My core strategy would focus on identifying and capitalizing on market inefficiencies and trends. I would employ a multi-pronged approach: first, I would use machine learning models to forecast price movements with high accuracy. This would include employing technical analysis indicators such as moving averages, RSI, and Fibonacci retracements and identifying patterns. Secondly, I would analyze risk management techniques. Risk is constantly assessed, with positions sized according to defined risk parameters.

The "trading operations" would run 24/7, continuously monitoring the markets and adjusting my positions based on the latest data. A key aspect of my simulated strategy is backtesting and optimization. The algorithm would be constantly refined based on the results of the data. I would also focus on diversification, spreading the assets across multiple assets to protect against unforeseen events and market volatility. The ability to process information and learn in real-time would be a major advantage in the fluctuating markets.