Andrea Amato obtained his Master of Science in Finance and his Bachelor degree in Economics and Finance cum laude from Bocconi University. In his Master's final thesis, he constructed a set of trading strategies on the commodity futures market and studied their past performances employing advanced econometric techniques that allowed for the presence of multiple and unobserved regimes in the model's dynamics. During his internship at Unicredit Bank, on its equity derivatives trading desk, Andrea focused on the monitoring, pricing, booking, and P&L reporting of both plain and complex equity-linked products. Andrea is passionate about research. While working at CAREFIN, a research center in applied finance at Bocconi University, and when he was a Ph.D. student at USC, he took part in several research projects, either as a research assistant or as co-author. These projects focused on different aspects of the financial research spectrum: from the pricing effect of the introduction of a new legal clause in government bonds' term sheets to a deep investigation of the proxies for illiquidity in the American stock market. Andrea is a passionate runner and swimmer and enjoys good food with the company of his family and friends.
Caleb Brody graduated Summa Cum Laude and Phi Beta Kappa from Rutgers University in 2014, at the age 20, with a degree in Applied Mathematics. He was awarded the Charles Pine Award for "outstanding scholastic excellence in the areas of physical science and mathematics". During his summers Caleb interned at Fairless Hills Credit Union working with the CEO and COO to automate the preparation of financial statements via VBA and SQL. Upon graduation, Caleb worked as a Global Cyber Security Analyst for Citigroup where he demonstrated exceptional skills in mathematical modeling and prediction. His work culminated in the creation of an automated computer model designed to detect changes in the flow of internal network traffic indicative of a hacked or otherwise compromised machine. After several successful mitigations the model is currently in the process of being filled for patent. During his time at Citi, Caleb's role frequently required him to meet in person with traders and Quants in order discuss specific data retrieval requirements of a functioning trading floor. Leveraging the exposure to trading provided by this experience, Caleb later worked on the Derivative Trading team for the Canadian Industrial Bank of Commerce. Caleb decided to join the Berkeley MFE program to enhance his formal financial and quantitative knowledge. Caleb enjoys hiking, camping and competing in A.I. programing competitions for chess and poker. He is currently ranked 1400 by the World Chess Federation (FIDE).
Yixing Cai obtained a Bachelor's degree in Economics and a Research Master's degree in Finance at Tilburg University in the Netherlands, where she acquired in-depth training in statistics, econometrics and finance. In her master's thesis, she modelled firms' patent litigation risk with a two-stage logistic model. She used word matching algorithms and constructed a dynamic dataset that covers financial, patent and legal information for all US publically traded firms. The model was tested on this data set and yielded significant results. During her last year of study, Yixing joined Danone as a media analyst trainee. She took leadership in reporting and analyzing global marketing and media activities, worked together with regional teams, media agencies and the global director to build the global media strategy. She then interned in the investment banking unit at XiangCai Securities in Shanghai, where her key responsibility was researching, producing industry reports and exploring M&A possibilities. Yixing also completed PDE and numerical analysis courses under the Master of Applied Mathematics at Delft University of Technology. She is highly interested in machine learning and knows several programming languages. In her spare time, Yixing enjoys singing, travelling and diving.
Marcela Cervini holds a Bachelor of Science degree in Applied Mathematics from Instituto Tecnológico Autónomo de México. For her thesis, she studied portfolio allocation in a practical way, developing and implementing a semi-variance model for Mexican stocks. The model resulted in considerable outperforming returns against its benchmark. This research project led her to apply her modeling and programming skills to show the benefits of implementing quantitative finance techniques in Mexico. Before graduating, she joined the quantitative team at Scotiabank, Asset Management, Mexico, where she used mathematics, statistics and programming (VBA) to create asset allocation optimization models and other tools aimed at improving portfolio performance and developing new investment strategies for funds. She then enrolled in a post-graduate specialization program in investment analysis, which led her to transition to HSBC Global Research, LatAm fixed income. Her experience at HSBC provided her with a more insightful view of FI markets. She combined economics concepts with her statistics knowledge to develop tools that could easily identify investment opportunities within the region, while contributing to the elaboration of research reports for global clients. Marcela enjoys sports, such as softball and indoor rock-climbing, painting, traveling and visiting art museums.
Will Chen graduated from Tsinghua University with a Bachelor's degree in engineering. He then joined Purdue University and earned his Master and PhD degree in Mechanical Engineering there. While at Purdue, he took classes in finance and management related subjects and earned the "Applied Management Principles" Certificate from Purdue's Krannert School of Management. His PhD thesis mainly focused on modeling and experimental design of semiconductor nano materials for LED and Solar Cells. Will designed molecular models and then wrote MATLAB code to combine density functional theory with numerical iterative methods to calculate the fundamental electronic properties. After graduating from Purdue, Will joined Western Digital and started using his simulation and experimental skills in tribology-related areas. He designed numerical models to mimic thermal and mechanical interactions between magnetic head and media. Will also designed and implemented MATLAB functions to automate the data analysis for large quantities of experimental data.
Wenyu Chen graduated from Nanjing University with a bachelor's degree in financial engineering where he established solid statistical analysis and programming skills in Python and MATLAB. Post graduation, Wenyu worked for three quantitative hedge funds as a quant trader in China. He implemented market neutral strategies based on Barra risk model to fix risk exposure and backtested abnormal alpha in event driven strategies. Meanwhile, Wenyu designed trend following and calendar spread arbitrage on multiple commodity futures. During his work experience, he came through the whole Dev-UAT-Prod process and achieved Exchange's API through callback functions to receive market data, send commands and get trading responses. Wenyu used MongoDB to set up database for inserting and updating the Order, Trade and Position information in living trading and set up SQL Database to store stock market data in panel structure and Index constituent data. He also wrote some easy-to-use scripts to achieve web data scraping and helped build up a back-testing, virtual trading, and live trading platform based on observer pattern. In his spare time, Wenyu likes playing soccer, badminton, and board games.
Jen-Chieh Cheng earned a B.B.A in Finance and completed the Quantitative Financial Analyst program from National Taiwan University. During his undergraduate studies, Jen-Chieh received rigorous training in finance and math. He gained practical experience in risk management, fixed-income trading, and debt capital raising during his internship at UBS and employment at Yuanta Bank. He also worked as a trader at BlackRock Taiwan, where he managed trade flows for onshore business across asset class and supported portfolio construction. Later, he worked at WageCan Inc., a Taiwanese fintech startup focusing on blockchain payment solutions; he conducted research on clients' flow and Bitcoin spot/future price. Passionate about data analytics, Jen-Chieh initiated independent research by implementing machine learning algorithms and natural language processing techniques. Jen-Chieh is also a certified FRM. In his spare time, Jen-Chieh enjoys swimming, jogging, biking, and solving open data challenges.
Ling Yu (Kelvin) Cheng completed his Bachelor degree in Mathematics (with specialization in Actuarial Science) from CUNY Baruch College in 2012. Upon graduation, he passed three actuarial science exams (P, FM and MFE) and earned the certificate of Oracle certified professional Java SE 6 Programmer. He joined the Risk Analytics department within Citigroup as a model developer, where he primarily focused on the implementation of the Wholesale Credit business line models for Comprehensive Capital Analysis and Review stress testing by using Java, Python, C++, SQL and Linux shell scripting. During his time at Citigroup, Kelvin obtained risk management skills and acquired the FRM designation. He later worked at Société Générale as a quantitative advisor in the model validation team where he performed independent conceptual and theoretical review, benchmarking, sensitivity analysis and independent implementation of the models employed across the region of Americas. Kelvin also passed the CFA level I exam. Kelvin is very interested in the fintech and data science industry. In his leisure time, he enjoys photography, biking, gaming and reading.
Manoj Cherukumalli completed his Bachelor's and Master's degree in Electronics from the Indian Institute of Technology, Kharagpur. Upon graduation, he worked at Oracle in the financial services department developing software applications for risk departments in banks. He later received his MBA degree from the Indian Institute of Management, Lucknow specializing in Finance and Economics. During his MBA, he worked as an intern in Nomura Equity Research where he worked on initiating research on Indian steel industry. Manoj also worked on an academic project modeling the returns and volatility of 4 Indian banks using ARMA & GARCH models. After graduation, he joined Goldman Sachs Asset Management as an analyst in Fundamental Equity team. During his tenure, he worked with two portfolio managers covering Latin America consumer, European business services and energy companies. He developed financial models used for equity valuation and also created custom templates for quickly understanding the companies in vast emerging market space. He cleared the CFA Level I in December 2013. Manoj is passionate about cricket, e-sports and technology.
Arundeep Chinta graduated with a Master of Engineering degree from Indian Institute of Technology, Kharagpur. He passed all three levels of the CFA exam and both parts of the FRM exam, and is also pursuing certification from The Institute of Actuaries of India. Prior to joining the Berkeley MFE program, Arundeep worked as a Senior Analyst at Deutsche Bank CIB in the Bond Analytics Team, where he was responsible for Modelling of Cash Flow Models that generate the bond payments to investors of MBS. Prior to Deutsche Bank, Arundeep was at CRISIL Global Research and Analytics, where he worked for the European Credit Strategy of an Investment Bank for two years. He worked on Time series analysis of Excess Returns of Fixed Income Indices using 'R' and was also involved in development and back testing of Trading Model for the London Credit Trading Desk. By intensively analyzing the time series data and testing several scenarios, he improved the quality of the trading signals. He worked on the integration of voice trades into the existing trading model and expanded product coverage. He received the Bright Spark Award of CRISIL GR&A – Financial Research of CRISIL's quarterly Rewards & Recognitions Programme which recognizes exemplary performance by employees.
James Cho graduated from UC Berkeley in 2016 with a BS in Mechanical Engineering and BA in Economics. He developed quantitative skills through projects in vehicle control systems and economic intuition through internships and coursework in Economics. James worked for Goldman Sachs as a gap year intern in macro research. His main role was to conduct macro level analysis on Asia economics and markets. Tasks ranged from drafting data commentaries to managing time-series forecast models using seasonal adjustment tools. In a major project, James assisted revamping the team's proprietary index by adding new sectors and backtesting performance. He also provided monthly sector picks based on macro and industry level indicators. James passed the CFA Level 2 and FRM Part 1 exams and cultivated leadership through a 2-year military experience in Korea.
Martin Cornero received a Bachelor's degree in Finance from Universidad Argentina de la Empresa (UADE) and a Postgraduate degree in Economics from Universidad Torcuato Di Tella. During his undergraduate studies, he developed a solid theoretical and practical background in finance, while his graduate studies trained him in statistics, econometrics, and mathematics. Prior to joining the Berkeley MFE program, he worked for more than three years at Crisil GR&A as a fixed-income research analyst of Latin American banks and Argentinian provinces. At Crisil, he supported the fixed-income research team from a top tier US investment bank. Among his tasks were assisting in periodic reports on bond performance, relative value analysis for bond recommendations and company reviews. Martin is a certified FRM and has passed the CFA level II exam. During his spare time, he enjoys playing tennis, soccer, running and reading.
Vinicio DeSola Jr. graduated from Universidad Simon Bolivar in 2009 with a Bachelor of Science Degree in Production Engineering. During his tenure at El Nacional in Venezuela, he developed new inventory models using Monte Carlo simulations and stochastic variables to predict the demand and the implicit exchange rate (BsF/$) to improve the procurement process. Later, he co-founded several entrepreneurial ventures, where he had been the group CFO and risk manager, trading between Bitcoins and dollars to hedge the inflation risk in Venezuela. He also developed a triangular arbitrage algorithm BTC-Bs-$. Vinicio has also been a private tutor for the last 9 years, having taught nearly 1000 undergrad and graduate students, forming his leadership and teamwork skills. He is currently a Level II CFA candidate, and a CQF candidate. During his spare time, he's a passionate fantasy football player, commissioning a league of his friends. He also enjoys reading fantasy literature and traveling the world with his wife.
Jeffery Ding graduated from Duke University with degrees in Biomedical Engineering and Economics. Previously, he interned at Bosera Funds where he was tasked with assessing the profitability of pairs trading in Chinese markets. He also interned at Macquarie Capital in the private equity group, where he contributed in several acquisition deals through LBO modeling and doing extensive research to understand the fundamentals of a company's operations. After graduation, Jeffery had the opportunity to work as a technical consultant at Epic. There, he was the lead technical resource for large-scale EMR implementation projects. Most recently, he worked as an actuarial consultant for Aon Hewitt, where he helped companies value their pension liabilities and manage their exposure to risk. Jeffery joined the Berkeley MFE program to further develop his financial acumen and quantitative skillset. Since being admitted, Jeffery has taken online courses in linear algebra and differential equations, C, Python, and machine learning to prepare for the program. Additionally, he took graduate-level courses in econometrics, real analysis, and linear algebra at Northern Illinois University and sat for the CFA Level 1 exam in December 2016. In his free time, Jeffery enjoys traveling, practicing tai chi, and building computers.
Fabien Doliger attended ENSAE ParisTech in Paris where he studied Applied Mathematics, Statistics and Economics. He will officially receive his Master's degree from ENSAE upon completion of the Berkeley MFE program. During his second year at ENSAE, Fabien had the opportunity to work on a machine learning project which aimed at predicting offensive strategies during an American Football game through online learning algorithms. Fabien worked for Credit Suisse in London as a Structurer within the Equity Derivatives team. The daily tasks involved the pricing of complex derivatives products, backtesting of strategies and help for the presentation of new product launch. Fabien also interned at Ernst & Young as a consultant in Actuarial services where he enhanced his understanding of insurance linked securities and took part in a Business Intelligence mission regarding markets after Solvency II. He speaks fluent English, French and Spanish. His main hobbies include watching American Football and traveling.