Exploring Circular and Iterative Calculations in Equities and Implementing AI in Sports Statistics
The State Changers had a complex discussion where they tackled the problem of how to iterate through computations, bringing in templates from Excel, and understanding where bottlenecks were happening in their process. The discussion moved between different topics including conceptualizing formulas for financial calculations, transferring these operations into coding languages like Python, making use of no-code solutions like Xano, and understanding different mathematical concepts like gradient descent, chain rule, and solver functions in Excel. In solving the iterative calculation problem, a suggestion was to create a while loop where the break point is when the difference (or error) between the computed and target output approaches close to zero.
Moreover, a part of the discussion covered how to debug and optimize background tasks for sports data that timed out due to high load. It was suggested to create an event log to track the function process and identify at which step it times out. The meeting provided insights into how complicated mathematical models could be integrated into software to solve financial and data processing challenges. Concepts discussed included machine learning, iterative calculations, API connections and gradient descent.