192 lines
17 KiB
HTML
Executable File
192 lines
17 KiB
HTML
Executable File
<!doctype html>
|
||
<html>
|
||
<head>
|
||
<link rel="stylesheet" href="style.css">
|
||
<link rel="stylesheet" href="fontawesome-free-5.15.3-web/css/all.css">
|
||
<meta http-equiv="content-type" content="text/html; charset=utf-8">
|
||
<title>YANG, Chen</title>
|
||
<script>
|
||
function toggleAbstract(absId) {
|
||
var x = document.getElementById(absId);
|
||
if (x.style.display === "none") {
|
||
x.style.display = "block";
|
||
} else {
|
||
x.style.display = "none";
|
||
}
|
||
}
|
||
</script>
|
||
</head>
|
||
<body bgcolor="#FFFFFF">
|
||
|
||
<div class="navbar">
|
||
<a href="#home">Home</a>
|
||
<a href="#teaching">Teaching</a>
|
||
<a href="#research">Research</a>
|
||
</div>
|
||
|
||
<div class="main" id="home">
|
||
<p> </p><br>
|
||
</div>
|
||
|
||
<h1>YANG, Chen</h1>
|
||
<div id="shadowbox">
|
||
<table>
|
||
<tbody>
|
||
<tr>
|
||
<td width="10"></td>
|
||
<td width="160"><img src="ME.jpeg" width="160"></td>
|
||
<td width="20"></td>
|
||
<td>
|
||
Assistant Professor <br>
|
||
<a href="http://www.se.cuhk.edu.hk" target="_blank">Department of Systems Engineering and Engineering Management</a> <br>
|
||
<a href="https://www.erg.cuhk.edu.hk/erg/">Faculty of Engineering</a> <br>
|
||
The Chinese University of Hong Kong <br><br>
|
||
<i class="fas fa-map-marker-alt"></i>
|
||
Room 511A, William M.W. Mong Engineering Building <br>
|
||
The Chinese University of Hong Kong <br>
|
||
Shatin, N.T., Hong Kong<br><br>
|
||
<i class="fas fa-envelope"></i> cyang at se.cuhk.edu.hk <br>
|
||
<i class="fas fa-phone-alt"></i> +852 3943-8322 <br>
|
||
</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
|
||
<br>
|
||
|
||
<p>
|
||
<h3 id="teaching">Teaching <br> <a href="https://blackboard.cuhk.edu.hk" target="_blank">[Blackboard@CUHK]</a></h3>
|
||
Undergraduate Courses
|
||
<ul class="notATable">
|
||
<li><label><b>Spring 2023 </b></label><div>SEEM3580 Risk Analysis for Financial Engineering</div></li>
|
||
<li><label><b>Fall 2022 </b></label><div>SEEM3590 Investment Science</div></li>
|
||
<li><label><b>Spring 2022 </b></label><div>SEEM3580 Risk Analysis for Financial Engineering</div></li>
|
||
<li><label><b>Fall 2021 </b></label><div>SEEM3590 Investment Science</div></li>
|
||
<li><label><b>Spring 2021 </b></label><div>SEEM3580 Risk Analysis for Financial Engineering</div></li>
|
||
<li><label><b>Fall 2020 </b></label><div>SEEM3590 Investment Science</div></li>
|
||
<li><label><b>Spring 2020 </b></label><div>SEEM3580 Risk Analysis for Financial Engineering</div></li>
|
||
<li><label><b>Fall 2019 </b></label><div>SEEM3590 Investment Science</div></li>
|
||
</ul>
|
||
|
||
Postgraduate Courses
|
||
<ul class="notATable">
|
||
<li><label><b>Spring 2023 </b></label><div>SEEM5670 Advanced Models in Financial Engineering</div></li>
|
||
<li><label><b>Fall 2021 </b></label><div>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/site/lingfeilicuhk/" target="_blank">Lingfei Li</a>)</div></li>
|
||
</ul>
|
||
</p>
|
||
<hr class="style-one">
|
||
|
||
<p>
|
||
<h3 id="research">Research Interest</h3>
|
||
Stochastic Control; Market Frictions; Market Microstructure; FinTech; Deep Learning for Stochastic Control.
|
||
</p>
|
||
|
||
<hr class="style-one">
|
||
|
||
<p>
|
||
<h3>Selected Publications</h3>
|
||
<ul style="list-style-type:square">
|
||
<li><b>Non-Concave Utility Maximization with Transaction Costs</b> (with <a href="https://sites.google.com/view/shuaijie-qian" target="_blank">Shuaijie Qian</a>).<br>
|
||
submitted. [<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>
|
||
<div style="display:none" id="abs_NonconcaveTC">
|
||
<hr>
|
||
<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>
|
||
</div>
|
||
</li><br>
|
||
|
||
<li><b>Optimal Investment under Block-Shaped Order Books</b> (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>
|
||
working paper. [<a href="" onclick="toggleAbstract('abs_LOB');return false">Abstract</a>]<br>
|
||
<div style="display:none" id="abs_LOB">
|
||
<hr>
|
||
<i>We study an optimal investment problem of a CARA investor trading in a market operated with a block-shaped limited order book (LOB). The model synergizes three key features of market microstructure: the bid-ask spread, the market depth, and a finite market resilience. Under a Bachelier process for the dynamic of the fundamental value of the asset, we develop explicit characterization on the investor’s optimal trading strategy. As an important extension of this model, an asymptotic expansion of the optimal trading strategies in the presence of return-predicting signals are also derived. The theoretical and numerical results unveil how an investor should strike a balance among several competing goals such as achieving the optimal risk exposure currently, incorporating signals about the future, and minimizing trading costs. Contributing to the existing literature, our model helps to quantify significant impacts of the market resilience on the trading decisions. </i>
|
||
</div>
|
||
</li><br>
|
||
|
||
<li><b>Designing Stable Coins</b> (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>
|
||
submitted. [<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>]<br>
|
||
<div style="display:none" id="abs_StableCoin">
|
||
<hr>
|
||
<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>
|
||
</div>
|
||
</li><br>
|
||
|
||
<li><b>An Equilibrium Model for the Cross-Section of Liquidity Premia</b> (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>
|
||
<i>Mathematics of Operations Research</i>, forthcoming. [<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"
|
||
target="_blank">arXiv</a>|<a href="https://pubsonline.informs.org/doi/abs/10.1287/moor.2022.1307" target="_blank">Article</a>]<br>
|
||
<div style="display:none" id="abs_LiqPre">
|
||
<hr>
|
||
<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>
|
||
</div>
|
||
</li><br>
|
||
|
||
<li><b>Leveraged Exchange-Traded Funds with Market Closure and Frictions</b> (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>
|
||
<i>Management Science</i>, 69(4):1935-2545, 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>
|
||
<div style="display:none" id="abs_LETF">
|
||
<hr>
|
||
<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.
|
||
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>
|
||
</div>
|
||
</li><br>
|
||
|
||
<li><b>A Stochastic Representation for Nonlocal Parabolic PDEs with Applications</b> (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>
|
||
<i>Mathematics of Operations Research</i>, 47(3):1707-2545, 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>
|
||
<div style="display:none" id="abs_FK">
|
||
<hr>
|
||
<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>
|
||
</div>
|
||
</li><br>
|
||
|
||
<li><b>Inventory Management for High-Frequency Trading with Imperfect Competition</b> (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>
|
||
<i>SIAM Journal on Financial Mathematics</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>
|
||
<div style="display:none" id="abs_HFT">
|
||
<hr>
|
||
<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>
|
||
</div>
|
||
</li><br>
|
||
|
||
<li><b>Optimal Tax-timing with Asymmetric Long-term/short-term Capital Gains Tax</b> (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>
|
||
<i>The Review of Financial Studies</i> 28.9:2687-2721, 2015. [<a href="" onclick="toggleAbstract('abs_taxTiming');return false">Abstract</a>|<a href=https://academic.oup.com/rfs/article/28/9/2687/1581078, target="_blank">Article</a>]<br>
|
||
<div style="display:none" id="abs_taxTiming">
|
||
<hr>
|
||
<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>
|
||
</div>
|
||
</li>
|
||
</ul>
|
||
</p>
|
||
|
||
<hr class="style-one">
|
||
|
||
<p>
|
||
<h3>Grants</h3>
|
||
<ul style="list-style-type:square">
|
||
<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 class="style-one">
|
||
|
||
<p>
|
||
<h3>Professional Service</h3>
|
||
<ul style="list-style-type:square">
|
||
<li> <b>Associate Editor:</b> <a href="https://www.springer.com/journal/42521" target="_blank"><i>Digital Finance</i></a>, 2020 - Present</li>
|
||
<li> <b>Reviewer:</b> Operations Research, Management Science, Mathematical Finance, Mathematics of Operations Research, SIAM Journal on Financial Mathematics, Quantitative Finance, Mathematics and Financial Economics. </li>
|
||
<li> <b>Conference Organizer:</b>
|
||
<ul style="list-style-type:circle">
|
||
<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>
|
||
<li> Invited Session Chair, <b>Financial Frictions and Machine Learning</b><a>, 2023 INFORMS Annual Meeting, 2023. </li>
|
||
</ul>
|
||
</li>
|
||
<li> <b>I am one of the organizers of <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>
|
||
</ul>
|
||
</p>
|
||
|
||
<hr class="curve">
|
||
|
||
<div align="right"><font size="-1"></font></div>
|
||
|
||
</body>
|
||
</html>
|