Algorithmic trading is a newly developed form of Technical Analysis which utilizes computer programs. The investor inputs a set of parameters or orders (algorithms) for the computer to follow, in order to place an exchange. Once these parameters are met, the computer immediately carries out the exchange. This form of trading allows investors to generate a profit at a speed and efficiency impossible to normal people.
Now that we know what algorithmic trading is, lets look at some of its features and analyse why and how it may very well lead to the future of finance and investing as we know it :
Above we mentioned that the computer requires certain parameters or orders to be filled. These parameters include but aren’t limited to details such as the 50 day moving average, the 100 day moving average, the P/E ratio, the actual price of the share, the put/call option variety. For example, A company may set up an order to purchase a share if its above its 100 day moving average, achieving a P/E ratio of 100, reaching a stock price of 20$ etc. This incredible flexibility of instructions on the share allow the companies to handpick the perfect time, according to them, when they would like to purchase/ sell the share, all with the precision and timing of a computer, without even having to monitor the markets.
There aren’t severe technical requirements for algorithmic trading. A computer with network service and access to all the different types of markets is the primary hardware requirement for it. It’s the human touch which defines how successful the operation will be. Companies require individuals well versed in both computer programming and financial acumen in order to set up these codes, such individuals are known as Quants and are now finding a massive surge in their employability.
High frequency trading is one of the most common strategies being employed. It involves buying and selling a massive number of shares based on premade algorithms/ instructions. According to some estimates, 60-70% of US Stocks are traded in this manner
Back Testing involves the process of imputing the set orders and algorithms of the new strategy you are going to use and testing it on past data in order to measure its profitability. This process enables investors to gauge how successful their set of instructions may be and how they perform on a practical basis. However, the downside to back testing is that the more complex the set of instructions are, the more difficult it will be to program and check their influence on past data.
With the onset of Algorithmic trading, most large investment banks, hedge fund, and other major investing institutions are taking on this trade. In this day and age, it is can provide a very useful tool to investors savvy enough to pick it up.