Cryptocurrency Trading BoT Using Python

DOI: 10.22214/ijraset.2023.52125

ABSTRACT: Abstract: Our daily life has been merged online and they become more flexible and more effective. A huge growth in number of online users has activated virtual word and created a new business phenomenon which is cryptocurrency to facilitate the financial activities such as buying, selling and . Cryptocurrency represent valuable and intangible objects which are used electronically in different applications and networks such as online social networks, online social games, virtual worlds and peer to peer networks. The use of virtual currency has become widespread in many different systems in recent years. At present, trading is done by human which is a hectic work. The first disadvantage is that we analyze the chosen cryptocurrency will rise or fall in value and or sell as per our strategies which is not accurate and efficient always, the second one is that we need to keep a watch every second to cope with loss, which is not possible for a human. We can use a that can trade by itself to maximize the profit. The bot function by taking the relative strength index (RSI) of the coin and calculates the selling price and buying price for the existing price. This can help the user to gain profit and be relaxed in the fluctuation period of the coin. These help capitalize on market opportunities and cut down time spent on monitoring.

– The paper proposes a trading bot coded in Python that uses the relative strength index (RSI) to determine when to buy and sell cryptocurrencies.
– The bot is trained using a random forest regression model and historical data.

– The paper proposes a trading bot coded in Python that uses the relative strength index (RSI) to determine when to buy and sell cryptocurrencies.
– The bot is trained using a random forest regression model and historical data.

– The paper proposes a trading bot coded in Python that uses the relative strength index (RSI) to determine when to buy and sell cryptocurrencies.
– The bot is trained using a random forest regression model and historical data.

Methods used:

– The paper proposes a trading bot coded in Python that uses the relative strength index (RSI) to automate cryptocurrency trading.
– The bot helps maximize profit and reduce the time spent on monitoring market opportunities.

– Digital behavior metrics have a significant effect on cryptocurrency trade websites' traffic.
– Organic traffic increases with higher bounce rate and unique visitors.

– The paper proposes a Python trading bot for cryptocurrency trading.
– The bot uses the relative strength index (RSI) to determine buying and selling prices.

– The paper aims to build an efficient cryptocurrency trading bot.
– The bot uses the Relative Strength Index (RSI) to make trading decisions.

In this paper , the authors proposed a bot that can trade by itself to maximize the profit of the user in order to relax the user during the fluctuation period of the coin, which can help the user to gain profit and be relaxed in the fluctuating period of coin.

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