Investing while utilizing an automated system involves employing an advanced software system to carry out pre-established procedures for initiating and terminating deals.

In this approach, you, as an ambitious trader investing smart money, should integrate meticulous technical and fundamental analysis with establishing opening order information, trailing stops, and assured checkpoints for your holdings.

You’ll be able to execute numerous transactions quickly with the help of automated trading, which also has the advantage of removing thoughts and feelings from your trading selections. This is because the criteria you select already include all the necessary guidelines.

Certain algorithms also enable you to monitor trends and make trades based on your pre-planned tactics. You need to first select a system and establish the specifics of your investment strategy.

Your own algorithm employs the policies and guidelines you develop based on your market knowledge to execute deals in your favor. The timeliness of the deal, the value at which a transaction ought to be initiated and sealed, and the volume of trading is typically the deciding considerations.

A defined algorithmic and automated trading method continuously tracks price movements on the capital markets, and if certain criteria are satisfied, transactions are carried out instantly. The goal is to conduct transactions more quickly and effectively while reaping the benefits of particular, technical economic trends.

How can you automate your trading processes: A 6-step guide

It’s advantageous to change your plan into a simple rule-based approach or to a thoroughly investigated and tried statistical analysis – which can likely be far more reliable, productive, and profitable. Automation will be really useful here.

Therefore, the topic of this essay will be to address one key question — what’re the best strategies to automate your trading approach? How and where to start? The numerous phases, or perhaps we should term it an implementation funnel — for automating your enterprise's algorithmic trading techniques are listed below.

1.    Start with a strategy

As you might think, there’re numerous advantages to creating something specifically for your requirements. Tailor and tune it to your exact specifications, and you can choose its constraints and be fully conscious of its possibilities.

Clearly, this necessitates some understanding and comprehension of what could be programmed. However, at this point, working with a programmer is a possibility. Your creativity and concepts will create the framework and help in designing a roadmap for the development company to adhere to.

First up, think of devising a thorough trading plan. It serves as your primary starting point since it enables you to outline your investment objectives and the ways your platform can assist you in achieving them. At this point, think about the audiences you want to target, your operating hours, the ratio of risks to rewards, and your chosen approach.

Create your framework after this. In this step, focus on the intricacies and decide how your objectives will be met, including how the platform will discover investment options and what to do when it does.

Selecting tools for risk management  also forms a part of the planning phase. This is crucial for reducing the threats you may encounter while using tools like basic, secured, as well as trailing stops. Another choice is to select a cap, which, when it’s activated, will either be at a value you have set or at a lower price.

2.    Obtain information through careful research

For back-testing your strategic plan, validating it, and putting it into practice in actual markets, you'll require to access market statistics. You need to obtain historical data through exchanges, data suppliers, or financial websites that provide access to past market intelligence.

You should also obtain real-time financial numbers from your brokers for nothing or maybe for a little fee. Further, you need to collect the information from the exchanges or suppliers if, for whatever reason, you would prefer to not obtain it from a brokerage firm.

Leading financial institutions spend a significant amount of money in creating their own algorithms, largely due to the capabilities required. The excellent thing is that many of these techniques, particularly those developed in coding languages, have become open-source.

It’s due to the rise of machine learning and data science, making them widely available to small and medium-sized investors. You must employ these research resources to generate thoughts that are of an academic caliber.

Note: Backtesting is among the most effective automated trading tools for investors. Why?

It’s a technique for analyzing an investing strategy's performance under previous economic conditions. It enables you to imagine what it might have been like to travel through time and put that concept into practice.

This is a crucial point – the implicit premise of backtesting is that the future will mirror the past. However, the linkages between assets and economic factors change with time, so simply because something has transpired in the past does not guarantee that it’ll happen again.

However, that doesn’t imply that backtesting is useless. It’s frequently used by professionals. 50% of analysts used backtesting over the course of the previous 12 months, according to a CFA Institute survey.

Why? Because backtesting makes data, accuracy, and knowledge available that would not otherwise be possible. And you might be able to get a little advantage if you’re really adept at digesting that data.

3.    Construct an automated trading algorithm

Coding knowledge is useful in this case. If your strategy is fairly simple, you’ll be able to utilize a variety of tools, which will enable you to develop your plan – within the given sophistication restrictions, sans coding.

You ought to be capable of programming, or you may pay somebody who can. Your brokerage vendor or a third-party software provider may provide you with the algorithmic trading software system on which you'll be developing such investment strategies.

Knowing how well your transactions have performed in the previous years is essential. Utilizing past statistical information as well as other benchmark datasets as needed by the methodology, algorithmic analysts devote the majority of their efforts to learning about and backtesting the trading techniques.

4.    Strategize about entering your target markets

This has to do with connecting to exchanges. For trading, you would be required to contact the exchange via a broker if you don't have your individual subscription. After validating your details, several brokers offer APIs (application programming interfaces) in Python or other coding languages for connecting with them.

With the help of APIs, you can write your algorithms from scratch. Utilizing industry-leading IG (interactive graphics) technology, transactions are processed to guarantee the finest performance. Examine previous and real-time valuations, analyze trading data and stocks and bonds, keep watchlists, and much more.

Through their particular APIs, you could obtain real-time hard numbers from brokers, exchanges, or suppliers. However, one must look out for any potential lag brought on by network congestion.

It might make logical sense to place your servers within the same location as your counterparties if you aren't in co-location.

5.    Test and improve

This stage is to evaluate your plan using actual market facts in practice accounts. For the forward testing phase, the majority of automated trading systems include a simulation model.

This is equivalent to using real-time market data when conducting paper trades. You can conclude your strategy with optimal settings if you're content with your investing plan's execution.

Your program will create technical indicators according to the market statistics. An algorithmic trading system's order manager interprets such trend lines, and matching buying and selling requests are then put on the exchanges.

It's crucial to perform state management on all active orders, which involves looking for any existing unfulfilled orders and removing them if required before issuing a fresh one. Additionally, before being submitted to the exchanges, each and every one of your transactions must pass the required risk assessments.

6.    Obtain the required legal authorizations

Before using automation, there’re a number of regulations that must be observed by each exchange, operator, and geographic area. With regard to automated trading, several exchanges have established clear guidelines.

Whenever you computerize your methods using any software, if you're investing through brokers, you must speak with them and obtain the necessary approvals.

Reviewing the effectiveness of your investment strategy and trading platform after going live is crucial.

Do the strategy's actual market results reflect the findings of the associated backtests?

Are you receiving your purchases filled for the intended prices?

Has the architecture of the market changed, and if so, should your approach or methodology start changing?

Your tactics must be modified in response to shifts in the market and thus should keep developing in order to become effective.

Continually improvise on your automated trading strategies for maximum and long-term results

People frequently assume that automated trading is a sort of set-it-and-forget-it technique, but this is rarely the case. These methods explain how to automate your trading techniques and execute trading algorithms.

Your business performance is closely correlated with the amount of work you put in. While automated trading won't bring in cash on its own, it might aid you in the quest for it by taking a systematic and effective approach.

Author bio

Atreyee Chowdhury is a freelance content writer with more than 10+ years of professional experience. She is passionate about helping SMBs and enterprises achieve their content marketing goals with her carefully crafted and compelling content. She loves to read, travel, and experiment with different cuisines in her free time. You can follow her on LinkedIn.