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Continue reading →: Taming Volatility: High-Performance Forecasting of the STOXX 600 with H2O AutoMLForecasting financial markets, such as the STOXX Europe 600 Index, presents a classic Machine Learning challenge: the data is inherently noisy, non-stationary, and highly susceptible to sudden market events. To tackle this, we turn to Automated Machine Learning (AutoML)—specifically the powerful, scalable framework provided by H2O.ai and integrated into the…
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Continue reading →: Integrating Python Forecasting with R’s TidyverseIn this article, we executed a successful integration of a non-standard Python forecasting model into the R Tidyverse/Tidymodels framework, primarily leveraging the reticulate package. 1. The Objective (The Challenge) The goal was to utilize a powerful, custom Python model (nnetsauce‘s MTS wrapper around a cyb$BoosterRegressor) and integrate its outputs—predictions and…
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Continue reading →: Nested Forecasting with Spark: Blockchain ETF TrendsBitcoin hit an all-time high of $125,664 on October 5. This increase was fueled by a historic net inflow of $3.24 billion into spot Bitcoin ETFs and rising public demand. In this article, we will predict the trend of two blockchain ETFs using nested forecasting with the Spark backend. I…
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Uncertainty Analysis: Gold vs. Bitcoin
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Continue reading →: Uncertainty Analysis: Gold vs. BitcoinDeutsche Bank Research Institute stated in its published report that Bitcoin has undergone a process similar to what gold experienced over the past 100 years. According to the report, Bitcoin’s increasing adoption and reduced volatility may transform it into a reserve asset that central banks could hold by 2030. The…
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I’m Selcuk Disci
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