Quantitative trading is a market strategy that heavily relies on statistical and mathematical models to identify and execute opportunities in the stock market. These models are driven by quantitative analysis, which gives the strategy its name- Quantitative Trading. In other terms, people also tend to refer to them as ‘quant trading’, or sometimes 'quant'. Quantitative Trading uses analysis based on research and measurement to convert complex patterns of trade into numerical values. This ignores qualitative analysis, which will evaluate the opportunities based on subjective factors like management expertise or brand strength. Quant trading demands a lot of computational power; traditionally, the usage is limited to large institutional investors and hedge funds. The past few years have seen the advent of new technology that has enabled increasing numbers of individual traders to get involved in quantitative trading. Working Model of Quantitative Trading? Quantitative tr
Since 2008, under the surveillance of trading bodies like SEBI, automated trading has been operational in India. Since then, the number of firms using algorithmic trading has been on the rise. In developed markets like the US, 70-80% of trading owes to algorithmic trading. This opens paths for a bright career in algorithmic trading in Asian countries where the market tends to be much more exciting as the concept is relatively new compared to developed markets. Here are some little-known facts about algorithmic trading : Prerequisites before you start algorithmic trading Various stock exchanges have different prerequisites before you can get an approval to start algorithmic trading. One can choose to be a trading member and directly trade through the exchange by fulfilling the stated criteria. The members of the exchange(s) apply for approval directly while the non-members apply through brokers. Anyone eyeing a change in algorithms must have the exchange’s approval before imple