The First Post: WHY I DO CODING
The story about how I got interested in coding
Discovering the Power of Coding: An Exchange Student's Tale
Reflecting on my journey, the seeds of my fascination with computer science were planted during my exchange student year in 2014. I was studying behavioral finance at Singapore Management University (SMU), and the crux of our main project was identifying anomalies in global stock markets and exploring certain renowned irrational phenomena.
Excel Skills Put to the Test
Back then, I prided myself on my advanced Excel skills. During my military service, I had created a complex Excel file to measure the fitness levels of over 20,000 soldiers, adjusting grades according to their respective age groups. I was pretty confident that I could replicate this technique for my behavioral finance project.
However, dealing with financial data turned out to be a different beast. I had to create numerous temporary tables, transpose datasets frequently, and somehow ended up with an unwieldy Excel file. Despite my best efforts, the result was far from perfect. I found myself constantly recalculating returns and creating various reference tables for different time intervals. I shared these struggles during a mid-term check-in with my project team.
The Revelation: The Power of Python
Our team was a diverse mix of five, including two SMU students and three exchange students like myself. One of the exchange students offered to handle my problem, saying he could sort it out in just a couple of days. I was skeptical at first - he hadn't contributed much to the project so far, so I doubted his abilities.
To my surprise, he delivered. Using Python, he effortlessly compared price movements at various intervals, from one day to a year after an event. Looking back, it was just simple matrix and vector manipulation, but it was a pivotal moment that profoundly changed my perspective on technology and coding.
Embracing Coding: A Decision That Changed My Life
When I returned to my university, I was in my senior year and job hunting was on the horizon. However, I realized that without a solid grasp of computer science and coding, I would always be dependent on others. I felt a pang of embarrassment thinking about my major in financial engineering. I was theoretically proficient, but I lacked the practical skills to be truly self-reliant.
I've always believed in the importance of fundamentals, perhaps a philosophy ingrained in me through practicing Judo. And so, I made the decision to self-study computer science, replicating an undergraduate curriculum. While most of my peers were taking it easy in their senior year, I was pushing myself harder, dedicating almost 80% of my day to learning in the library.
The Payoff: A Victory with VaR
Admittedly, it was a challenging journey. Self-study often left me lost and making mistakes without guidance. However, the fruits of my labor showed themselves even before I graduated. In an advanced risk management course, I employed a bootstrap method to run simulations for a project on Value at Risk (VaR) for hypothetical financial institutions. This involved comparing randomly selected asset groups and adjusting portfolios, all achieved with the help of VBA. The experience was both gratifying and defining.
Staying Ahead of the Curve: A Commitment to Continuous Learning
Since then, I've made it a point to stay updated with the ever-evolving field of computer science. While my primary expertise is finance, I firmly believe that being technologically literate is indispensable for staying competitive in the future.
This realization led me to leave my previous job and pursue an MBA at Tepper, known for its strong emphasis on computer science and engineering. I was fortunate to work on numerous projects at Tepper, interacting with many engineers and going beyond the typical MBA experience.
The Future of Finance: Data Handling and Privacy
In this era of digital finance, data handling has taken on a new level of importance. Data privacy concerns and tighter regulations have made efficient and ethical data management a critical skill set. This applies not just to the realm of financial simulations in trading, but also significantly extends to corporate finance and financial analysis, the area where I envision my future career.
High-quality data handling enables more accurate simulations, bolstered by real market data. These simulations provide a quantifiable foundation for decision making, guiding strategic initiatives and future projects. Having the ability to manipulate and interpret this data, while respecting privacy guidelines, is an invaluable asset.
As a financial analyst, you need to be armed with reliable data and the ability to interpret it effectively. This forms the basis for benchmarking performance, monitoring trends, and ultimately providing strategic financial guidance. An analyst equipped with advanced data handling skills will not only be able to provide more accurate and comprehensive advice, but will also be able to foresee potential opportunities and risks, offering a competitive advantage.
Moreover, with the increasing importance of data analytics and machine learning in finance, being adept at handling large datasets can be a game-changer. It opens up opportunities for developing predictive models and data-driven strategies, giving companies an edge in the competitive financial landscape.
What's Next: Sharing My Journey
Going forward, I'll be sharing more about my journey, focusing on how I've applied technology and financial knowledge to real-world business scenarios. Stay tuned for updates on various tasks and projects, and join me as I navigate the intersection of technology and finance. I hope to inspire others with my story, and demonstrate the powerful role of computer science in shaping our future.