Cryptocurrency Analysis and Forecasting

DOI: 10.1109/ASIANCON55314.2022.9909168

ABSTRACT: Cryptocurrencies are becoming a well-known and commonly acknowledged kind of substitute trade money. Most monetary businesses now include cryptocurrency. Accordingly, cryptocurrency is widely regarded as the most of prevalent and capable types of lucrative investments. However, because this financial sector is already known for its extreme volatility and quick price changes, over brief periods of time. For such constantly changing nature of trends and price, it has become a necessary part for traders and crypto enthusiast to get a detailed before investing. Also, the construction of a precise and dependable forecasting model is regarded vital for portfolio management and optimization. In this paper we propose a web system, which will help to understand cryptocurrency in a more statistical way. Proposed system focuses mainly on four coins : Bitcoin, Ethereum, Dogecoin and Shiba Inu performing analysis and forecasting on all the four coins. System will also do statistical between the coins. Analysis and comparison is carried out using and modules whereas LSTM and ARIMA are used for forecasting. Extensive was conducted using real-time and historical information, on four key cryptocurrencies, two of which had the greatest market capitalization, notably Bitcoin and Ethereum, while the other, Dogecoin and Shiba Inu, that had a significant growth in market capitalization over the previous year. In comparison to old fully-connected deep neural networks, the suggested model may employ mixed crypto data more proficiently, minimizing overfitting and computing costs.

– Proposed web system for cryptocurrency analysis and forecasting
– Use of LSTM and ARIMA for forecasting

– Proposed web system for cryptocurrency analysis and forecasting
– Use of LSTM and ARIMA for forecasting

– Proposed web system for cryptocurrency analysis and forecasting
– Use of LSTM and ARIMA for forecasting

– Extreme volatility and quick price changes in the cryptocurrency market.
– Overfitting and computing costs in fully-connected deep neural networks.

Methods used: – Extreme volatility and quick price changes in the cryptocurrency market.
– Overfitting and computing costs in fully-connected deep neural networks.

– Provides a web system for statistical analysis and forecasting of cryptocurrencies.
– Focuses on Bitcoin, Ethereum, Dogecoin, and Shiba Inu for analysis and comparison.

– Proposed web system for cryptocurrency analysis and forecasting
– Focus on Bitcoin, Ethereum, Dogecoin, and Shiba Inu

– Cryptocurrencies are widely used and considered lucrative investments.
– The paper proposes a web system for cryptocurrency analysis and forecasting.

– Cryptocurrencies are widely used and considered as lucrative investments.
– The paper proposes a web system for statistical analysis and forecasting of cryptocurrencies.

A web system, which will help to understand cryptocurrency in a more statistical way, focuses mainly on four coins : Bitcoin, Ethereum, Dogecoin and Shiba Inu performing analysis and forecasting on all the four coins.

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