Algorithmic trading is basically instructing a computer program what to do in certain situations. It has triggers and conditions and a constant data stream that feeds the algorithm with all the information needed in order to make decision sand execute trade orders.
Our trading procedure allows it to trade safely and return regular profit with minimal losses using market data which is then processed by our engines and executed onto the exchanges we trade in.
The algorithm is constantly evolving, being optimized every day to improve it and adapt it to ever-changing market conditions. An algorithm cannot be simply be allowed to run by itself because markets, parameters and circumstances change and not adapting to these can lead to a loss.
The advantage of a computerized execution engine is that depending on the particular strategy it can place orders and execute faster than a human can. Humans can average around 2.5hrs/day of focus, the rest of the day is creating and accomplishing other tasks and not being productive. Imagine a fund that trades only 2.5hrs/day /trader, you would need a lot of traders to handle the deployment of large capital strategies or to generate a healthy return. That was the case a long time ago when big hedge funds employed 300–500 traders to do just that.
Computer algorithms can review market conditions immediately after an execution and respond and adapt faster than a human can.However, there is no way to completely replace human intuition and certain abilities. For this reason, we always have traders and developers overseeing the performance and advancement of the strategies we deploy.
Another important aspect is that a computer program doesn’t have any feelings and it does not stress about a bad entry or a position going the wrong way, it just does what it has been programmed to do and does it consistently.
In theory the algorithm is programmed to place consistent and repetitive trades that will result in a positive daily return, however that is the theory only. The reality is that some days are zero percent days or loss days. There are mainly three factors that cause situations like this:
The first one is that we have positions opened from days before on one of our longer term algorithms and we can not state that we have achieved a certain profit until the positions are closed.
The second one is when either our traders or our algorithm decide that it is not safe to trade based on our strategies or market conditions. Hence, these are days that the algorithm doesn’t trade or only partially trades.
The third one is when an event happens in a particular market that makes it inefficient, imperfect, or not holding to normal market conditions. These are rare but include: extreme volatility, closure, acts of god, tampering, etc. Our strategies have a stop loss risk mitigation feature that identify such situations and immediately halts and exists trading thus minimizing any losses. The possibility still remains for a loss during a day with these rare circumstances.
While our main goal is to produce profit for our investors, risk management is even more important and we take it very seriously, that’s why we prefer to have days of no wins and no losses and where circumstances are not right to minimize loss or simply avoid loss.