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Keys to a good trading strategy

In “Building an Algorithmic Trading Strategy” by Tad Slaff the key components of creating an algorithmic trading strategy are concisely highlighted and discussed. The points he highlights (Idea, Test,Trade with a pertinent aside to risk management) are all key components of any (manually or algorithmically implemented) trading strategy or investment strategy.

Real-time news analysis with market news insights can greatly increase the actionable set of data that becomes a part of your trading concept. Whether you are a fundamental or technical trader or investor incorporating quantified market news sentiment data can aid in generating an edge in any trading strategy. Testing your trading strategy will be the same whether you are manually or algorithmically implementing the strategy in the markets. The trading phase of the strategy is another phase that can be enhanced with the integration of trading signals derived from market news analysis – helping to better identify entry/exit points or confirm your existing trading signals. Lastly, the risk management component of any good trading strategy algorithmic or manual is crucial. The risk management component of the trading strategy helps protect capital and maximize trading profits. Many risk management systems rely on monitoring changes in the trade as well as underlying fundamental data about the stock, option, currency(FX). A natural extension to monitoring changes in the trade and underlying data is to know and monitor changes in the sentiment data contained within market news. Adding this news analytics data will enrich the entire risk management process and improve the ability to protect capital while also maximizing profits.

There are many similarities to creating a good trading strategy whether it is implemented algorithmically or manually in the markets. They both require timely and impactful data for all phases of the strategy. And they can all benefit from the inclusion of relevant new data sources. Quantified news data can greatly strengthen and inform your decision making from trade idea and trade implementation as well as risk management for both algorithmic trading strategies as well as manually implemented trading strategies.