4 posts tagged with "swing-trading"

While our initial LLM-based market analysis approach has faced criticism, there may be hidden value in this ambitious experiment. From developing cutting-edge prompting techniques to potentially exploiting the predictable behavior of algorithmic traders, this deep dive explores two compelling perspectives on how we could pivot our research to create genuine competitive advantages. Whether you're interested in advancing the field of LLM applications or discovering novel trading strategies, these insights could reshape how you think about the intersection of artificial intelligence and financial markets.

Our ambitious experiment using LLMs for market analysis has revealed some uncomfortable truths. While we've made fascinating discoveries about the capabilities of language models, our current approach may be fundamentally flawed. In this deep-dive critique, I'll explain why we need to radically rethink how we leverage AI in trading - and propose an alternative direction that could actually give us a genuine edge in the market.

Looking to enhance your market analysis without the complexity of LoRA fine-tuning? This deep dive reveals four powerful techniques to supercharge DeepSeek-R1's technical analysis capabilities using just prompt engineering and Ollama's built-in features. Whether you're a quant developer seeking better market insights or an ML engineer optimizing model performance, these battle-tested approaches will help you achieve professional-grade analysis without the computational overhead of custom training.

Swing trading is the art of capturing significant price moves over days to weeks. Unlike scalping or day trading, which rely on rapid entries and exits, swing traders aim to profit from broader market movements, capitalizing on momentum, trends, and key price levels.

Why Swing Trading?​

✅ Less screen time than day trading ✅ High reward-to-risk potential ✅ Works well with technical analysis ✅ Avoids the noise of lower timeframes