Digging deeper into the data means you are increasingly dependent on data quality and accuracy. Tick data is usually derived from many sources. There are 13 major exchanges in the U.S. alone and 20 across Europe and Asia. Asia’s markets are characterized by unique technologies, cost structures, regulations and cultures. The disparity across markets is a natural barrier to algorithmic trading and can create challenges for efficient trading. The determinants of price discovery, volume and trading patterns define the structure unique to each market, asset class and geography influenced by participants and current regulation.
To conquer this disparity across markets, data has to be analyzed and scrubbed clean. Crossing borders also means global symbologies, which requires symbol maps and currency conversions. For risk management, data quality goes one step further for accuracy – statistically scrubbing algorithms. Once data is scrubbed, traders must then analyze the data for trading opportunities, which are often fleeting.
Market inefficiencies, the life blood of alpha generating strategies, are manifested by many things, including but not limited to human behavior, geo-political events and complex market structure. Quants must apply an empirically-tested and rules-based approach to exploit these inefficiencies if they hope to outsmart the competition. Nonetheless, trade models have a short shelf life and shifting market conditions can stress model performance. This creates a side effect of increasing demands for comprehensive historical data over extended time periods.
Historical analysis of high quality and comprehensive data can lead to the recognition of similar market conditions in the past, which can shed light on their consequences. Back-testing your models against past market conditions enables you to fine-tune algorithms, manage inherent risk and reveal alpha.
This new normal that we live in today is defined by diminishing volumes, wild rallies and uncertain regulatory policy. But it does not signal an end to profitability and the discovery of alpha hidden within the depths of our markets – on the contrary, when equipped with data and the tools to tame it, this is where the quest to tap profitability and alpha begins.