Market conditions can be volatile and affect the price level, the number of transactions, and the execution of orders. The same strategy can show different results on rising or falling markets, and this should be taken into account in the process of AI Trading Bot Development.
The developers of the trading bots should make tests under various market conditions, including sharp price changes, small volumes of trading, or wide spread between the buying and selling prices. Rules regarding the place where to place an order, the size of the position, and the risk allowed should also be established.
Testing can be done based on historical data, but it cannot predict the future results. Tests based on the recent data and analysis of the real trades can help discover the weak points of the strategy and the moment when its modification is necessary.
Upon comparing an AI Trading Bot with other AI Crypto Trading approaches, it is important for companies to look at how each system interprets market data and adheres to trading policies Since various Crypto Trading Bots use different strategies it is important to evaluate the systems individually.
In what should the developer concentrate in the light of changing market environment for modifying trading policy, in checking the validity of market data, or in minimizing risks? It all depends on the type of assets traded and the approach adopted.
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