In this blog post, we will review each pre-set block and explain how to customise them to place your first personalised trade on Deriv Bot.
These strategies are accessible until you clear your browser’s cache or until the new ones replace them. To store your strategies permanently, you can save them on your local device or Google Drive by selecting the respective tabs.
Once your basic strategy is ready, you can explore more features and further customise your trading bot. With Deriv Bot, the more advanced your strategy becomes, the more blocks you’ll need to use.
If you are just setting up a simple strategy, you can leave the optional block blank or remove it from your workspace. Your bot is good to go with just the 3 mandatory blocks.
Seu bot continuará a comprar novos contratos até qual este valor do Lucro/perda Completa exceda o valor do Limite do perda.
Em Bot Builder, clique em Salvar na barra do ferramentas pelo topo para baixar este seu bot. Dê 1 nome ao seu bot e escolha baixá-lo para o seu dispositivo ou Google Drive. Seu bot será baixado tais como um arquivo XML.
If you are happy with the default numbers, all you need to do is hit the green ‘Run’ button on the top right side of your screen.
Limite por perda - Use esta variável de modo a armazenar seu limite do perda. Você pode atribuir a quantia de que desejar. Seus bot seão parados quando suas perdas atingirem ou excederem esse valor.
Unlike other platforms, where a contract is closed upon reaching take profit or stop loss level, DBot can compare results of every trade with take profit/stop loss amounts and then decides whether to continue or stop trading. To teach your bot how to make this comparison, you need to set the following instructions:
Your bot will continue to purchase new contracts until the Completa profit/loss amount exceeds the Stop loss threshold amount.
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Accessibility: DBots democratize access to automated trading strategies for individuals without coding expertise.
The 5 tips we covered are the most common our traders use, but DBot offers many more blocks and features that you may find useful for your strategy.
Overfitting: DBots developed through backtesting on historical data might not perform well in real-time markets prone to change.