![]() Why did you decide to pursue the quantitative finance major and what advice do you have for someone considering this path? Wharton Major/Program: Quantitative Finance Previous Experience: Coastal Engineer at Moffatt & Nichol Previous Education: University of California, Berkeley, BS Civil Engineering Stanford University, MS Civil Engineering I believe I have the requisite tools to get me started. I want to be at the forefront of infrastructure investments in Africa. I believe a good grasp and understanding of investments, especially around the application of financial tools and techniques for infrastructure investors, is key to unlocking the African economy for unprecedented growth. Why did you decide to pursue the quantitative finance major? It’s really opened my mind to the world of finance and now I believe I can understand technical topics that I never understood before Wharton. I’m surrounded by incredibly brilliant colleagues and faculty, who share their perspectives on finance and key trends. What has your Jacobs Scholars Program experience been like so far? Wharton Major/Program: Quantitative Finance and Operations, Information, and Decisions Previous Experience: Started at Procter & Gamble as a Process Engineer before joining McKinsey & Company where I served corporate clients across Africa and NA Previous Education: Imperial College London, MSc in Advanced Mechanical Engineering We spoke with six inaugural Jacobs Scholars to learn more about why they decided to major in quantitative finance, how it has impacted their academic experience, and what they hope to accomplish in the future. Wharton’s new major provides the opportunity to explore this vitally important field.” It’s imperative that future business leaders have a basic understanding of quantitative finance. “Innovations created by quantitative finance contribute meaningfully to global economic growth and will continue to do so at an increasing pace. Jacobs, G’79, GRW’86, co-founder of Jacobs Levy Equity Management, whose gifts to Wharton bolstered the new quantitative finance major by creating a professorship and a Scholars initiative for top students in the program. “Finance, much of it quantitative, fuels the world’s economy,” said Dr. The major allows students to dive into financial economics and data analysis while also gaining the leadership and communication skills that are at the heart of the Wharton MBA experience. Machine learning and AI re also areas of growing importance in this field.Launched in 2020, Wharton’s quantitative finance major brings together students from a variety of academic backgrounds, such as computer science, engineering, and technology, and prepares them for successful leadership roles in finance. Time Series Analysis is also key to analyzing financial data. Necessary Skills: command of programming languages used in statistical modeling, such as Python and R, ability to work with large sets of financial data, and strong quantitative analysis skills. Data Scientists are increasingly using machine learning, clustering algorithms, and artificial intelligence to identify unusual data patterns. Data Scientists work in many data driven companies, such as investment banks, asset management firms, and technology companies. Their roles typically focus on risk management and predictive analytics. Professionals in this area work on data mining, gathering data sets, and deriving insights from these data sets. Sample of Employer Partners in this area:Īs financial institutions further integrate the practice of collecting and analyzing data to gauge profit, loss, and client satisfaction, data science continues to be the fastest growing area of quantitative finance. In addition, traders must possess the ability to thrive under pressure, maintain focus despite long hours, withstand an often competitive/intense environment, and respond well to failure. It also requires the knowledge of statistical analysis, numerical linear algebra, and machine learning processes. ![]() Ability to navigate price indexes, such as SPX and VIX. ![]() Necessary Skills: a strong background in programming skills in Python, C++, SQL, R, and/ or Java. Quantitative trading techniques also include high-frequency trading, algorithmic trading and statistical arbitrage. If the strategy yields profit, it is then applied onto real-time markets to implement an automated trading process. Traders analyze market data, such as price and volume, and use mathematical and statistical models to identify and execute trading decisions that may involve hundreds of thousands of shares and securities.Ī trader develops a strategy and applies the model to historical market data so that it can be back-tested and optimized.
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