from the
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buyer's perspective remains scarce. This gap stems from the nature of data assets: their value lies
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not in direct revenue generation but in providing informational advantages that enable enhanced
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decision-making and excess returns. This paper addresses this gap by developing a pricing model
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based on the informational value of data assets from the buyer's perspective. We determine data
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asset prices through an implicit function derived from the value functions in two robust
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investment-consumption problems under ambiguity markets via indifference pricing principle. By the
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existing research results, we simplify the value function, using mathematical analysis and
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differential equation theory, we derive general expressions for data assets price and explore their
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properties under various conditions. Furthermore, we derive the explicit pricing formulas for
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specific scenarios and provide numerical illustration to describe how to use our pricing model.
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</div>
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</li><br>
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<li>Arbitrage in Perpetual Contracts (with <a class="authorlink" href="https://sites.google.com/view/mindai/home"
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target="_blank">Min Dai</a> and <a class="authorlink" href="https://sg.linkedin.com/in/linfeng-li-263843184" target="_blank">Linfeng Li</a>).<br>
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<b>submitted</b>. Updated: September 2025. <span class="links">[<a class="paperlink" href="" onclick="toggleAbstract('abs_arbPerp');return false">Abstract</a>|<a class="paperlink"
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5262988" target="_blank">SSRN</a>]</span><br>
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<div class="fade-in" style="display:none" id="abs_arbPerp">
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<hr>
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Perpetual contracts, designed to track the underlying price through a funding swap mechanism, have
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gained significant popularity in cryptocurrency markets. However, observed price discrepancies
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between perpetual contracts and the underlying asset cannot be explained solely by transaction fees.
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By examining the impact of the clamping function inherent in the funding swap mechanism -- an
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overlooked aspect in existing literature -- we derive model-free no-arbitrage bounds for perpetual
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contracts. Our findings reveal that these bounds persist as intervals even without transaction fees,
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due to the clamping function. Empirical analysis using two years of Binance data supports the
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validity of our proposed bounds.
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</div>
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</li><br>
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<li>Optimal Design of Automated Market Makers on Decentralized Exchanges (with <a class="authorlink"
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href="https://sites.google.com/site/xuedonghepage/home" target="_blank">Xuedong He</a> and <a class="authorlink" href="https://hk.linkedin.com/in/yutian-zhou-555870189" target="_blank">Yutian Zhou</a>).<br>
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<b>submitted</b>. <span class="links">[<a class="paperlink" href="" onclick="toggleAbstract('abs_AMM');return false">Abstract</a>|<a class="paperlink"
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4801468" target="_blank">SSRN</a>|<a class="paperlink"
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href="https://arxiv.org/abs/2404.13291" target="_blank">arXiv</a>]</span><br>
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<div class="fade-in" style="display:none" id="abs_AMM">
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<hr>
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Automated market makers are a popular mechanism used on decentralized exchange, through which users
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trade assets with each other directly and automatically through a liquidity pool and a fixed pricing
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function. The liquidity provider contributes to the liquidity pool by supplying assets to the pool,
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and in return, they earn trading fees from investors who trade in the pool. We propose a model of
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optimal liquidity provision in which a risk-averse liquidity provider decides the amount of wealth
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she would invest in the decentralized market to provide liquidity in a two-asset pool, trade in a
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centralized market, and consume in multiple periods. We derive the liquidity provider's optimal
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strategy and the optimal design of the automated market maker that maximizes the liquidity
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provider's utility. We find that the optimal unit trading fee increases in the volatility of the
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fundamental exchange rate of the two assets. We also find that the optimal pricing function is
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chosen to make the asset allocation in the liquidity pool efficient for the liquidity provider.
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</div>
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</li><br>
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<li>Calibration of Local Volatility Models under the Implied Volatility Criterion (with <a class="authorlink"
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href="https://scholar.google.com/citations?user=MbbX8kUAAAAJ&hl=en" target="_blank">Xinfu Chen</a>, <a class="authorlink"
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href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, and <a class="authorlink" href="https://www.researchgate.net/profile/Zhou-Yang-9" target="_blank">Zhou Yang</a>).<br>
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<b>submitted</b>. <span class="links">[<a class="paperlink" href="" onclick="toggleAbstract('abs_LocalVol');return false">Abstract</a>|<a class="paperlink"
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href=" https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4801520" target="_blank">SSRN</a>]</span><br>
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<div class="fade-in" style="display:none" id="abs_LocalVol">
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<hr>
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We study non-parametric calibration of local volatility models, which is formulated as an inverse
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problem of partial differential equations with Tikhonov regularization. In contrast to the existing
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literature minimizing the distance between theoretical and market prices of options as a calibration
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criterion, we instead minimize the distance between theoretical and market implied volatilities,
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complying with market practices. We prove that our calibration criterion naturally leads to the
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well-posedness of the calibration problem. In particular, comparing to Jiang and Tao (2001), we
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obtain a global uniqueness result, where no additional weight functions are required. Numerical
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results reveal that our method achieves a better trade-off between minimizing calibration errors and
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reducing overfitting.
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</div>
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</li><br>
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<li>Patience is a Virtue: Optimal Investment in the Presence of Market Resilience (with <a class="authorlink"
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href="https://www1.se.cuhk.edu.hk/~nchenweb/index.htm" target="_blank">Nan Chen</a>, <a class="authorlink"
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href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, and Qiheng Ding).<br>
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<b>submitted</b>. Updated: July 2025. <span class="links">[<a class="paperlink" href="" onclick="toggleAbstract('abs_LOB');return false">Abstract</a>|<a class="paperlink"
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4671774" target="_blank">SSRN</a>]</span><br>
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<div class="fade-in" style="display:none" id="abs_LOB">
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<hr>
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This paper investigates an optimal investment problem in an illiquid market, modeling explicitly the
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effects of three key features of market microstructure --- market tightness, market depth, and
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finite market resilience --- on the investor's decision. By employing a Bachelier process to model
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the dynamic of the fundamental value of the asset and assuming CARA-type utility for the investor,
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we obtain the investor's optimal dynamic trading strategy in closed form by solving the
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resulting high-dimensional singular control problem. Furthermore, we extend the model to incorporate
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return-predicting signals and utilize an asymptotic expansion approach to derive approximate optimal
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trading strategies. The theoretical and numerical results emphasize the vital role of patience.
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Specifically, rather than dispersing small trades continuously over time as advocated by the
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existing literature, our findings suggest that investors should strategically time their trading
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activities jointly based on market liquidity and market signal. To quantify this
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timing decision, we introduce a patience index that enables investors to strike a balance among
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various competing goals, including achieving currently optimal risk exposure, incorporating signals
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about future predictions, and minimizing trading costs, by leveraging market resilience. We also
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demonstrate how to implement our patient trading strategy using real-life market data.
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</div>
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</li><br>
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<li>Non-Concave Utility Maximization with Transaction Costs (with <a class="authorlink"
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href="https://sites.google.com/view/shuaijie-qian" target="_blank">Shuaijie Qian</a>).<br>
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<b>submitted</b>. <span class="links">[<a class="paperlink" href="" onclick="toggleAbstract('abs_NonconcaveTC');return false">Abstract</a>|<a class="paperlink"
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4500965" target="_blank">SSRN</a>|<a class="paperlink"
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href="https://arxiv.org/abs/2307.02178" target="_blank">arXiv</a>]</span><br>
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<div class="fade-in" style="display:none" id="abs_NonconcaveTC">
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<hr>
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This paper studies a finite-horizon portfolio selection problem with non-concave terminal utility and
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proportional transaction costs. The commonly used concavification principle for terminal value is no
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longer valid here, and we establish a proper theoretical characterization of this problem. We first
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give the asymptotic terminal behavior of the value function, which implies any transaction close to
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maturity only provides a marginal contribution to the utility. After that, the theoretical
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foundation is established in terms of a novel definition of the viscosity solution incorporating our
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asymptotic terminal condition. Via numerical analyses, we find that the introduction of transaction
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costs into non-concave utility maximization problems can prevent the portfolio from unbounded
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leverage and make a large short position in stock optimal despite a positive risk premium and
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symmetric transaction costs.
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</div>
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</li><br>
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<li>Optimal Tax-Timing with Transaction Costs (with <a class="authorlink" href="https://sites.google.com/view/mindai/home"
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target="_blank">Min Dai</a>, Yaoting Lei, and <a class="authorlink" href="http://apps.olin.wustl.edu/faculty/liuh/"
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target="blank">Hong Liu</a>).<br>
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<i><b>Management Science</b></i>, <i>Accepted for Publication</i>. <span class="links">[<a class="paperlink" href="" onclick="toggleAbstract('abs_TaxTC');return false">Abstract</a>|<a class="paperlink"
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4952040" target="_blank">SSRN</a>]</span><br>
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<div class="fade-in" style="display:none" id="abs_TaxTC">
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<hr>
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We develop a dynamic portfolio model incorporating capital gains tax (CGT), transaction costs, and
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year-end taxation. We find that even tiny transaction costs can lead to significant deferral of
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large losses and transaction costs affect loss deferrals much more than gain deferrals. Our model
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can thus help explain the puzzle that even when investors face equal long-term/short-term CGT rates,
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they may still defer realizing large capital losses for an extended period of time, displaying the
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disposition effect. In addition, we find misestimating transaction costs is costly. We also provide
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several unique, empirically testable predictions and shed light on recently proposed tax policy
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changes.
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</div>
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</li><br>
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<li>Designing Stablecoins (with <a class="authorlink" href="https://www.linkedin.com/in/yizhoucao/" target="_blank">Yizhou Cao</a>,
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<a class="authorlink" href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, <a class="authorlink"
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href="https://www.bu.edu/questrom/profile/steven-kou/" target="_blank">Steven Kou</a> and <a class="authorlink"
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href="https://www.linkedin.com/in/lewei-li/" target="_blank">Lewei Li</a>).<br>
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<i><b>Mathematical Finance</b></i>, 35(1):263-294, 2025. <span class="links">[<a class="paperlink" href=""
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onclick="toggleAbstract('abs_StableCoin');return false">Abstract</a>|<a class="paperlink"
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3856569" target="_blank">SSRN</a>|<a class="paperlink"
|
|
href="https://doi.org/10.1111/mafi.12445" target="_blank">Article</a>]</span><br>
|
|
<div class="fade-in" style="display:none" id="abs_StableCoin">
|
|
<hr>
|
|
Stable coins, which are cryptocurrencies pegged to other stable financial assets such as U.S. dollar,
|
|
are desirable for payments within blockchain networks, whereby being often called the “Holy Grail of
|
|
cryptocurrency.” However, existing cryptocurrencies are too volatile for these purposes. By using
|
|
the option pricing theory, we design several dual-class structures that offer a fixed income crypto
|
|
asset, a stable coin pegged to a traditional currency, and leveraged investment instruments. To
|
|
understand the impact of the proposed coins on the speculative and non-speculative demands of
|
|
cryptocurrencies, we study equilibrium with and without the stable coins. Our investigation of the
|
|
values of stable coins in presence of jump risk and black-swan type events shows the robustness of
|
|
the design.
|
|
</div>
|
|
</li><br>
|
|
|
|
<li>An Equilibrium Model for the Cross Section of Liquidity Premia (with <a class="authorlink"
|
|
href="https://wwwf.imperial.ac.uk/~jmuhleka/" target="_blank">Johannes Muhle-Karbe</a> and <a class="authorlink"
|
|
href="https://xf-shi.github.io" target="_blank">Xiaofei Shi</a>).<br>
|
|
<i><b>Mathematics of Operations Research</b></i>, 48(3):1423-1453, 2023. <span class="links">[<a class="paperlink" href=""
|
|
onclick="toggleAbstract('abs_LiqPre');return false">Abstract</a>|<a class="paperlink"
|
|
href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3738500" target="_blank">SSRN</a>|<a class="paperlink"
|
|
href="https://arxiv.org/abs/2011.13625" target="_blank">arXiv</a>|<a class="paperlink"
|
|
href="https://pubsonline.informs.org/doi/abs/10.1287/moor.2022.1307" target="_blank">Article</a>]</span><br>
|
|
<div class="fade-in" style="display:none" id="abs_LiqPre">
|
|
<hr>
|
|
We study a risk-sharing economy where an arbitrary number of heterogenous agents trades an arbitrary
|
|
number of risky assets subject to quadratic transaction costs. For linear state dynamics, the
|
|
forward-backward stochastic differential equations characterizing equilibrium asset prices and
|
|
trading strategies in this context reduce to a system of matrix-valued Riccati equations. We prove
|
|
the existence of a unique global solution and provide explicit asymptotic expansions that allow us
|
|
to approximate the corresponding equilibrium for small transaction costs. These tractable
|
|
approximation formulas make it feasible to calibrate the model to time series of prices and trading
|
|
volume, and to study the cross-section of liquidity premia earned by assets with higher and lower
|
|
trading costs. This is illustrated by an empirical case study.
|
|
</div>
|
|
</li><br>
|
|
|
|
<li>Leveraged Exchange-Traded Funds with Market Closure and Frictions (with <a class="authorlink"
|
|
href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, <a class="authorlink"
|
|
href="https://www.bu.edu/questrom/profile/steven-kou/" target="_blank">Steven Kou</a> and <a class="authorlink"
|
|
href="https://people.math.ethz.ch/~hmsoner/" target="blank">H. Mete Soner</a>).<br>
|
|
<i><b>Management Science</b></i>, 69(4):2517-2535, 2023. <span class="links">[<a class="paperlink" href=""
|
|
onclick="toggleAbstract('abs_LETF');return false">Abstract</a>|<a class="paperlink"
|
|
href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3856573" target="_blank">SSRN</a>|<a class="paperlink"
|
|
href="https://pubsonline.informs.org/doi/abs/10.1287/mnsc.2022.4407" target="_blank">Article</a>]</span><br>
|
|
<div class="fade-in" style="display:none" id="abs_LETF">
|
|
<hr>
|
|
Although leveraged ETFs are popular products for retail investors, how to hedge them poses a great
|
|
challenge to financial institutions. We develop an optimal rebalancing (hedging) model for leveraged
|
|
ETFs in a comprehensive setting, including overnight market closure and market frictions. The model
|
|
allows for an analytical optimal rebalancing strategy.
|
|
The result extends the principle of "aiming in front of target" introduced by <a class="paperlink"
|
|
href="https://onlinelibrary.wiley.com/doi/abs/10.1111/jofi.12080" target="_black">Gârleanu
|
|
and Pedersen (2013)</a> from a constant weight between current and future positions to a
|
|
time-varying weight, because the rebalancing performance is monitored only at discrete time points
|
|
but the rebalancing takes place continuously. Empirical findings and implications for the weekend
|
|
effect and the intraday trading volume are also presented.
|
|
</div>
|
|
</li><br>
|
|
|
|
<li>A Stochastic Representation for Nonlocal Parabolic PDEs with Applications (with <a class="authorlink"
|
|
href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a> and <a class="authorlink"
|
|
href="https://www.bu.edu/questrom/profile/steven-kou/" target="_blank">Steven Kou</a>).<br>
|
|
<i><b>Mathematics of Operations Research</b></i>, 47(3):1707-1730, 2022 <span class="links">[<a class="paperlink" href=""
|
|
onclick="toggleAbstract('abs_FK');return false">Abstract</a>|<a class="paperlink"
|
|
href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3541591" target="_blank">SSRN</a>|<a class="paperlink"
|
|
href="https://pubsonline.informs.org/doi/abs/10.1287/moor.2020.1061" target="_blank">Article</a>]</span><br>
|
|
<div class="fade-in" style="display:none" id="abs_FK">
|
|
<hr>
|
|
We establish a stochastic representation for a class of nonlocal parabolic terminal-boundary value
|
|
problems, whose terminal and boundary conditions depend on the solution in the interior domain; in
|
|
particular, the solution is represented as the expectation of functionals of a diffusion process
|
|
with random jumps from boundaries. We discuss three applications of the representation, the first
|
|
one on the pricing of dual-purpose funds, the second one on the connection to regenerative
|
|
processes, and the third one on modeling the entropy on a one-dimensional non-rigid body.
|
|
</div>
|
|
</li><br>
|
|
|
|
<li>Inventory Management for High-Frequency Trading with Imperfect Competition (with <a class="authorlink"
|
|
href="http://www-personal.umich.edu/~sherrma/" target="blank">Sebastian Herrmann</a>, <a class="authorlink"
|
|
href="https://wwwf.imperial.ac.uk/~jmuhleka/" target="blank">Johannes Muhle-Karbe</a> and <a class="authorlink"
|
|
href="https://www.linkedin.com/in/dapeng-shang-654316105/" target="blank">Dapeng Shang</a>).<br>
|
|
<i><b>SIAM Journal on Financial Mathematics</b></i>, 11(1):1-26, 2020. <span class="links">[<a class="paperlink" href=""
|
|
onclick="toggleAbstract('abs_HFT');return false">Abstract</a>|<a class="paperlink"
|
|
href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3232037" target="_blank">SSRN</a>|<a class="paperlink"
|
|
href="http://arxiv.org/abs/1808.05169" target="_blank">arXiv</a>|<a class="paperlink"
|
|
href="https://epubs.siam.org/doi/abs/10.1137/18M1207776" target="_blank">Article</a>]</span><br>
|
|
<div class="fade-in" style="display:none" id="abs_HFT">
|
|
<hr>
|
|
We study Nash equilibria for inventory-averse high-frequency traders (HFTs), who trade to exploit
|
|
information about future price changes. For discrete trading rounds, the HFTs' optimal trading
|
|
strategies and their equilibrium price impact are described by a system of nonlinear equations;
|
|
explicit solutions obtain around the continuous-time limit. Unlike in the risk-neutral case, the
|
|
optimal inventories become mean-reverting and vanish as the number of trading rounds becomes large.
|
|
In contrast, the HFTs' risk-adjusted profits and the equilibrium price impact converge to their
|
|
risk-neutral counterparts. Compared to a social-planner solution for cooperative HFTs, Nash
|
|
competition leads to excess trading, so that marginal transaction taxes in fact decrease market
|
|
liquidity.
|
|
</div>
|
|
</li><br>
|
|
|
|
<li>Optimal Tax-timing with Asymmetric Long-term/short-term Capital Gains Tax (with <a class="authorlink"
|
|
href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, <a class="authorlink"
|
|
href="http://apps.olin.wustl.edu/faculty/liuh/" target="blank">Hong Liu</a> and <a class="authorlink"
|
|
href="https://www.linkedin.com/in/yifei-zhong-12858524/" target="_blank">Yifei Zhong</a>).<br>
|
|
<i><b>The Review of Financial Studies</b></i>, 28.9:2687-2721, 2015. <span class="links">[<a class="paperlink" href=""
|
|
onclick="toggleAbstract('abs_taxTiming');return false">Abstract</a>|<a class="paperlink"
|
|
href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1786012" target="_blank">SSRN</a>|<a class="paperlink"
|
|
href=https://academic.oup.com/rfs/article/28/9/2687/1581078, target="_blank">Article</a>]</span><br>
|
|
<div class="fade-in" style="display:none" id="abs_taxTiming">
|
|
<hr>
|
|
We develop an optimal tax-timing model that takes into account asymmetric long-term and short-term
|
|
tax rates for positive capital gains and limited tax deductibility of capital losses. In contrast to
|
|
the existing literature, this model can help explain why many investors not only defer short-term
|
|
capital losses to long term but also defer large long-term capital gains and losses. Because the
|
|
benefit of tax deductibility of capital losses increases with the short-term tax rates, effective
|
|
tax rates can decrease as short-term capital gains tax rates increase.
|
|
</div>
|
|
</li>
|
|
</ol>
|
|
</p>
|
|
|
|
<hr class="style-one">
|
|
|
|
<p>
|
|
<h3>Grants</h3>
|
|
<ul style="list-style-type:square">
|
|
<li> General Research Fund, <i>Continuous-Time Nonconcave Portfolio Selection with General Payoffs and
|
|
Transaction Costs</i>, 2023 - 2026</li>
|
|
<li> General Research Fund (ECS), <i>High-Dimensional Continuous-Time Portfolio Selection with Capital Gains
|
|
Tax</i>, 2022 - 2024</li>
|
|
<li> Direct Grant, <i>Hedging Periodic Cash Flow Streams under Market Frictions</i>, 2020 - 2022 </li>
|
|
<li> Start-up Grant at CUHK </li>
|
|
</ul>
|
|
</p>
|
|
|
|
<hr id="service" class="style-one">
|
|
|
|
<p>
|
|
<h3>Professional Service</h3>
|
|
<ul style="list-style-type:square">
|
|
<li> <b>Associate Editor:</b> <a class="jourlink" href="https://www.springer.com/journal/42521" target="_blank"><i><b>Digital
|
|
Finance</b></i></a>, 2020 - Present</li><br>
|
|
<li> <b>Reviewer:</b>
|
|
<ul style="list-style-type:circle">
|
|
<li> Management Science, Operations Research, Mathematics of Operations Research, Journal of the Operational Research Society, Journal of Optimization Theory and Applications</li>
|
|
<li> Mathematical Finance, Finance and Stochastics, SIAM Journal on Financial Mathematics, Quantitative
|
|
Finance, Mathematics and Financial Economics. </li>
|
|
<li> Journal of Financial and Quantitative Analysis, European Financial Management, Journal of Economic Dynamics and Control, International Journal of
|
|
Theoretical and Applied Finance, Economic Modelling. </li>
|
|
</ul>
|
|
</li><br>
|
|
<li> <b>Conference Organizing:</b>
|
|
<ul style="list-style-type:circle">
|
|
<li> Local Organizing Committee Member, <a class="jourlink" href="https://events.polyu.edu.hk/scftml/home"
|
|
target='_blank'><b>Workshop on Stochastic Control, Financial Technology, and Machine Learning</b></a>, 2025</li>
|
|
<li> Mini-Symposium Organizer, <a class="jourlink" href="https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=84092"
|
|
target='_blank'><b>MS54 Recent Advances in Quantitative Finance and FinTech</b></a>, SIAM
|
|
Conference on Financial Mathematics and Engineering (FM25), 2025.</li>
|
|
<li> Session Chair, <b>ME14 Quantitative Finance and FinTech</b>, 2024 INFORMS Annual Meeting, 2024.
|
|
</li>
|
|
<li> Local Organizing Committee Member, <a class="jourlink" href="https://events.polyu.edu.hk/icfe/home"
|
|
target='_blank'><b>First INFORMS Conference on Financial Engineering and FinTech</b></a>, 2024. </li>
|
|
<li> Session Chair, <b>TA73 Financial Frictions and Machine Learning</b>, 2023 INFORMS Annual Meeting,
|
|
2023. </li>
|
|
<li> Local Organizing Committee Member, <a class="jourlink"
|
|
href="https://www.polyu.edu.hk/ama/news-and-events/events/2023/8/recent-advances-on-quantitative-finance/"
|
|
target="_blank"><b>Recent Advances on Quantitative Finance</b></a>, 2023. </li>
|
|
<li> Mini-Symposium Organizer, <a class="jourlink"
|
|
href="https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=70910"
|
|
target="_blank"><b>MS5 Investment and Asset Pricing under Market Frictions</b></a>, SIAM
|
|
Conference on Financial Mathematics and Engineering (FM21), 2021. </li>
|
|
</ul>
|
|
</li><br>
|
|
<li> <b> Seminar Organizing:</b>
|
|
<ul style="list-style-type:circle">
|
|
<li> Organizing Committee Member, <a class="extlink" href="https://sites.google.com/view/hksgfinmatheng/home"
|
|
target="_blank"><b>The Hong Kong - Singapore Joint Seminar Series in Financial
|
|
Mathematics/Engineering</b></a>.</li>
|
|
<li> Organizing Committee Member, <a class="extlink" href="https://www.cfe.cuhk.edu.hk/cuhkqf/" target="_blank"><b>CUHK
|
|
Distinguished Lectures in Quantitative Finance</b></a>.</li>
|
|
</ul>
|
|
</li>
|
|
</ul>
|
|
</p>
|
|
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