Differentiation to an integer degree is used to make a series stationary. However, fractional differentiation allows the exponent to be a real number. This helps to preserve memory.
Research Topics:
- To train a machine learning model, we usually need a labeled dataset. In the world of finance, this involves creating a matrix of features, $X$, and an array of labels or values, $y$. In this blog, we'll delve into various methods of labeling financial data.
- You might have noticed that many financial models rely on the assumption that data points are independent and identically distributed (IID). However, this is often not the case in real-world financial applications.
- In traditional settings, cross-validation is an effective tool for evaluating a machine learning model's performance. However, the complexities of financial data pose unique challenges.
- When dealing with a set of training observations and outcomes, you would want to estimate a function that closely matches the true function.