The Week Ahead – Algorithmic and Quant Trading




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Last week was very busy with economic data including FOMC meeting, ECB meeting, and the usually powerful payrolls report from the US. The risk assets outperformed with Copper rising 3.9% and the NASDAQ 100 gaining 3.8%. Wheat and Corn gained while Soybeans dropped. In FX the risk currencies gained while the Japanese Yen dropped. In the week ahead the focus will be on Australia’s RBA and the Bank of England. While the RBA announces interest rates on Tuesday, take note that in the past month the Australian dollar has been the underperforming risk currency. In the equity markets the S&P 500 broke to a new all-time high following the stronger-than-expected US employment report. Looking ahead, I will be focusing on the correlation between the equity markets and risk assets including Crude Oil And Copper price action.



What is Algorithmic and  Quant Trading?

Algorithmic trading, also called Quant trading, is the use of algorithms to gather data in order to create computer driven models that analyze and execute preprogrammed trading instructions that may include timing, price, and risk. Quant trading has gained popularity in the financial markets, it now accounts for well over 50% of all trading. The advantage of using computers is the ability to run complex and multiple tasks in real time.

What Is The Strategy Logic Behind The Algorithms?

The basis of our strategies reflect the belief that price action is determined by the changing attitudes of market participants influenced by a variety of expectations including economic, political, and psychological outcomes. Our approach is based on the theory that price is a reflection of crowd behavior in action. It aims to forecast future price action on the assumption that crowd psychology moves between panic, fear and pessimism and at other times with confidence, excessive optimism, and greed.