Eureka Program

Introduction to Quantitative Research

Frequently Asked Questions

Program Dates and Location

Eureka Introduction to Quantitative Research Program Overview

Step-by-Step Program Guide

Course Requirements

Completing a research project or research paper in this program is optional. All students in this program must create a Final Presentation Video, which will clearly document their research journey, highlight their key findings, detail the skills they have developed, and share how they intend to apply their knowledge in their academic pursuits.

Where Can Course Knowledge Be Applied?

This course will equip students with quantitative research skills that are foundational and versatile, enabling them to excel in these fields:

Finance
Economics
Mathematics
Data Science
Cybersecurity
Computer Science
Machine Learning
Artificial Intelligence
Cryptocurrency
Asset Management

Eureka Alumni Outcomes

Past students who have participated in the Eureka Economic and Finance Programs have achieved outstanding academic and career outcomes! Previous Alumni have secured positions and acceptances to the following firms/programs:

LinkedIn: Software Engineer Intern
Goldman Sachs: Virtual Insight Series Participant
Credit Suisse Steps to Success: Explore Program
Nomura: 2022 Freshman and Sophomore Diversity Program Participant
Morgan Stanley: 2022 Early Insight Program Participant
Yale Center for Environmental Law & Policy - Research Assistant for Yale Initiative on Sustainable Finance (YISF)
University of Chicago: Pathways in Economics (Summer Program)
Davidson College: Research Intern for Economics Professor
Dongxing Securities: Investment Banking Summer Analyst
Lead Capital Partners: Private Equity Intern
52 Capital Partners: Investment Banking Intern
CE Innovation Capital: Investment Analyst Intern
Monad Ventures: Web3 Extern

These examples highlight the wide range of options that Eureka students have upon completion, allowing them to explore various industries and pursue careers in fields they are passionate about.

Students who complete this program are encouraged to explore internship opportunities found on our Partnerships page. These opportunities offered by our partner organizations, provide valuable real-world experience and a chance to apply the skills learned during the program in professional settings.

What Alumni Have Accomplished

Eureka Economics and Finance alumni have received college admission offers to Princeton University, Yale University, University of Pennsylvania (UPenn), University of Chicago, John Hopkins University (JHU), and other top US universities.

The research experience and skills students receive at the Eureka Program have helped students get accepted to programs such as the MIT - LaunchX Entrepreneurship Summer Program, The Wharton School - Leadership in the Business World, and other top summer programs.

Many students from this program are also very engaged in their communities, sharing in volunteering activities and starting non-profit organizations to help the community. During COVID-19, several students have started organizations to help obtain and distribute health supplies. Many alumni from this program have received top awards like the Scholastic Art & Writing National Awards, U.S. Presidential Scholars Awards, and many others.

The below sections will provide more insight into the students who have attended this program and share their experiences and successes.

Certificate of Completion

Upon successful completion of this course, students will be award a Certificate of Completion. This certificate stands as a testament to the student's dedication, commitment, and accomplishments in research

Colleges Eureka Students Have Been Accepted to

Attended Eureka

High School Name

Admission Offer Received

Eureka Research Title

2022 Summer

The Webb School

• University of California - Berkeley (UCB)

The Appropriate Credit Rating For Indonesia In 2023 Is Going To Be Between 69.5 And 38.3

Attended Eureka

High School Name

Admission Offer Received

Eureka Research Title

2022 Summer

The Hotchkiss School

• University of Texas at Austin

Finance Group Paper - Title Undisclosed

Attended Eureka

High School Name

Admission Offer Received

Eureka Research Title

2021 Summer

Phillips Academy Andover

• Case Western Reserve University (EA)

Investment Banking Conferences And Their Impact On Stock Price

Eureka Alumni Research Projects

Challenges in Applying the 'Lazy Prices' Mechanism for Alpha-Generating Stock Portfolios in the Chinese Market

Student S.'s* paper examines the applicability of the "changers vs. nonchangers mechanism" from Lazy Prices—an established U.S. stock market strategy—to forecast the performance of Chinese stocks. Despite its success in the U.S., he addresses various challenges specific to the Chinese market. Factors such as the substantial involvement of the Chinese government in stock ownership, potential influence on financial reporting, and regulatory interventions present obstacles. Additionally, the tightly regulated short-selling market in China complicates the feasibility of shorting "changers." The paper proposes potential remedies, such as selling information to institutional investors, but acknowledges the intricate nature of evaluating the strategy's effectiveness in the Chinese context. Given these complexities, a case-by-case analysis is imperative to gauge the strategy's potential in generating alpha in the Chinese stock market.

The Influence of Investment Banking Conferences on Stock Prices

Student N.* worked with his professor to research the influence of investor inattention and how conferences exploit this phenomenon, resulting in significant short-term impacts on stock prices. This paper thoroughly examines three examples, including an empirical study on Goodyear stock, to understand how conferences, and sharing crucial financial information, impact stock prices. Despite the challenges of interpreting non-textual and number-based conference information, their influence on stock prices is evident. The study emphasizes the need for deeper exploration into conference dynamics and their impact on market behavior. While establishing a link between conferences and stock price fluctuations, the paper advocates for a more detailed analysis, especially in categorizing conferences for nuanced assessments of positive and negative impacts. It also recommends using a Fama French Regression model to pinpoint factors contributing to significant conference impacts, enabling more precise investor reactions. In essence, the research underscores conferences' significant role in shaping stock prices and outlines avenues for future exploration in this domain.

Investors' Differential Reactions to Earnings and Sales Surprises at Growth Firms vs. Value Firms

Student L.* conducted a study that delves into the nuanced market reactions to revenue and earnings surprises, particularly examining variations between value and growth companies. While prior research has established a positive association between both revenue and earnings surprises and subsequent three-day returns, this study unveils distinct reactions based on the company's growth stage. Investors exhibit a notably stronger response to sales surprises in growth firms compared to value firms. Additionally, for value companies, investors display a greater indifference between revenue and earnings surprises than in the case of growth companies. These differential market reactions have significant implications for financial statement analysis, suggesting the need for tailored approaches when interpreting earnings surprises based on a company's growth classification. Researchers studying earnings quality and management can leverage these findings to enhance their analyses.

Risk and Loss Behavior Amidst the COVID-19 Pandemic

In Student W.'s* Project, he challenges the conventional belief in the stability of people's preferences over time by directly assessing preferences in the aftermath of the COVID-19 pandemic. Examining individuals significantly affected by the pandemic, and experiencing adverse financial effects, the research reveals a shift towards increased risk aversion in uncertain gains and heightened risk-seeking behavior in uncertain losses. The findings contradict traditional utility functions with a single risk parameter but align with a behavioral risk aversion model across gain and loss domains. Participants displayed decreasing loss aversion over the pandemic's duration, coupled with a reduced willingness to take financial and health risks. Demographic variables emerged as influential factors in shaping risk preferences and loss aversion. This study challenges the assumption of stability in preferences, offering new insights and prompting future research avenues in understanding the dynamic nature of individual preferences, particularly in the context of significant societal events like the COVID-19 pandemic.

Student G.* explores the connection between financial analysts, growth and value firms, and market reactions to earnings surprises. The study employs a range of variables, including seasonal random walk earnings and sales surprises, three-day return surprises, and book value equity. The results indicate that revenue surprises positively correlate with size-adjusted returns, while expense surprises show a negative correlation, with the sales surprise coefficient's magnitude surpassing that of the expense surprise coefficient. The paper analyzes three-day return quarterly sales surprises for growth and value firms, shedding light on the nuanced impact of positive and negative surprises on stock prices. The study draws insights from data on Pepsi and Coca-Cola to provide valuable findings on market reactions to earnings surprises.

Student Y.* explored Reinforcement Learning (RL), a subset of machine learning, examining its role in optimizing decision-making by maximizing rewards and minimizing penalties. RL, rooted in optimal control and trial-and-error animal learning, incorporates Temporal Difference Learning (TD). In finance, RL is applied in trading bots, risk optimization, and portfolio management. Examples illustrate RL's efficiency gains, risk reduction, and increased Return on Investments (ROI). Despite challenges like feature/reward design and parameter impact, RL's potential extends to predicting stock prices and automating financial decisions. The growing focus of the financial industry on RL implies ongoing exploration and the emergence of new models.

What is Quantitative Finance?

Quantitative Finance, also known as Mathematical Finance or Financial Engineering, is a field that utilizes mathematical models, statistical techniques, and computational tools to analyze and solve financial problems. This discipline employs mathematical models, statistical techniques, and computational tools to analyze market trends, risk factors, and investment opportunities.

In our dynamic world increasingly centered around data, quantitative research plays a pivotal role not only in finance but also in areas such as computer science and data science. Quantitative techniques use evidence-based and structured frameworks to tackle difficult problems in these areas. Its applications span various realms, encompassing Machine Learning and AI, Software Engineering, Cybersecurity, Data Analysis, Predictive Modeling, A/B Testing, Big Data Analytics, and beyond!

Quantitative Finance Career Options

In today's rapidly evolving world, the demands of different fields are merging to create new opportunities for success. Business, finance, computer science, and data are converging to meet mutual needs, and those who recognize and adapt to this changing landscape are poised to thrive. A degree in Quantitative Analysis is becoming a highly versatile qualification, providing individuals with a wide range of career opportunities in this dynamic landscape. Career opportunities with a Quantitative Finance Degree include:

Quantitative Analyst
Risk Analyst
Asset Management
Actuary
Quantitative Developer
Software Engineer
Data Scientist
Credit Risk Analyst
Financial Machine Learning Engineer

Quantitative Finance Career Opportunities and Salaries

Quantitative Finance careers provide lucrative and rewarding opportunities, consistently placing professionals in this field among the highest-paid in finance. Salary amounts may vary depending on factors such as education, experience, location, and the specific industry or employer, but often these amounts range from mid-six figures to well over a million for seasoned experts in the field.

To establish a presence in financial engineering, seeking internship opportunities is essential, as reported by Business Insider. According to Levels.fyi, a platform that provides information about compensation levels and job roles within various technology companies, the median salary for Quant Interns on Wall Street is $111.00 per hour, with some interns receiving an average monthly pay as high as $22,817.00, with additional benefits.

Highest Paying Firms for Quant Internships

Highest Paying Firms for Quant Finance Internships (Source: Levels.fyi)

More About Quantitative Finance

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Introduction to Quantitative Research

What is Quantitative Finance?

More About Quantitative Finance

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