DataHour: Wavelet Analysis for Macro-Casting Under Uncertainties
DataHour: Wavelet Analysis for Macro-Casting Under Uncertainties
23 Apr 202413:04pm - 23 Apr 202414:04pm
DataHour: Wavelet Analysis for Macro-Casting Under Uncertainties
About the Event
Macro-casting, pivotal in economic policymaking, has gained significance as a communication tool for central banks. Despite the complexity of macroeconomic variables like inflation, GDP growth, and exchange rates, generating reliable predictions is challenging due to their nonlinear and unpredictable nature. Additionally, uncertainties such as economic policy and geopolitical risks further complicate long-term projections.
Wavelet analysis offers promise in deciphering financial data by extracting crucial information and detecting significant signals. A new approach, the Filtered Ensemble Wavelet Neural Network, shows potential in forecasting macroeconomic variables. We'll explore its application, along with smart feature engineering practices and the Conformalized Prediction Interval, which addresses uncertainty in machine learning predictions for time series forecasting.
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
Who is this DataHour for?
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
About the Speaker

Shovon Sengupta is a distinguished expert in the field of data science, specializing in advanced predictive analytics, machine learning, deep learning, and reinforcement learning. As the Principal Data Scientist at the AI Center of Excellence for Fidelity Investment in the United States, Shovon is at the forefront of driving innovative initiatives that leverage artificial intelligence (specifically on Generative AI) to solve complex business challenges. Shovon holds a US patent: Automated Predictive Call Routing Using Reinforcement Learning.
Shovon is also a Ph.D. scholar specializing on the application of machine learning algorithms in the realm of Finance. Shovon's primary research interests include deep reinforcement learning, deep learning, natural language processing, knowledge graphs, causality analysis, and time series analysis. His dedication to advancing the field of data science is evident in his continuous pursuit of knowledge and innovation.
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