Memecoin Shiba Inu saw its price grow by more than 300 percent within one and the same month, marking a trading fury reminiscent of Dogecoin in early 2021. Indeed, the SHIB coin ranked as one of the biggest crypto in the world based on 24h trading volume in October 2021 - with trading activity being almost as high as that of Ethereum. Originally starting out as a fun token based on the famous Japanese dog breed, the digital currency grabbed mainstream attention in 2021 probably due to its low barrier of entry: Even after its price spikes, Shiba Inu was one of the cheapest coins available, especially when compared to the price of 99 other cryptocurrencies. Combine this with survey information that most consumers in the U.S. and the UK invest in crypto either for growth or fun, and Shiba Inu is probably seen by many as a relatively simple, "quick win" investment. As of May 19, 2025, the price of one million Shiba Inu is 14.08.

Somewhat resembling developments of Dogecoin in early 2021, the market cap of Shiba Inu (SHIB) more than tripled in only a few weeks. This rapid growth especially occurred since September 2021, with the cryptocurrency breaking the ** billion U.S. dollar barrier multiple in the following month. Whilst no exact reason was given why the memecoin grew so fast during this time, the digital currency did become available on Coinbase, one of the world's most well-known crypto exchanges, on September 17. This move, and the fact that consumers in the U.S. and the UK overall tend to invest in crypto for fun or as a potential growth investment, might explain the popularity of the dog-themed coin. Indeed, Shiba Inu ranked as the number ** cryptocurrency in the world based on market cap in late October 2021 - closely behind DeFi-affilated like Uniswap (UNI) and Terra (LUNA).

Shiba Inu trading volume accelerated significantly in October 2021, as the *** trade volume grew from roughly *********** U.S. dollars into double digits. Whilst the cryptocurrency based on the famous Japanese dog breed already had a trading peak early in ********, ************ could be seen as the breakthrough month for the coin as it became one of the most valuable cryptocurrencies available. The meme-inspired digital currency saw a major price increase during this month, as it invoked a similar sentiment as to early 2021 when Dogecoin became a popular cryptocurrency to invest in.

Cryptocurrency historical datasets from January 2012 (if available) to October 2021 were obtained and integrated from various sources and Application Programming Interfaces (APIs) including Yahoo Finance, Cryptodownload, CoinMarketCap, various Kaggle datasets, and multiple APIs. While these datasets used various formats of time (e.g., minutes, hours, days), in order to integrate the datasets days format was used for in this research study. The integrated cryptocurrency historical datasets for 80 cryptocurrencies including but not limited to Bitcoin (BTC), Ethereum (ETH), Binance Coin (BNB), Cardano (ADA), Tether (USDT), Ripple (XRP), Solana (SOL), Polkadot (DOT), USD Coin (USDC), Dogecoin (DOGE), Tron (TRX), Bitcoin Cash (BCH), Litecoin (LTC), EOS (EOS), Cosmos (ATOM), Stellar (XLM), Wrapped Bitcoin (WBTC), Uniswap (UNI), Terra (LUNA), SHIBA INU (SHIB), and 60 more cryptocurrencies were uploaded in this online Mendeley data repository. Although the primary attribute of including the mentioned cryptocurrencies was the Market Capitalization, a subject matter expert i.e., a professional trader has also guided the initial selection of the cryptocurrencies by analyzing various indicators such as Relative Strength Index (RSI), Moving Average Convergence/Divergence (MACD), MYC Signals, Bollinger Bands, Fibonacci Retracement, Stochastic Oscillator and Ichimoku Cloud. The primary features of this dataset that were used as the decision-making criteria of the CLUS-MCDA II approach are Timestamps, Open, High, Low, Closed, Volume (Currency), % Change (7 days and 24 hours), Market Cap and Weighted Price values. The available excel and CSV files in this data set are just part of the integrated data and other databases, datasets and API References that was used in this study are as follows: [1] https://finance.yahoo.com/ [2] https://coinmarketcap.com/historical/ [3] https://cryptodatadownload.com/ [4] https://kaggle.com/philmohun/cryptocurrency-financial-data [5] https://kaggle.com/deepshah16/meme-cryptocurrency-historical-data [6] https://kaggle.com/sudalairajkumar/cryptocurrencypricehistory [7] https://min-api.cryptocompare.com/data/price?fsym=BTC&tsyms=USD [8] https://min-api.cryptocompare.com/ [9] https://p.nomics.com/cryptocurrency-bitcoin-api [10] https://www.coinapi.io/ [11] https://www.coingecko.com/en/api [12] https://cryptowat.ch/ [13] https://www.alphavantage.co/

This dataset is part of the CLUS-MCDA (Cluster analysis for improving Multiple Criteria Decision Analysis) and CLUS-MCDAII Project: https://aimaghsoodi.github.io/CLUSMCDA-R-Package/ https://github.com/Aimaghsoodi/CLUS-MCDA-II https://github.com/azadkavian/CLUS-MCDA