Challenges individual traders face
Discretionary trading is demanding on time and focus with little room for diversification trading activities for reducing correlations and risks. No matter how good discretionary trader is, balancing portfolio for reducing risks and improving profits is the most important and at the same time, challenging thing.
Effective approach, how to diversify manual trading with minimal time effort and low correlations in performances, is automated or also algorithmic trading. This method may be hardly acceptable for some heavily manual traders. However as technology and automation in general is in the rise, automated trading is improving as well. In retail sector it is still mostly about “robots”, how many people call it. The idea that some algorithm can work on dozens of market instruments forever is wrong of course.
In the recent years, technology, computing power and data processing moved forward very much. The old way was to find logic in the market, test it and optimize. Everything manually. Between retail community, this is still the most used approach to algorithmic trading from developing to trading and evaluation. And at the same time, this is the reason why they mostly fail in algorithmic trading. Effective approach is in right development and evaluation process together with approaches to process big information blocks.
Algorithmic trading trends
New trends in algorithmic trading covers methods like machine learning which together with computing power can evaluate millions of trading concepts in short time. What developers did weeks to test one trading concept, now can be done with computing power within a few seconds. But algorithmic trading is not easy at all. It is still about objective advantage in the market which can be measured and evaluated.
The biggest challenge for developers is to find algorithms with predictive capabilities, not only with good historical results. Predictive capabilities don’t mean the ability to predict future forever as in “robots” idea. Due to market dynamic, individual algorithms in automated trading systems has limited effectiveness in time for which they can make a profit. Solving of this problem should be integrated in the whole process for long term success in algorithmic trading.
Solutions now available
It is not necessary to become trader using algorithms and developer at the same time. There are solutions how to implement algorithmic trading in trader’s portfolio without need of developing them. Where traders paid for market research, now they can pay for algorithmic solution to balance their portfolio.
Long term, achievable success is not in trading algorithms nor manual trading method. Long term success is in the right allocation and management of trader’s portfolio no matter on manual or algorithmic trading. Manual trading can fail as well as trading algorithms. The goal should be balance risks in portfolio with uncorrelated approaches and control of risks.
Director, Co-Founder of Algofxsolution.com
Algofxsolution offers free MetaTrader 4 Expert Advisor for closing open orders at a specified time. Visit this page to find out more.