But advancement in technology, especially in cloud computing resources, has opened the doors for average retail traders to also try their hands in this space. As mentioned earlier, quantitative trading has always been more common with financial institutions because of the computational power it demands. The trade ideas can then be executed manually or automatically in the market. A quant trader will research, and analyse historical data, and then proceed to apply advanced mathematical and statistical models to pick out trading opportunities in the market. The idea of quantitative trading is to generate solid trade ideas purely by using mathematical models. If it is established that this pattern happens over 90% of the time, then the quantitative trading model developed will predict that the pattern will be repeated 90% of the time in the future. A quant would then develop a program to analyse this pattern over the entire history of the stock. An example of a quantitative model would be analysing the bullish pressure experienced on the McDonald’s Stock (MCD) on the NYSE during lunch hours. Nonetheless, in recent days it is increasingly being utilised by retail investors too. This is why quantitative trading has, for a long time, been a preserve of top financial institutions and high-net-worth individuals. It requires a lot of computational power to extensively research and it makes conclusive hypotheses out of numerous numerical data sets. Quantitative trading is largely data-driven and uses purely statistical and mathematical models to establish the probability of certain outcomes. Granted, the results may not be accurate all the time, but the success rate is usually more than respectable, and any predictions will be based on both a huge historical and present database. Trading has always been likened to forecasting the weather, and if that is the case, quantitative traders are the equivalent of modern-day real-time meteorologists using the latest state-of-the-art equipment to determine the weather of any particular place at any given time. For quantitative traders, price and volume are the most important variables, and the bigger the dataset, the better.
Quantitative trading is known to implement advanced modern technologies on huge databases so as to provide comprehensive analyses of the opportunities present in the market. Quantitative trading is the use of sophisticated mathematical and statistical models and computation to identify profitable opportunities in the financial markets.
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