On July 29, 2026, Data Investment Institute under BGU FinData (bgudata.cn) announced the official launch of the practical course "Behavioral Finance and Investment Decision". This course is designed for beginners, systematically covering core theories of behavioral finance and using real market data to help students identify and overcome common psychological biases in investing, thereby building a more rational decision-making framework.
Why Behavioral Finance?
Traditional finance assumes market participants are fully rational, but in reality, investors are often influenced by emotions, cognitive limitations, and social factors, leading to systematic decision errors. For example, investors may overtrade due to overconfidence, or sell profitable stocks too early and hold losing stocks too long due to loss aversion. These biases not only affect individual returns but also cause market anomalies at the macro level, such as excessive volatility and herding effects. Behavioral finance is the discipline that studies these irrational behaviors and their impact on financial markets.
A spokesperson for Data Investment Institute said: "Previously, our courses focused on quantitative analysis, data collection, and other technical aspects. However, many students reported that even after mastering the tools, they still made wrong decisions in practice due to psychological factors. Therefore, we decided to integrate behavioral finance into the curriculum to help students improve their investment capabilities from both 'psychological' and 'data' perspectives."
Course Content Overview
The course is divided into six modules covering key areas of behavioral finance. Each module includes theoretical explanations, case studies, and data backtesting practice:
- Module 1: Overview of Cognitive Biases — Introduces representativeness bias, availability bias, anchoring effect, etc., and uses questionnaires for students to assess their own bias tendencies.
- Module 2: Overconfidence and Trading Behavior — Analyzes how overconfidence leads to high-frequency trading and risk misestimation, and validates its impact using account data.
- Module 3: Loss Aversion and Disposition Effect — Uses investors' portfolio data to demonstrate the existence of the disposition effect and discusses how to overcome it through stop-profit and stop-loss discipline.
- Module 4: Herding Effect and Market Bubbles — Reviews famous historical bubble events (e.g., the 2000 tech bubble) and uses fund flow data to identify herding behavior.
- Module 5: Behavioral Finance and Quantitative Strategies — Introduces how to use behavioral biases to build reversal strategies, momentum strategies, etc., and provides Python code implementation.
- Module 6: Cultivating Rational Investment Habits — Combines psychological tools to teach how to create investment checklists, set decision rules, and reduce emotional interference.
Real Data-Driven Teaching
Unlike theoretical behavioral finance courses on the market, Data Investment Institute fully utilizes the massive financial data on BGU FinData platform, equipping each module with data experiments. For example, in the "Disposition Effect" module, students can download historical trading data of a stock and use a Python script to calculate the average holding time for winning vs. losing stocks, intuitively experiencing the bias. The course also provides a backtesting framework for students to verify the performance of behavioral finance-based strategies over the past 10 years.
"Data is the best tool to test theories." said Dr. Li, the lead lecturer and behavioral finance researcher. "By analyzing data firsthand, students will discover that even those considered perfectly rational also commonly exhibit similar biases. This cognitive shock is often more profound than just listening to lectures."
Target Audience and Learning Method
This course is suitable for all beginners interested in investing, even without prior background in finance or programming. It adopts a hybrid model of recorded video lectures, live Q&A, and community discussion. Students can enroll anytime on the Data Investment Institute website (bgudata.cn) and rewatch unlimitedly within one year. Those who complete all assignments and pass the exam will receive an electronic certificate from BGU FinData.
Since its inception, Data Investment Institute has launched a series of courses including financial data collection, quantitative modeling fundamentals, and backtesting framework construction, serving over 50,000 students. The addition of this behavioral finance course further improves the end-to-end education system from data acquisition, analysis, and modeling to psychological management, helping investors make better decisions in the data era.
Expert Opinions
Professor Wang from the Department of Financial Engineering at South China University of Technology commented: "Behavioral finance is the bridge between theory and practice. Many students master advanced quantitative techniques but still lose money because they cannot manage their own psychology. This course at Data Investment Institute combines psychological biases with data validation, a meaningful attempt. I recommend all financial data learners to explore this field."
Additionally, the course invites several senior fund managers to share practical cases, describing how they use behavioral finance principles to design stock selection models and risk control rules. A student in the internal test reported: "After learning this course, when I see a stock price surge, my first reaction is no longer to chase the rally but to consider whether it's a herding effect. This mindset shift is immensely valuable to me."
In the future, Data Investment Institute plans to develop advanced behavioral finance courses, focusing on deep learning applications for identifying psychological patterns, and collaborate with universities on investor behavior research. For the majority of investors, in today's increasingly homogeneous technology landscape, psychological advantage may be the key factor determining success or failure.
