Gerry Tsoukalas

Gerry Tsoukalas is an assistant professor at the Wharton School at the University of Pennsylvania, teaching the core MBA class in Business Analytics. His research interests lie at the interface of operations, economics and finance. His recent work focuses on developing theoretical models and datadriven decisionmaking tools to study how firms are/should be financing their operations. Specific areas of application include: supply chain financing and inventory management under debt, new funding mechanisms, such as crowdfunding, financial market microstructure, and portfolio optimization.

Professor Tsoukalas completed his undergraduate studies in France, receiving degrees in Physics from the University of Paris, and Aeronautical Engineering from the Institut Supérieur de l'Aéronautique et de l'EspaceSupearo (2005). He completed his graduated studies in the US, receiving a Masters in Aeronautics & Aerospace from MIT (2007) and a PhD in Economics & Finance from the Management Science & Engineering Department at Stanford University (20092013). He was also previously a doctoral exchange scholar at the MIT Operations Research Center (20112012).

Professor Tsoukalas has experience working with a variety of firms in the financial services industry. Previously, he was a structured products trader at Morgan Stanley in London (20072009). He has also worked and consulted for several proprietary investment firms and hedge funds, including EvA Funds (20102011), and Weiss Asset Management (20122013), and has held stints in several international banks, including Barclays Capital (2006) and Societe Generale (2005).

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Jiri Chod, Trichakis Nikos, Gerry Tsoukalas (Under Review), Supplier Diversification Under Buyer Risk.

Abstract: We develop a new theory of supplier diversification based on buyer risk. When suppliers are subject to the risk of buyer default, buyers may take costly action to signal creditworthiness so as to obtain more favorable terms. But once signaling costs are sunk, buyers sourcing from a single supplier become vulnerable to future holdup. Although ex ante supply base diversification can be effective at alleviating the holdup problem, we show that it comes at the expense of higher upfront signaling costs. We resolve the ensuing trade off and show that diversification emerges as the preferred strategy in equilibrium. Our theory can help explain sourcing strategies when risk in a trade relationship originates from the sourcing firm, e.g., SMEs or startups; a setting which has eluded existing theories so far.

Vlad Babich, Gerry Tsoukalas, Simone Marinesi (Under Review), Does Crowdfunding Benefit Entrepreneurs and Venture Capital Investors?.

Abstract: We study how a new form of entrepreneurial finance crowdfunding interacts with more traditional financing sources, such as venture capital (VC) and bank financing. We model a multistage bargaining game, with a moralhazard problem between entrepreneurs and banks, and a doublesided moralhazard problem between entrepreneurs and VCs. We decompose the economic value of crowdfunding into cash gains or losses, costs of bad investments avoided, and projectpayoff probability update. This economic value is generally shared between entrepreneurs and VC investors, benefiting both. In addition, crowdfunding can alleviate the underinvestment problem due to moralhazard frictions. Furthermore, crowdfunding allows some projects to gain access to both VC and bank financing and the competition between those investor classes benefits entrepreneurs. However, competition from other investors reduces value to VC investors, who may walk away from the deal entirely. This can also hurt entrepreneurs who lose out on valuable VC expertise.

Jiri Chod, Trichakis Nikos, Gerry Tsoukalas (Under Review), A Signaling Theory of InKind Finance.

Abstract: We argue that by borrowing goods (e.g., through trade credit) rather than cash (e.g., through bank credit), firms may be able to convey private information to their creditors more efficiently. This is because borrowing illiquid, and potentially perishable goods, constitutes a more credible commitment, and hence a stronger signal of a firm's quality. Our theory rationalizes preference for supplier financing under information asymmetry without ascribing any prior informational advantage to the supplier. The effect is more pronounced when inputs are more differentiated and profit margins are higher.

Justin Sirignano, Gerry Tsoukalas, Kay Giesecke (2016), LargeScale Loan Portfolio Selection, Operations Research, 64, pp. 12391255.

Abstract: We consider the problem of optimally selecting a large portfolio of risky loans, such as mortgages, credit cards, auto loans, student loans, or business loans. Examples include loan portfolios held by financial institutions and fixedincome investors as well as pools of loans backing mortgage and assetbacked securities. The size of these portfolios can range from the thousands to even hundreds of thousands. Optimal portfolio selection requires the solution of a highdimensional nonlinear integer program and is extremely computationally challenging. For larger portfolios, this optimization problem is intractable. We propose an approximate optimization approach that yields an asymptotically optimal portfolio for a broad class of datadriven models of loan delinquency and prepayment. We prove that the asymptotically optimal portfolio converges to the optimal portfolio as the portfolio size grows large. Numerical case studies using actual loan data demonstrate its computational efficiency. The asymptotically optimal portfolio's computational cost does not increase with the size of the portfolio. It is typically many orders of magnitude faster than nonlinear integer program solvers while also being highly accurate even for moderatesized portfolios.

Dan Iancu, Trichakis Nikos, Gerry Tsoukalas (2016), Is Operating Flexibility Harmful under Debt?, Management Science.

Abstract: We study the relation between operating flexibility and the borrowing costs incurred by a firm financing inventory investments with debt. We find that flexibility in replenishing or liquidating inventory, by providing risk shifting incentives, could lead to borrowing costs that erase more than a third of the firm's value. In this context, we examine the effectiveness of practical and widely used covenants in restoring firm value by limiting such risk shifting behavior. We find that simple financial covenants can fully restore value for a firm that possesses a midseason inventory liquidation option. In the presence of added flexibility in replenishing or partially liquidating inventory, financial covenants fail, but simple borrowing base covenants successfully restore firm value. Explicitly characterizing optimal covenant tightness for all these cases, we find that better market conditions, such as lower inventory depreciation rate, higher gross margins or increased product demand, are typically associated with tighter covenants.   Our results suggest that inventoryheavy firms can reap the full benefits of additional operating flexibility, irrespective of their leverage, by entering simple debt contracts of the type commonly employed in practice. For such contracts to be effective, however, firms with enhanced flexibility and/or operating in better markets must also be willing to abide by more and/or tighter covenants.

Gerry Tsoukalas, Jiang Wang, Kay Giesecke (2015), Dynamic Portfolio Execution, Management Science, Forthcoming.

Abstract: We analyze the optimal execution problem of a portfolio manager trading multiple assets. In addition to the liquidity and risk of each individual asset, we consider crossasset interactions in these two dimensions, which substantially enriches the nature of the problem. Focusing on the market microstructure, we develop a tractable order book model to capture liquidity supply/demand dynamics in a multiasset setting, which allows us to formulate and solve the optimal portfolio execution problem. We find that crossasset risk and liquidity considerations are of critical importance in constructing the optimal execution policy. We show that even when the goal is to trade a single asset, its optimal execution may involve transitory trades in other assets. In general, optimally managing the risk of the portfolio during the execution process affects the time synchronization of trading in different assets. Moreover, links in the liquidity across assets lead to complex patterns in the optimal execution policy. In particular, we highlight cases where aggregate costs can be reduced by temporarily overshooting one's target portfolio.

Trichakis Nikos, Gerry Tsoukalas, Emer Moloney (2015), Credem: Banking on Cheese, Harvard Business School.

Abstract: Credem, an Italian regional bank, grants loans to Parmigiano Reggiano producers and holds the cheese as collateral in its own warehouse during the maturation process, essentially replacing part of the operations for the cheese producers and gaining deep operations expertise.

Kay Giesecke, Jack Kim, Baeho Kim, Gerry Tsoukalas (2014), Optimal Credit Swap Portfolios, Management Science, 60, pp. 22912307.

Abstract: This paper formulates and solves the selection problem for a portfolio of credit swaps. The problem is cast as a goal program that involves a constrained optimization of preferenceweighted moments of the portfolio value at the investment horizon. The constraints address collateral and solvency requirements, initial capital, and position limits. The portfolio value takes account of the exact timing of protection premium and default loss payments, as well as any marktomarket profits and losses realized at the horizon. The multimoment formulation accommodates the complex distribution of the portfolio value, which is a nested expectation under riskneutral and actual probabilities. It also generates computational tractability. Numerical results illustrate the features of optimal portfolios.

Gerry Tsoukalas, Peter Belobaba, William Swelbar (2008), Cost Convergence in the US Airline Industry: An Analysis of Unit Costs 19952006, Journal of Air Transport Management, 14 (4), pp. 179187.

Abstract: Recent changes in the strategies of US airlines have led to a convergence of unit costs between the network legacy carriers and lowcost carriers. We develop a methodology for breaking down operating cost data reported by the airlines and argue that certain cost categories must be excluded to make a valid comparison between the carrier groups. We find significant evidence of convergence in unit costs excluding fuel and transportrelated expenses, and labor unit costs in particular. While network legacy carriers have improved cost efficiency through dramatic labor cost reductions and longer stage length flying, lowcost carriers labor unit costs continue to increase as these former new entrant airlines mature.

Past Courses

OIDD353 MATH MDLNG APPL IN FNCE

Quantitative methods have become fundamental tools in the analysis and planning of financial operations. There are many reasons for this development: the emergence of a whole range of new complex financial instruments, innovations in securitization, the increased globalization of the financial markets, the proliferation of information technology and the rise of highfrequency traders, etc. In this course, models for hedging, asset allocation, and multiperiod portfolio planning are developed, implemented, and tested. In addition, pricing models for options, bonds, mortgagebacked securities, and other derivatives are studied. The models typically require the tools of statistics, optimization, and/or simulation, and they are implemented in spreadsheets or a highlevel modeling environment, MATLAB. This course is quantitative and will require extensive computer use. The course is intended for students who have strong interest in finance. The objective is to provide students the necessary practical tools they will require should they choose to join the financial services industry, particularly in roles such as: derivatives, quantitative trading, portfolio management, structuring, financial engineering, risk management, etc. Prospective students should be comfortable with quantitative methods ,such as basic statistics and the methodologies (mathematical programming and simulation) taugh tin OIDD612 Business Analytics and OIDD321 Management Science (or equivalent). Students should seek permission from the instructor if the background requirements are not met.

OIDD612 BUSINESS ANALYTICS

"Managing the Productive Core: Business Analytics" is a course on business analytics tools and their application to management problems. Its main topics are optimization, decision making under uncertainty, and simulation. The emphasis is on business analytics tools that are widely used in diverse industries and functional areas, including operations, finance, accounting, and marketing.

OIDD653 MATH MDLNG APPL IN FNCE

Quantitative methods have become fundamental tools in the analysis and planning of financial operations. There are many reasons for this development: the emergence of a whole range of new complex financial instruments, innovations in securitization, the increased globalization of the financial markets, the proliferation of information technology and the rise of highfrequency traders, etc. In this course, models for hedging, asset allocation, and multiperiod portfolio planning are developed, implemented, and tested. In addition, pricing models for options, bonds, mortgagebacked securities, and other derivatives are studied. The models typically require the tools of statistics, optimization, and/or simulation, and they are implemented in spreadsheets or a highlevel modeling environment, MATLAB. This course is quantitative and will require extensive computer use. The course is intended for students who have strong interest in finance. The objective is to provide students the necessary practical tools they will require should they choose to join the financial services industry, particularly in roles such as: derivatives, quantitative trading, portfolio management, structuring, financial engineering, risk management, etc. Prospective students should be comfortable with quantitative methods ,quantitative methods, such as basic statistics and the methodologies (mathematical programming and simulation) taught in OPIM612 Business Analytics or OPIM321 Management Science (or equivalent). Students should seek permission from the instructor if the background requirements are not met.

• Mack Institute for Innovation Management, 2015
• Jacobs Levy Equity Management Center for Quantitative Financial Research, 2015
• Dean’s Research Fund, 2015
• FishmanDavidson Center for Service and Operations Management, 2014
• Dean’s Research Fund, 2014
• FishmanDavidson Center for Service and Operations Management, 2013

• Dean’s Research Fund, 2013

• Why Budget Airlines Are Flying High, Knowledge@Wharton 06/13/2017

• When Crowdfunding Crowds Out the Competition, Mack Institute for Innovation Management 01/25/2017

• How Can We Combine Loans into Balanced Loan Portfolios?, Latest Thinking 12/01/2016

• Italian Bank Takes Cheese as Collateral for Loans, Fox News 07/06/2015

• A Bank That Accepts Parmesan As Collateral: The Cheese Stands A Loan, Forbes 07/01/2015

• The US steam locomotive driving global economic growth, BHMA Economics 07/15/2013

Knowledge @ Wharton

Why Budget Airlines Are Flying High, Knowledge @ Wharton 06/13/2017