Building Automated Trading Strategies October 2018 | Page 49

CHAPTER-8: CONCLUSIONS
These are some general conclusions regarding automated trading:
➢ Automated trading is a sophisticated branch of systematic trading. All
automated trading systems are systematic but NOT all systematic
systems are automated systems
➢ When we refer to an automated trading strategy, we refer to the way
that trading orders are executed. An automated trading strategy must
be able to execute trades without human intervention by also placing
limit orders (a take-profit and a stop-loss)
➢ Nowadays, due to the technological advancement of the financial
industry, any retail trader can afford the cost of buying or creating an
automated trading strategy
➢ The great advantage of automated trading is that it is able to exclude
human psychology out of the trading game. Furthermore, an
automated trading system never gets tired. Using a VPS hosting
service you can turn-off your PC and continue trading 24hours per day
➢ Automated trading requires a good (but not very expensive)
combination of computer software and hardware
➢ Retail traders mainly use strategies running on platforms such as
MetaTrader-4 and MetaTrader-5. On the other hand, institutional
traders use data-driven modelling techniques or trading systems based
on granular data, often referred to as Big Data
➢ There are two key approaches for building automated-trading
strategies: Model-based and Data-driven approaches
➢ An algorithmic trading strategy incorporates two basic components:
the forecasting and the trading modules
➢ Machine learning refers to the process of using statistical tools and
techniques in order to offer computer systems the ability to ‘Learn’
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