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Continue reading →: Skewness-Managed Portfolios: A Practical Guide with RIntroduction Portfolio construction often relies on mean–variance optimization or factor models. Yet, recent research highlights the importance of skewness—the third statistical moment—as a driver of asset returns. Assets with lottery-like payoffs (high positive skewness) tend to be overpriced, while negatively skewed assets are often underpriced. A 66‑page study demonstrates that…
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Continue reading →: Breaking the Python Barrier: Building a Pure R-Native DeepAR Engine with LibTorchDeep learning for time series forecasting in R has historically faced a major architectural hurdle: Python overhead. Frameworks like modeltime.gluonts provide interface wrappers around AWS GluonTS, but they rely on a complex execution chain passing through reticulate, virtual environments, Python serialization, and MXNet/PyTorch backends. To overcome the performance bottlenecks and…
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Continue reading →: Analyzing Financial Trends: Kalman Filtering for Gold vs BitcoinIn their paper “A Synchronized Multi‑IMU Wearable System for Tracking of Joint‑Angles in Sports Motion Analysis” (arXiv:2607.26027v1), Samarasekera and colleagues set out to solve a very practical problem: how to reliably measure joint angles in dynamic sports movements using wearable IMUs. Their goal was to design a synchronized pipeline that…
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Continue reading →: Understanding Tail Analysis in Financial MarketsIn financial markets, distinguishing between information-driven movements and liquidity-driven shocks is critical. The reference study we based our work on highlights the importance of tail analysis: comparing Gaussian (thin-tailed) and Student‑t (fat-tailed) distributions to understand whether price changes are more likely to reflect genuine information or temporary liquidity imbalances. Financial…
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I’m Selcuk Disci
The DataGeeek focuses on machine learning, deep learning, and Generative AI in data science using financial data for educational and informational purposes.
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