How Algorithmic Trading Strategies Work
People use Options to mitigate their financial risks, when this is trades done algorithmic, it’s called algorithmic options trading. Algorithmic trading depends on a set of algorithms which help in deciding related to purchase/sale. The main feature of an Option contract is that when an investor decides to purchase an Option, the obligated seller pays a strike price to the buyer, at a certain time before the expiration of the Option. At the time of writing this article, the price of an Option is near to the historical average cost.
In addition to Option contracts, there are other types of Options such as naked Option, forward Contract, put option and futures options (for agricultural commodity and Forex Trading).
However, it has been found that in the case of pure algorithmic trading, it’s much easier to use backtesting to analyze trading data. Backtesting is an analytical technique that’s been proven to be very efficient in analyzing trading data, this in turn helps in identifying strengths and weaknesses in trading strategies. This is basically what’s called backtesting, hence the name.
In case of algorithmic options trading, the trader is looking for entry and exit points, this is very important when trading options. Backtest trading can be conducted using a simulated financial instrument, where the trader can execute the trade using hypothetical trading strategies. While trading using these strategies, the trader can make use of an indicator to indicate the potential support and resistance levels, along with other parameters. But the greatest advantage of backtesting is that you can get a hold of the actual market behavior, including reversals in price. One of the primary reasons why investors choose to carry out backtesting instead of manual trading strategies is because they don’t have to deal with the possible trading losses.
Basically, back testing is a technique where the investor makes use of historical data and applies it to the current time to come up with a profit target. When looking at the profit diagram, which is a graphical representation of the portfolio’s profit and loss, it is easy to see that algorithmically generated options trading will generate a higher profit than manual option trading strategies. The profit diagram is actually generated by an algorithm using past real-time market behavior and is hence considered to be an accurate depiction of the current trend of the underlying asset. But the truth is that the profit and loss graph will change depending upon the severity of market losses, which will reduce the profitability. Hence, the profitability of algorithmic options trading relies on the extent of loss over the course of time.
But even with the reduction in the profitability, the use of backtest trading strategies will still depend on the investor sticking to the rules of the strategy, and not to risk more than he can handle. Algorithmic Options trading strategies are usually sophisticated and are designed to deal with extreme scenarios. However, they are not foolproof, and investors should be prepared for drastic changes in the market by implementing a number of self-disciplined risk limits and rigid rules of the backtest trading strategies.
The most important factor about Algorithmic Options trading strategies is that they rely on the backtest results to predict the future direction of the underlying asset price, but they are unable to consider the recent past or recent trends. This can lead to the strategies’ inaccuracy in the sense that backtesting strategies’ predictions are influenced by the current trends and are therefore unreliable and may fail to provide a clear picture of the future direction of the prices of
the underlying securities. There are a few backtesting platforms which allow users to adjust the parameters of the backtesting algorithm. For example, Metatrader4 has several different parameter settings that allow the users to trade on a range of parameters, including maximum drawdown and expiration length.