From circulating ETF information to counterparties daily and providing them with execution throughout the day, to working on designing new efficient ways to best represent the team’s growth and trajectory for the upcoming years. In my role as an Institutional Trader, I get to explore many different sides of this multifaceted profession on a daily basis. From the entrepreneurial spirit where people feel supported to suggest and promote change, to the fast pace at which we implement innovative strategies.
#QUANT TRADING STRATEGIES FULL#
Since I joined Flow Traders full time, no two days are truly the same and it is a dynamic environment to be part of. To my surprise, I found these two characteristics to immediately be at the center of my role within even just the first week of my internship with Flow Traders in the summer of 2021.
When looking for my first job after University, I looked to fulfill two main requirements, firstly an ever-changing role where no two days are the same and secondly a closeness to the financial markets. Next to trading on-exchange, our Institutional Traders trade off-exchange with institutional investors all over Europe, APAC and the Americas, providing competitive quotes upon request for several asset classes.
Our Analysts monitor global news, prepare for major market events and continuously inform and advise our Traders based on macro, micro and fundamental considerations. Quantitative Researchers are responsible for generating and back testing new trading ideas, with generation of alpha and automated strategies as ultimate output goals. Our Traders manage and optimize our daily positions, formulate innovative trading strategies and build trading tools. The team trades a wide range of financial products, including ETPs, Fixed Income, FX and Digital Assets. Trading is for brilliant minds, independent thinkers, energetic doers, and outstanding talent. They are extremely driven and determined to be the best. Human discretion such as macro view on the future market trend is considered to still play an important role for quantitative trading to be successful in the long-run.Our Traders, Quants and Analysts work in a fast-paced, highly intensive environment, where each day brings complex challenges. Some strategies recorded higher performances than the benchmark in the back-tests, however it is still a problem how we can distinguish these winner strategies beforehand from the losers at the beginning of our investment horizon. Then I attempt to articulate and decompose the source for successes of some strategies in the back-tests into several factors such as trend patterns or relationships between market information variables in intuitive way. The strategies utilize the historical data of the stock index itself, trading volume movement, risk-free rate movement and implied volatility movement in order to generate buy or sell trading signals. by executing back-tests assuming that the S&P 500 stock index is a risky asset to trade.
In this research, I introduce several quantitative trading strategies and investigate their performances empirically i.e. They try to find some patters or trends from the historical data and use them to beat the market benchmark. They challenge the Efficient Market Hypothesis by trying to forecast future price movements of risky assets from the historical market information in algorithmic ways or in statistical ways. Along with the increasing computing power, growing availability of various data streams, introduction of the electronic exchanges, decreasing trading costs and heating-up competition in financial investment industry, quantitative trading strategies or quantitative trading rules have been evolving rapidly in a few decades.
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