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290 lines
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<title>Homepage of YANG Chen @ SEEM, CUHK</title>
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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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<h1>YANG, Chen</h1>
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<td width="5"></td>
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<td width="160"><img src="ME.jpeg" width="160"></td>
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<td width="20"></td>
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<td>
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Assistant Professor <br>
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<a href="http://www.se.cuhk.edu.hk" target="_blank">Department of Systems Engineering and Engineering Management</a> <br>
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<a 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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Room 511A, William M.W. Mong Engineering Building <br>
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The Chinese University of Hong Kong <br>
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Shatin, N.T., Hong Kong<br><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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<h3>Teaching <br> <a href="https://blackboard.cuhk.edu.hk" target="_blank">[Blackboard@CUHK]</a></h3>
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Undergraduate Courses
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<dl>
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<dt><b>Spring 2020-2025</b></dt>
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<dd>SEEM3580 Risk Analysis for Financial Engineering</dd>
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<dt><b>Fall 2019-2024</b></dt>
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<dd>SEEM3590 Investment Science</dd>
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</dl>
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Postgraduate Courses
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<dt><b>Spring 2025</b></dt><dd>SEEM5140 Optimal Control</dd>
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<dt><b>Spring 2023</b></dt><dd>SEEM5670 Advanced Models in Financial Engineering</dd>
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<dt><b>Fall 2021</b></dt><dd>SEEM5340 Stochastic Calculus (with <a href="https://sites.google.com/site/xuedonghepage/home" target="_blank">Xuedong He</a> and <a href="https://sites.google.com/view/lingfeili" target="_blank">Lingfei Li</a>)</dd>
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<hr id="research" class="style-one">
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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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<ul style="list-style-type:square">
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<li>Arbitraging on Decentralized Exchanges (with <a href="https://sites.google.com/site/xuedonghepage/home" target="_blank">Xuedong He</a> and Yutian Zhou).<br>
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Working Paper. [<a href="" onclick="toggleAbstract('abs_arbDEX');return false">Abstract</a>]<br>
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<div style="display:none" id="abs_arbDEX">
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<hr>
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<i>Decentralized exchanges (DEXs) are alternative venues to centralized exchanges to trade cryptocurrencies (CEXs) and have become increasingly popular. An arbitrage opportunity arises when the exchange rate of two cryptocurrencies in a DEX differs from that in a CEX. Arbitrageurs can then trade on the DEX and CEX to make a profit. Trading on the DEX incurs a gas fee, which determines the priority of the trade being executed. We study a gas-fee competition game between two arbitrageurs who maximize their expected profit from trading. We derive the unique symmetric mixed Nash equilibrium and find that (i) the arbitrageurs may choose not to trade when the arbitrage opportunity is small; (ii) the probability of the arbitrageurs choosing a higher gas fee is lower; (iii) the arbitrageurs pay a higher gas fee and trade more when the arbitrage opportunity becomes larger and when liquidity becomes higher. The above findings are consistent with our empirical study. </i>
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</div>
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</li><br>
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<li>Portfolio Selection with Time-Varying Taxation (with Xianhao Zhu).<br>
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Working Paper. [<a href="" onclick="toggleAbstract('abs_TaxTimeVarying');return false">Abstract</a>]<br>
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<div style="display:none" id="abs_TaxTimeVarying">
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<hr>
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<i>The capital gains tax rate has fluctuated significantly over time, leading to substantial changes in investors' optimal strategies, as documented by the empirical studies. This paper proposes a novel continuous-time portfolio selection framework with a time-varying capital gains tax rate. Featuring differential tax rate announcement time and implementation time, our framework is able to capture the investors' anticipation over a potential future tax rate change before its announcement, as well as their reaction to an announced tax change yet to be implemented. The optimal investment strategy embodies the interaction between the time-varying tax rate and the lock-in and diversification effects proposed in the existing literature. Furthermore, our findings provide theoretical support for the permanent and transitory effects of tax rate changes documented in the empirical studies. The strength of the transitory effect depends on the size of the tax rate change, and the tax rate uncertainty mostly affects the transitory effect and has a negligible impact on the permanent effect. Moreover, the permanent effect vanishes under a zero interest rate while the transitory effect persists. </i>
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</div>
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</li><br>
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<li>Periodic Evaluation with Non-Concave Utility (with <a href="https://scholar.google.com/citations?user=OzeF8T0AAAAJ&hl" target="_blank">Cong Qin</a> and <a href="https://www.ma.ic.ac.uk/~hz/"> Harry Zheng</a>).<br>
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<b>submitted</b>. [<a href="" onclick="toggleAbstract('abs_periodicEvaluation');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5305617" target="_blank">SSRN</a>]<br>
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<div style="display:none" id="abs_periodicEvaluation">
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<hr>
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<i>A fund manager's performance is often evaluated annually and compared with a benchmark, such as a market index. In addition, the manager may be subject to trading constraints, such as limited use of leverage, no short-selling, and a forced liquidation clause. We formulate this as a periodic evaluation problem with a non-concave utility, a stochastic reference point, and trading constraints. The value function is characterized as the unique solution to a Hamilton-Jacobi-Bellman equation with periodic terminal and boundary conditions, which must be imposed carefully due to possible discontinuities at the terminal time and/or on the liquidation boundary. We find that, at the evaluation time, future investment opportunities induce a discontinuity in the value function on the liquidation boundary, leading to a substantial change in local risk-aversion. More importantly, this local concavity/convexity weakens and shifts inward from the liquidation boundary to the interior region as the evaluation horizon increases. As a result, the joint effect of periodic evaluation and forced liquidation can generate highly nonlinear investment strategies, which is helpful in understanding the complexity of trading strategies in the loss region.</i>
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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 href="https://scholar.google.com/citations?user=os0TtfkAAAAJ&hl=en" target="_blank">Xiaoshan Chen</a> and Zhou Yang).<br>
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<b>submitted</b>. [<a href="" onclick="toggleAbstract('abs_dataAsset');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5263455" target="_blank">SSRN</a>|<a href="https://arxiv.org/abs/2505.16106" target="_blank">arXiv</a>]<br>
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<div style="display:none" id="abs_dataAsset">
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<hr>
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<i>Data assets are data commodities that have been processed, produced, priced, and traded based on actual demand. Reasonable pricing mechanism for data assets is essential for developing the data market and realizing their value. Most existing literature approaches data asset pricing from the seller's perspective, focusing on data properties and collection costs, however, research from the buyer's perspective remains scarce. This gap stems from the nature of data assets: their value lies not in direct revenue generation but in providing informational advantages that enable enhanced decision-making and excess returns. This paper addresses this gap by developing a pricing model based on the informational value of data assets from the buyer's perspective. We determine data asset prices through an implicit function derived from the value functions in two robust investment-consumption problems under ambiguity markets via indifference pricing principle. By the existing research results, we simplify the value function, using mathematical analysis and differential equation theory, we derive general expressions for data assets price and explore their properties under various conditions. Furthermore, we derive the explicit pricing formulas for specific scenarios and provide numerical illustration to describe how to use our pricing model.</i>
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</div>
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</li><br>
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<li>Arbitrage in Perpetual Contracts (with <a href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a> and Linfeng Li).<br>
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<b>submitted</b>. [<a href="" onclick="toggleAbstract('abs_arbPerp');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5262988" target="_blank">SSRN</a>]<br>
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<div style="display:none" id="abs_arbPerp">
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<hr>
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<i>Perpetual contracts, designed to track the underlying price through a funding swap mechanism, have gained significant popularity in cryptocurrency markets. However, observed price discrepancies between perpetual contracts and the underlying asset cannot be explained solely by transaction fees. By examining the impact of the clamping function inherent in the funding swap mechanism -- an overlooked aspect in existing literature -- we derive model-free no-arbitrage bounds for perpetual contracts. Our findings reveal that these bounds persist as intervals even without transaction fees, due to the clamping function. Empirical analysis using two years of Binance data supports the validity of our proposed bounds. </i>
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</div>
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</li><br>
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<li>Optimal Tax-Timing with Transaction Costs (with <a href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, Yaoting Lei, and <a href="http://apps.olin.wustl.edu/faculty/liuh/" target="blank">Hong Liu</a>).<br>
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<b>submitted</b>. [<a href="" onclick="toggleAbstract('abs_TaxTC');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4952040" target="_blank">SSRN</a>]<br>
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<div style="display:none" id="abs_TaxTC">
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<hr>
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<i>We develop a dynamic portfolio model incorporating capital gains tax (CGT), transaction costs, and year-end taxation. We find that even tiny transaction costs can lead to significant deferral of large losses and transaction costs affect loss deferrals much more than gain deferrals. Our model can thus help explain the puzzle that even when investors face equal long-term/short-term CGT rates, they may still defer realizing large capital losses for an extended period of time, displaying the disposition effect. In addition, we find misestimating transaction costs is costly. We also provide several unique, empirically testable predictions and shed light on recently proposed tax policy changes.</i>
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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 href="https://sites.google.com/site/xuedonghepage/home" target="_blank">Xuedong He</a> and Yutian Zhou).<br>
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<b>submitted</b>. [<a href="" onclick="toggleAbstract('abs_AMM');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4801468" target="_blank">SSRN</a>|<a href="https://arxiv.org/abs/2404.13291" target="_blank">arXiv</a>]<br>
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<div style="display:none" id="abs_AMM">
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<hr>
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<i>Automated market makers are a popular mechanism used on decentralized exchange, through which users trade assets with each other directly and automatically through a liquidity pool and a fixed pricing function. The liquidity provider contributes to the liquidity pool by supplying assets to the pool, and in return, they earn trading fees from investors who trade in the pool. We propose a model of optimal liquidity provision in which a risk-averse liquidity provider decides the amount of wealth she would invest in the decentralized market to provide liquidity in a two-asset pool, trade in a centralized market, and consume in multiple periods. We derive the liquidity provider's optimal strategy and the optimal design of the automated market maker that maximizes the liquidity provider's utility. We find that the optimal unit trading fee increases in the volatility of the fundamental exchange rate of the two assets. We also find that the optimal pricing function is chosen to make the asset allocation in the liquidity pool efficient for the liquidity provider.</i>
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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 href="https://scholar.google.com/citations?user=MbbX8kUAAAAJ&hl=en" target="_blank">Xinfu Chen</a>, <a href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, and Zhou Yang).<br>
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<b>submitted</b>. [<a href="" onclick="toggleAbstract('abs_LocalVol');return false">Abstract</a>|<a href=" https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4801520" target="_blank">SSRN</a>]<br>
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<div style="display:none" id="abs_LocalVol">
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<hr>
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<i>We study non-parametric calibration of local volatility models, which is formulated as an inverse problem of partial differential equations with Tikhonov regularization. In contrast to the existing literature minimizing the distance between theoretical and market prices of options as a calibration criterion, we instead minimize the distance between theoretical and market implied volatilities, complying with market practices. We prove that our calibration criterion naturally leads to the well-posedness of the calibration problem. In particular, comparing to Jiang and Tao (2001), we obtain a global uniqueness result, where no additional weight functions are required. Numerical results reveal that our method achieves a better trade-off between minimizing calibration errors and reducing overfitting.</i>
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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 href="https://www1.se.cuhk.edu.hk/~nchenweb/index.htm" target="_blank">Nan Chen</a>, <a href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, and Qiheng Ding).<br>
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<b>submitted</b>. [<a href="" onclick="toggleAbstract('abs_LOB');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4671774" target="_blank">SSRN</a>]<br>
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<div style="display:none" id="abs_LOB">
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<hr>
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<i>This paper investigates an optimal investment problem in an illiquid market, modeling explicitly the effects of three key features of market microstructure --- market tightness, market depth, and finite market resilience --- on the investor's decision. By employing a Bachelier process to model the dynamic of the fundamental value of the asset and assuming CARA-type utility for the investor, we manage to obtain the investor's optimal dynamic trading strategy in closed form by solving the resulting high-dimensional singular control problem. Furthermore, we extend the model to incorporate return-predicting signals and utilize an asymptotic expansion approach to derive approximate optimal trading strategies. The theoretical and numerical results emphasize the vital role of patience. Specifically, rather than dispersing small trades continuously over time as advocated by the existing literature, our findings suggest that investors should strategically time their trading activities to align with the aim portfolio in the presence of market resilience. To quantify this timing decision, we introduce a patience index that enables investors to strike a balance among various competing goals, including achieving currently optimal risk exposure, incorporating signals about future predictions, and minimizing trading costs, by leveraging market resilience.</i>
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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 href="https://sites.google.com/view/shuaijie-qian" target="_blank">Shuaijie Qian</a>).<br>
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<b>submitted</b>. [<a href="" onclick="toggleAbstract('abs_NonconcaveTC');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4500965" target="_blank">SSRN</a>|<a href="https://arxiv.org/abs/2307.02178" target="_blank">arXiv</a>]<br>
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<div style="display:none" id="abs_NonconcaveTC">
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<hr>
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<i>This paper studies a finite-horizon portfolio selection problem with non-concave terminal utility and proportional transaction costs. The commonly used concavification principle for terminal value is no longer valid here, and we establish a proper theoretical characterization of this problem. We first give the asymptotic terminal behavior of the value function, which implies any transaction close to maturity only provides a marginal contribution to the utility. After that, the theoretical foundation is established in terms of a novel definition of the viscosity solution incorporating our asymptotic terminal condition. Via numerical analyses, we find that the introduction of transaction costs into non-concave utility maximization problems can prevent the portfolio from unbounded leverage and make a large short position in stock optimal despite a positive risk premium and symmetric transaction costs.</i>
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</div>
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</li><br>
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<li>Designing Stablecoins (with <a href="https://www.linkedin.com/in/yizhoucao/" target="_blank">Yizhou Cao</a>, <a href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, <a href="https://www.bu.edu/questrom/profile/steven-kou/" target="_blank">Steven Kou</a> and <a 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. [<a href="" onclick="toggleAbstract('abs_StableCoin');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3856569" target="_blank">SSRN</a>|<a href="https://doi.org/10.1111/mafi.12445" target="_blank">Article</a>]<br>
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<div style="display:none" id="abs_StableCoin">
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<hr>
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<i>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.</i>
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</div>
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</li><br>
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<li>An Equilibrium Model for the Cross Section of Liquidity Premia (with <a href="https://wwwf.imperial.ac.uk/~jmuhleka/" target="_blank">Johannes Muhle-Karbe</a> and <a href="https://xf-shi.github.io" target="_blank">Xiaofei Shi</a>).<br>
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<i><b>Mathematics of Operations Research</b></i>, 48(3):1423-1453, 2023. [<a href="" onclick="toggleAbstract('abs_LiqPre');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3738500" target="_blank">SSRN</a>|<a href="https://arxiv.org/abs/2011.13625"
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target="_blank">arXiv</a>|<a href="https://pubsonline.informs.org/doi/abs/10.1287/moor.2022.1307" target="_blank">Article</a>]<br>
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<div style="display:none" id="abs_LiqPre">
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<hr>
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<i>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.</i>
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</div>
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</li><br>
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<li>Leveraged Exchange-Traded Funds with Market Closure and Frictions (with <a href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, <a href="https://www.bu.edu/questrom/profile/steven-kou/" target="_blank">Steven Kou</a> and <a href="https://people.math.ethz.ch/~hmsoner/" target="blank">H. Mete Soner</a>).<br>
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<i><b>Management Science</b></i>, 69(4):2517-2535, 2023. [<a href="" onclick="toggleAbstract('abs_LETF');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3856573" target="_blank">SSRN</a>|<a href="https://pubsonline.informs.org/doi/abs/10.1287/mnsc.2022.4407" target="_blank">Article</a>]<br>
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<div style="display:none" id="abs_LETF">
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<hr>
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<i>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.
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The result extends the principle of "aiming in front of target" introduced by <a 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.</i>
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</div>
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</li><br>
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<li>A Stochastic Representation for Nonlocal Parabolic PDEs with Applications (with <a href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a> and <a href="https://www.bu.edu/questrom/profile/steven-kou/" target="_blank">Steven Kou</a>).<br>
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<i><b>Mathematics of Operations Research</b></i>, 47(3):1707-1730, 2022 [<a href="" onclick="toggleAbstract('abs_FK');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3541591" target="_blank">SSRN</a>|<a href="https://pubsonline.informs.org/doi/abs/10.1287/moor.2020.1061" target="_blank">Article</a>]<br>
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<div style="display:none" id="abs_FK">
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<hr>
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<i>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.</i>
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</div>
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</li><br>
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<li>Inventory Management for High-Frequency Trading with Imperfect Competition (with <a href="http://www-personal.umich.edu/~sherrma/" target="blank">Sebastian Herrmann</a>, <a href="https://wwwf.imperial.ac.uk/~jmuhleka/" target="blank">Johannes Muhle-Karbe</a> and <a href="https://www.linkedin.com/in/dapeng-shang-654316105/<Paste>" target="blank">Dapeng Shang</a>).<br>
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<i><b>SIAM Journal on Financial Mathematics</b></i>, 11(1):1-26, 2020. [<a href="" onclick="toggleAbstract('abs_HFT');return false">Abstract</a>|<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3232037" target="_blank">SSRN</a>|<a href="http://arxiv.org/abs/1808.05169" target="_blank">arXiv</a>|<a href="https://epubs.siam.org/doi/abs/10.1137/18M1207776" target="_blank">Article</a>]<br>
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<div style="display:none" id="abs_HFT">
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<hr>
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<i>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.</i>
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</div>
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</li><br>
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<li>Optimal Tax-timing with Asymmetric Long-term/short-term Capital Gains Tax (with <a href="https://sites.google.com/view/mindai/home" target="_blank">Min Dai</a>, <a href="http://apps.olin.wustl.edu/faculty/liuh/" target="blank">Hong Liu</a> and <a href="https://www.linkedin.com/in/yifei-zhong-12858524/" target="_blank">Yifei Zhong</a>).<br>
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<i><b>The Review of Financial Studies</b></i>, 28.9:2687-2721, 2015. [<a href=""
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onclick="toggleAbstract('abs_taxTiming');return false">Abstract</a>|<a
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href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1786012" target="_blank">SSRN</a>|<a href=https://academic.oup.com/rfs/article/28/9/2687/1581078, target="_blank">Article</a>]<br>
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<div style="display:none" id="abs_taxTiming">
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<hr>
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<i>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.</i>
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</div>
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</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>Grants</h3>
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<ul style="list-style-type:square">
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<li> General Research Fund, <i>Continuous-Time Nonconcave Portfolio Selection with General Payoffs and Transaction Costs</i>, 2023 - 2026</li>
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<li> General Research Fund (ECS), <i>High-Dimensional Continuous-Time Portfolio Selection with Capital Gains Tax</i>, 2022 - 2024</li>
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<li> Direct Grant, <i>Hedging Periodic Cash Flow Streams under Market Frictions</i>, 2020 - 2022 </li>
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<li> Start-up Grant at CUHK </li>
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</ul>
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</p>
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<hr id="service" class="style-one">
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<p>
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<h3>Professional Service</h3>
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<ul style="list-style-type:square">
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<li> <b>Associate Editor:</b> <a href="https://www.springer.com/journal/42521" target="_blank"><i>Digital Finance</i></a>, 2020 - Present</li><br>
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<li> <b>Reviewer:</b>
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<ul style="list-style-type:circle">
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<li> Management Science, Operations Research, Mathematics of Operations Research. </li>
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<li> Mathematical Finance, Finance and Stochastics, SIAM Journal on Financial Mathematics, Quantitative Finance, Mathematics and Financial Economics. </li>
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<li> European Financial Management, Journal of Economic Dynamics and Control, International Journal of Theoretical and Applied Finance, Economic Modelling. </li>
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</ul>
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</li><br>
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<li> <b>Conference Organizing:</b>
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<ul style="list-style-type:circle">
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<li> Session Chair, <b>ME14 Quantitative Finance and FinTech</b>, 2024 INFORMS Annual Meeting, 2024. </li>
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<li> Local Organizing Committee Member, <a href="https://events.polyu.edu.hk/icfe/home" target='_blank'>First INFORMS Conference on Financial Engineering and FinTech</a>, 2024. </li>
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<li> Session Chair, <b>TA73 Financial Frictions and Machine Learning</b>, 2023 INFORMS Annual Meeting, 2023. </li>
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<li> Local Organizing Committee Member, <a href="https://www.polyu.edu.hk/ama/news-and-events/events/2023/8/recent-advances-on-quantitative-finance/" target="_blank">Recent Advances on Quantitative Finance</a>, 2023. </li>
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<li> Mini-Symposium Organizer, <a 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>
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</ul>
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</li><br>
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<li> <b> Seminar Organizing:</b>
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<ul style="list-style-type:circle">
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<li> Organizing Committee Member, <a 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>
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<li> Organizing Committee Member, <a href="https://www.cfe.cuhk.edu.hk/cuhkqf/" target="_blank"><b> CUHK Distinguished Lectures in Quantitative Finance</b><a>.</li>
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</ul>
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</li>
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</ul>
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</p>
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