A Deep Learning Approach to Predict the Fall [of Price] of Cryptocurrency Long Before its Actual Fall (2411.13615v3)

Abstract: In modern times, the cryptocurrency market is one of the world's most rapidly rising financial markets. The cryptocurrency market is regarded to be more volatile and illiquid than traditional markets such as equities, foreign exchange, and commodities. The risk of this market creates an uncertain condition among the investors. The purpose of this research is to predict the magnitude of the risk factor of the cryptocurrency market. Risk factor is also called volatility. Our approach will assist people who invest in the cryptocurrency market by overcoming the problems and difficulties they experience. Our approach starts with calculating the risk factor of the cryptocurrency market from the existing parameters. In twenty elements of the cryptocurrency market, the risk factor has been predicted using different machine learning algorithms such as CNN, LSTM, BiLSTM, and GRU. All of the models have been applied to the calculated risk factor parameter. A new model has been developed to predict better than the existing models. Our proposed model gives the highest RMSE value of 1.3229 and the lowest RMSE value of 0.0089. Following our model, it will be easier for investors to trade in complicated and challenging financial assets like bitcoin, Ethereum, dogecoin, etc. Where the other existing models, the highest RMSE was 14.5092, and the lower was 0.02769. So, the proposed model performs much better than models with proper generalization. Using our approach, it will be easier for investors to trade in complicated and challenging financial assets like Bitcoin, Ethereum, and Dogecoin.

• Cryptocurrency typology is a classification system that organizes different digital currencies based on their unique characteristics, technologies, and market roles.
• Different typologies highlight categories like foundational currencies (Bitcoin, Ethereum), innovation platforms (Cardano, Cosmos), stablecoins (Tether), and niche assets (Meme coins).
• Understanding cryptocurrency typology helps researchers and practitioners analyze the diverse, dynamic environment and challenges related to scalability, regulation, and market behavior.

Analysis of Cryptocurrency Typology

The document serves as a canvas containing typological representations of various cryptocurrencies. These categories have been organized succinctly, and each is distinguished by its unique characteristics within the cryptocurrency ecosystem. This visual representation contributes to a clearer understanding of the diversity and distinct functionalities among different cryptocurrencies. The arrays of cryptocurrencies are cataloged with visual media and utilize technical typography to indicate separate segments.

The palmary typologies illustrated include:

1. Binance Smart Chain and Bitcoin: The presentation emphasizes these cryptocurrencies as staples in the ecosystem, highlighting their robust infrastructure and decentralized nature. Their overarching influence in market capitalization and adoption rate is significant. Bitcoin especially is pioneering in mainstream financial adoption, providing a decentralized alternative to fiat currency. Binance Smart Chain is noted for its Ethereum-like smart contract functionality but with enhanced efficiency.
2. Cardano, Chainnlink, Cosmos, and Cryptocom: These entities are positioned within the innovation forefront of blockchain technology. Cardano's focus on sustainability and scalability through its Proof-of-Stake consensus model offers a distinctive advantage in energy consumption compared to Proof-of-Work models. Cosmos and Cryptocom expand on interoperability, enabling a more unified blockchain ecosystem through protocols that facilitate information exchange between separate blockchains.
3. Dogecoin, and other so-called "Meme" or community-driven cryptocurrencies: Such currencies highlight the influence of social dynamics and pop culture on cryptocurrency valuation and adoption. Dogecoin’s increased attention serves as a case paper of how community endorsement can propel a currency's value despite lacking substantial technological backing.
4. Ethereum and its economic impact due to Smart Contracts: Ethereum is underscored for its influence in transforming blockchain from a mere financial tool into a platform for decentralized applications (DApps). The emergence of Ethereum gave rise to various decentralized finance (DeFi) projects, opening gateways to innovation in financial products and services.
5. Stellar and Solana showcase scalability and speed. Solana's focus on scalability positions it as significant competition to Ethereum by offering higher throughput and lower transaction fees.
6. Other cryptocurrencies such as Tron, Tether (USDT), and other stablecoins highlight efforts to integrate cryptocurrencies with fiat currencies, facilitating usage beyond speculative investment into everyday transactions. Tether's pegging mechanism ensures stability and broad acceptance in digital transactions across platforms.
7. XRP's role in cross-border transactions offered by Ripple Labs presents innovations in the settlement of international payments, providing reduced costs and improved transaction times across borders.

This taxonomy's presentation is pertinent for researchers and practitioners within the cryptocurrency field, offering a visual documentation of the diverse, dynamic, and multifaceted cryptocurrency environment. The document exemplifies the progression and categorization of blockchain-based technologies. Future research can analyze the evolving roles of such cryptocurrencies, examining further improvements and challenges in scalability, energy consumption, regulation, and market behavior within the cryptocurrency sphere.