| DigHiSci | https://newdigitals.org/ |
| AI | Artificial Intelligence |
| ML | Machine learning |
| Python | MLaaS AIOps use cases |
#python #machinelearning #technology #finance #riskmanagement #stockmarket
#volatility #investing #algorithmictrading
👉 Hybrid Machine Learning for Market Regime Detection Part 1: SPY, IWM, HYG, LQD & Volatility (VIX) 📈 🤖
Integrating data wrangling, unsupervised/supervised learning, and interpretability into a unified market regime detection framework in Python
#python #technology #finance
#riskmanagement #investing
#automation #optimization #statistics #algorithmictrading
👉 Azapy: A Feature-Rich Python Toolkit for Multi-Risk Portfolio Optimization & Flexible Asset Management 🤖 📈 🐍
Explore 10 Risk Measures × 6 Strategies = 60 Ways to Optimize Your Regime-Robust Portfolios in Pythonic Asset Management 💰
#python #machinelearning #ai
#technology #programming
#automation
#algorithmictrading #investing
#riskmanagement #profit
The Unexpected Profitability of Adaptive Local Linear Regression in Short-Term Trend-Following Strategies of Growth Stocks
Bias-Free Expanding-Window Linear Regression: Backtesting and Out-of-Sample (OOS) Palantir (PLTR) Risk-Adjusted Returns
#exploremore 📈
If you don’t have a Medium membership, you can check it out for free right here: 👇
https://medium.com/@alexzap922/the-unexpected-profitability-of-adaptive-local-linear-regression-in-short-term-trend-following-8f5643b3df96?sk=819d5176d1b06c00ce9e48704667a9be
#python #programming #technology #automation #stock #palantir #backtesting #risk #volatility #machinelearning #ai
#datascience
A Polynomial Regression–Based Trend-Following Strategy vs Market: Backtesting and Out-of-Sample Results
💰 📈 🧠 🤖 🐍
Discovering Profitable Algorithmic Trading Strategies in Python with Polynomial Regression — A PLTR Use Case
#exploremore 👇
https://medium.com/@alexzap922/a-polynomial-regression-based-trend-following-strategy-vs-market-backtesting-and-out-of-sample-e5720c052ee9?sk=9520ef5ad9cde1e1c520cc47ce9765e5
#python #algorithm #investing
#growth #palantir #backtesting
#technology #optimization #noise #filtering #risk
#volatility #ROI
Evaluating a Laplace Trend Strength Strategy Using Backtesting and Out-of-Sample Tests: Evidence from PLTR 🧠 💰
Noise-Resilient Algorithmic Trading Using a Laplace Trend Filter in Python (with Tested Codes)
#exploremore 👇 📈
#python #datascience #technology #analytics #data #online #webscraping #legal #ethics #AI #automation #bot #google #API #profit #risk
Ethical Web Scraping with Python: Doing It Right with Dollar Value in Mind 📈 📝 🧠 💰
Discover the great commercial potential of ethical web scraping and see how it translates into real revenue, all while keeping legal and ethical considerations in mind
#python #data #financial #technology #datascience
#stockmarket #investing
#risk #volatility #fractal #statistics
📈 Using Causal 1D Mellin Transform for Market Regime Detection and Scale-Invariant Volatility Analysis in Python
Handling Multiplicative Noise in Financial Time Series: 5-Year PLTR Daily Returns 🧠
#python #programming
#science #datascience
#stock #AI #tech #technology
#review #investing #finance
Taking Stock of the Tech-Centered Market in 2025 & Outlook for 2026
Python-Led & Third-Party FinTech Macro-to-Micro SWOT Analysis of the Growing Tech Segment Share Across 11 GICs: A Holistic View
#python #programming #technology #investing #automation #AI #stockmarket
👉 Beginner-Friendly Python-Based SMA Backtesting & Parameter Tuning for Long-Term Investing in Palantir Technologies Inc. (NASDAQ: PLTR) 📈
Simple Data-Driven Technical Analysis of Palantir (PLTR) for Growth-Focused, AI-Centered Investing 🧠
#python #algorithm #stock #palantir #signal #market
#datascience #socialmedia
#investing #risk #tech
#volatility #technology #machinelearning
Market Noise Detection & Elimination using Volatility-Adaptive EMAs & Causal Laplace Filters
PLTR Use-Case Study: Enhancing Exponential Moving Averages (EMAs) with Volatility-Based Tuning and Causal Laplace Filters, Backtested Without Lookahead Bias
