Description:

Algorithmic Trading is a term that has been in the limelight since the pandemic. Many people are familiar with it, but they may not fully understand how it works and what factors to consider when building trading algorithms.

There are several issues surrounding algorithmic trading:

• People find algorithmic trading to be a very complex term, which is not the case once they grasp its fundamental concepts.
• People may be hesitant to trust algorithmic trading due to the fear of potential losses outweighing potential gains.
• Most individuals are not familiar with the production process of a trading strategy/algorithm and the steps it needs to go through for successful implementation.
• It is possible to integrate Language Models like ChatGPT using Langchain or other Python libraries to enhance algorithmic trading strategies and increase profits.

In my 30-minute talk, I will explain the concepts of algorithmic trading, how it works, and address the concerns mentioned earlier. As someone who has been working as a developer in the backtesting system of a crypto-trading platform for one year, I have gained insights about the ecosystem of algorithmic trading.

Through algorithmic trading, traders and investors can automate their trading and investement strategies and optimize their portfolio using exchange APIs. This automation allows for accurate analysis and trade placement. But it isn't as easy as it sounds. One should need to know the whole workflow of how a strategy or an algorithm comes into picture.

Key Takeaways:

1. Algorithmic trading automates investment strategies, allowing for accurate analysis and trade placement through exchange APIs.
2. Algorithmic trading can be complex but becomes more understandable once the fundamental concepts are grasped.
3. Address concerns about algorithmic trading by emphasizing risk management, thorough backtesting, and responsible implementation.
4. Integrating language models like ChatGPT can enhance trading/investing models and improve decision-making.
5. Python libraries and tools facilitate the integration of language models in algorithmic trading strategies.
6. Utilize AI-driven strategies responsibly to generate profits and stay curious about advancements in the field.

Integrating Language Models like ChatGPT can further enhance the accuracy of trading models. During the talk, I will explain how this integration can be achieved and share my experiences in understanding this complex topic at a young age of 15. I will also discuss how algorithmic trading can be effectively utilized to generate profits. Additionally, the talk will cover the rapid growth of Artificial Intelligence (AI) and its impact on people, especially in the context of algorithmic trading.

Prerequisites:

I expect that participants have a basic knowledge of -

• Python
• Data Analysis
• Financial Markets
• Artificial Intelligence
• ChatGPT
• Prompt Engineering

Content URLs:

Slides will be available soon, but this is the breakdown of the content during my talk -

1. About Algorithmic trading (3 mins)
2. Misconceptions in Algorithmic trading (2 mins)
3. Complete workflow of strategy coming into production (3 mins)
4. Overcoming Trust Issues (2 mins)
5. The role of backtesting in minimizing potential losses (3 mins)
6. Inroduction to integrating Language Models in Python apps (5 mins)
7. Examples include a stock analyser and some backtesting work (3 mins)
8. My Experience and Insights (2 mins)
9. Conclusion (2 mins)
10. Q&A session (5 mins)

Speaker Info:

Gaurav Lahoti is a Data Scientist with over a year of experience in development and testing activities. He is proficient in analyzing and manipulating data using Python. Additionally, he possesses extensive expertise in frontend technologies, including ReactJS, HTML, and CSS. On the backend, he has substantial experience in processing data from CSV files provided by servers and APIs. He has also served as a developer for backtesting systems in both Cryptocurrency and Commodities domains. Moreover, he has contributed to the UI development of a crypto-trading platform. His primary focus lies in gathering data from various crypto exchanges, particularly Binance, and subsequently processing, cleaning, and manipulating the data.

Speaker Links:

• LinkedIn