I am a professional trader who trades on a discretionary basis but supported by quantitative research and models that support my decisions. The asset classes I trade are equities, crude oil and natural gas. I use various instruments to get exposure to my views: stocks, options

, futures, options on futures. While I take price bets on the above asset classes, I also trade volatility and can go both long or short volatility through implied/realized volatility spreads. I have a team that supports me in mechanical aspects of trading while I focus on

hypothesis making that quantitative researchers in team help develop or refute based on my guidance albeit in a collegial team oriented environment. The process of quantitative research starts from our own observations about the market or an insight from an academic paper or

ideas from our competitors, brokers and other industry participants. If we don't have a viable economic explanation for the phenomenon we stop right here. In all our reasearch we look for why some market participants will pay us for a particular trade. Thus market structure

and associated economic incentives of various players are very important. Our models for pricing given a priori information of various factors into the pricing models are indeed very sophisticated. You will hear us talk about 4 factor options pricing models with stochastic

volatility with jumps in price and volatility but our tools and models that predict risk factor evolution itself are simple and even crude at times. Here market knowledge, flow and economic environment come into play. We like to place a large number of bets seeking

seeking diversification through bets on uncorrelated assets and position sizing. In certain industry such as crypto we have long term bets that are based on strength of underlying technology, markets/needs served and competitive dynamics. In such cases, microeconomics analysis

and application of porter's forces framework is a key. We have a bias towards trading as opposed to doing research ad nauseam due to the fact the markets are far too complex to be captured by quantitative models and best way to learn is to start dabbling hands on for a new

strategy. We have found with discipline and portfolio optimization one can beat index performance many times over. Also nimbleness allows returns far above the benchmark buy and hold.