Director with Barclays Capital
About Keyvan Azami
A longtime investment banking executive with nearly 15 years of experience in the field, Keyvan Azami currently serves as the director and global head of Rates eTrading Technology with Barclays Capital in New York City. In this capacity, he oversees the global development team and ensures the success of the firm’s Fixed Income Rates electronic and algorithmic trading platform. In addition to spearheading a key Swaps Electronic Trading program, Keyvan Azami implemented a number of sophisticated market tools for swaps and rate cash businesses.
Before assuming his current responsibilities, Keyvan Azami spent three years as the global head of Rates Trade Capture and OTC Clearing with Barclays Capital, where he designed a highly integrated front office platform for Emerging Markets and Fixed Income businesses. He also ensured connectivity with a number of Client Clearing platforms, equipped front office and risk managers with important optimization tools, and created a truly global development process.
Keyvan Azami holds a master of science in computer science from the University of London.
What is Algorithmic Trading?
Financial technologist Keyvan Azami commands more than 15 years of experience in the investment banking field. As the current director of the global technology team at Barclays Capital, Keyvan Azami oversees eTrading and algorithmic technology for the prominent Wall Street firm.
Algorithmic trading has revolutionized the way that we buy and sell stocks. In algorithmic trading, also known as algo-trading, computers follow a specific set of instructions to buy and sell stocks without human intervention. Algo-trading is advantageous for several reasons: computers can operate at a much higher speed than human traders, computers don't make decisions based on emotion, and, when programmed correctly, computers can consistently discern opportunities for profit in algo-trading.
Although algo-trading may be fast and convenient, it is important for algo-traders to thoroughly test their algorithms before implementing them. The usage of an incorrect algorithm could ultimately result in a trader losing money or making poor decisions in regard trades. However, once the algorithm has proven itself through testing, algo-traders can feel confident about moving forward with their stock trading activities.