How Does Backtesting Work in Algorithmic Trading?

224

Financial trading has become more sophisticated with the use of modern technology that helps execute trades effortlessly. Modern algorithmic trading software has taken stock trading to a different level. Today, most traders wouldn’t think of trading without backtesting.

What Is Backtesting?

Backtesting is a business procedure where you check historical market data to devise a new trading strategy. Backtesting is being used increasingly by stock traders to make sure they can curb their losses.

It is somewhat similar to buying a product only after reading several reviews and testimonials because that is when you'll know if it is worth buying.  However, there can always be exceptions, and one cannot take anything for granted in the stock market.

Automated and Manual Backtesting

Just as there is manual and algorithm-based automated trading, you have manual and automated backtesting to choose from. Manual backtesting is a laborious process where you need to manually study past charts and prevailing conditions by scanning several records before placing your current orders. However, with automated backtesting, you need to go by the code created by a tech team and can place orders automatically as the code takes care of the trading. The tech team needs to keep in mind the prevailing market conditions and create the code accordingly, to suit such requirements.

Crucial Points for an Effective Backtesting Trading Strategy:

Choosing the Ideal Market, including the Asset Segment

Stock trading depends on factors like the risk you are willing to take: The higher the risk, the more the profit. Short-term profit is always fraught with high risks, while a watch and wait strategy is safer though it takes time to complete a transaction.  Also, the risk varies according to the asset.

While trading in cryptocurrencies involves taking high risks, the returns match, often resulting in huge profits. Selecting the market and the asset makes a lot of difference, and the final decision is left to the investor, despite the use of sophisticated backtesting strategies.

Data Covering Various Market Conditions

Various factors in the market affect price movements. Stock markets are never static and tend to fluctuate depending on the current situation. Significant announcements on monetary policies make the markets swing in either direction. Similarly, the half-yearly and annual results of major companies also affect the stock price movement. Under such circumstances, a backtesting strategy based on the most advanced algorithmic trading software may not work as expected.

What are the Backtesting Parameters that Evaluate a System?

Total P & L

Having the total profit or loss figures will help you evaluate your trading strategy – whether it ended in a profit or a loss. Please note that the current profit or loss may not match the ones mined from historical data involving similar scenarios.

Average P & L

Average profit and loss indicate the amount realized as profit or suffered as a loss in a particular session or day or a specific period.

Different Types of Backtesters

When traders wish to automate their backtesting strategy using customized algorithmic trading software, it is up to the trader to decide whether the scrip’s future performance will depend on its past performance. This can be decided with the use of two forms of backtesting systems. One is the research-based backtester, and the other is an event-driven backtesting system.

Research-based Backtesters

These may not be the best tools for exactly replicating a past-case scenario for current conditions, though they can make an approximate evaluation. Despite this, these tools are used for backtesting and execution of transactions. These tools may not suit same-day trading (intraday), where the risks are much higher. They are more suitable for “testing the waters” before formulating a solid strategy involving a rigorous backtest in a real-time scenario.

Event-Based Backtesting

In this scenario, the algorithmic trading software-based automated trading strategy is linked to a live market feed. It gets market updates that will trigger a trading signal for a new potential position. Such systems consider historical data and brokerage replication, making the backtesting as good as live execution. The only problem traders may face maybe in the design, which is prone to bugs.

Common Errors

The standard error one can commit with backtesting is that as traders work with sample historical data continuously, the new strategy they formulate may fit the past data. The problem is that the current scenario need not end with a similar result, making the sample data quite useless for this particular scenario.

Summing it Up

Backtesting is certainly advantageous while using algorithmic trading software, as you can test your strategy before deploying it in a live market.  Any automated tool or software can be used by seasoned and experienced traders but may not be suitable for beginners who need to learn the ropes first.