Tayloe Draughon

Tayloe Draughon

Senior Product Manager at CloudQuant
Message Message me Posts: 33 Comments: 22
Bio eTrading product manager, technology & FINTECH innovator Career History Currently: Senior Product Manager, CloudQuant Formerly: Independent Consultant. Neurensic: MD Product Design. Societe Generale: Director Global eSolutions Products & Strategy. Newedge: Head of E-Solutions Client Services & Product Management



The Market Data Fire Swamp

26 Oct 2018

Market Data in the trading industry reminds me of the Fire Swamp in the movie “The Princess Bride” (1987). Do you remember the Fire Swamp? It was characterized by three primary dangers - The Creatures of Unusual Size, The Lightning Sand, and the Fire Spurts. The SEC is currently facing off with the industry over market data. My experience going thr...

Fintech innovation and startups

Getting Started in Algorithmic Trading Includes Overcoming Common Problems

29 May 2018

Many people have attempted to become the next great trader. They try assets like cryptocurrencies, or futures, or options and soon find out that it isn’t as easy as they originally thought. They run into many of the same problems. Problem: Not enough cash. I recently lost some personal cash on short-term volatility. I knew it was a gamble. I should...


Algo Trading and Ethics

29 Nov 2017

Algorithmic Trading and Ethics Alessio Farhadi posted “A.I. Trading - A Question of Ethics” on LinkedIn. His main point is that machine learning and algos do not have ethics. His thoughts may be overly influenced by the referenced Flash Boys book that painted the trading industry with a somewhat cynical brush. Just as AI technology has enabled g...

Fintech innovation and startups

Social Sentiment in Trading Algorithms

21 Jun 2017

Bloomberg recently wrote that “It’s no secret that hedge fund managers are always looking for new sources of data that will help them in their never-ending quest to beat the market.” (1) This has been increasing interesting to me. I have found that the incorporation of social sentiment data is definitely improving the quality of algorithms as shown...

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