Price swings of Bitcoin increased substantially in November 2022, recording a 10-day volatility of more than *** percent. Measured in a metric called volatility, the percentage shown here reflect how much the price of BTC in U.S. dollars changed historically over a preceding 7-day window. Changes can be either up or down, with a higher volatility reflecting that an asset is more risky, as price movements are less easy to predict and can swing in any direction. The volatility metric referred to here is called "realized volatility", otherwise known as "historic volatility" and describes these price swings over a given period of time - and consequently is not looking into the future. Despite the rise of several cryptocurrencies since 2021, Bitcoin still had the highest market share ("dominance") of all cryptocurrencies in 2022.

The CAPIVIX Index gives crypto traders something traditional markets have long relied on - a clear measure of expected market volatility. Think of it as the VIX for Bitcoin and Ethereum, showing what the market anticipates for price swings over the next 30 days.

This crypto volatility index tracks market sentiment for BTC/USD and ETH/USD pairs by analyzing options data from major derivatives exchanges. When CAPIVIX rises, it signals increased uncertainty and potential turbulence ahead. When it falls, markets are expecting calmer conditions.

What makes CAPIVIX valuable is its methodology - we've adapted the widely-trusted VIX calculation approach to work specifically with cryptocurrency options. This gives you a standardized way to gauge market anxiety or confidence across different market conditions.

The index updates continuously throughout trading hours, incorporating real-time options pricing to reflect the market's evolving risk perception. For traders and investors looking to understand market sentiment beyond price movements alone, CAPIVIX provides that crucial additional dimension of market intelligence.

➡️ Why choose us?

📊 Market Coverage & Data Types: ◦ Real-time and historical data since 2010 (for chosen assets) ◦ Full order book depth (L2/L3) ◦ Trade-by-trade data ◦ OHLCV across multiple timeframes ◦ Market indexes (VWAP, PRIMKT) ◦ Exchange rates with fiat pairs ◦ Spot, futures, options, and perpetual contracts ◦ Coverage of 90%+ global trading volume ◦ Bitcoin Price Data

🔧 Technical Excellence: ◦ 99% uptime guarantee ◦ Multiple delivery methods: REST, WebSocket, FIX, S3 ◦ Standardized data format across exchanges ◦ Ultra-low latency data streaming ◦ Detailed documentation ◦ Custom integration assistance

Whether you're hedging positions, timing entries and exits, or just wanting to better understand market psychology, our Bitcoin and Ethereum volatility data offers valuable insights into what the market collectively expects in the weeks ahead.

It is estimated that the cumulative market cap of cryptocurrencies increased in early 2023 after the downfall in November 2022 due to FTX. That value declined in the summer of 2023, however, as international uncertainty grew over a potential recession. Bitcoin's market cap comprised the majority of the overall market capitalization. What is market cap? Market capitalization is a financial measure typically used for publicly traded firms, computed by multiplying the share price by the number of outstanding shares. However, cryptocurrency analysts calculate it as the price of the virtual currencies times the number of coins in the market. This gives cryptocurrency investors an idea of the overall market size, and watching the evolution of the measure tells how much money is flowing in or out of each cryptocurrency. Cryptocurrency as an investment The price of Bitcoin has been erratic, and most other cryptocurrencies follow its larger price swings. This volatility attracts investors who hope to buy when the price is low and sell at its peak, turning a profit. However, this does little for price stability. As such, few firms accept payment in cryptocurrencies. As of June 25, 2025, the cumulative market cap of cryptocurrencies reached a value of ******.

In March 2024 Bitcoin BTC reached a new all-time high with prices exceeding 73000 USD marking a milestone for the cryptocurrency market This surge was due to the approval of Bitcoin exchange-traded funds ETFs in the United States allowing investors to access Bitcoin without directly holding it This development increased Bitcoin’s credibility and brought fresh demand from institutional investors echoing previous price surges in 2021 when Tesla announced its 15 billion investment in Bitcoin and Coinbase was listed on the Nasdaq By the end of 2022 Bitcoin prices dropped sharply to 15000 USD following the collapse of cryptocurrency exchange FTX and its bankruptcy which caused a loss of confidence in the market By August 2024 Bitcoin rebounded to approximately 64178 USD but remained volatile due to inflation and interest rate hikes Unlike fiat currency like the US dollar Bitcoin’s supply is finite with 21 million coins as its maximum supply By September 2024 over 92 percent of Bitcoin had been mined Bitcoin’s value is tied to its scarcity and its mining process is regulated through halving events which cut the reward for mining every four years making it harder and more energy-intensive to mine The next halving event in 2024 will reduce the reward to 3125 BTC from its current 625 BTC The final Bitcoin is expected to be mined around 2140 The energy required to mine Bitcoin has led to criticisms about its environmental impact with estimates in 2021 suggesting that one Bitcoin transaction used as much energy as Argentina Bitcoin’s future price is difficult to predict due to the influence of large holders known as whales who own about 92 percent of all Bitcoin These whales can cause dramatic market swings by making large trades and many retail investors still dominate the market While institutional interest has grown it remains a small fraction compared to retail Bitcoin is vulnerable to external factors like regulatory changes and economic crises leading some to believe it is in a speculative bubble However others argue that Bitcoin is still in its early stages of adoption and will grow further as more institutions and governments recognize its potential as a hedge against inflation and a store of value 2024 has also seen the rise of Bitcoin Layer 2 technologies like the Lightning Network which improve scalability by enabling faster and cheaper transactions These innovations are crucial for Bitcoin’s wider adoption especially for day-to-day use and cross-border remittances At the same time central bank digital currencies CBDCs are gaining traction as several governments including China and the European Union have accelerated the development of their own state-controlled digital currencies while Bitcoin remains decentralized offering financial sovereignty for those who prefer independence from government control The rise of CBDCs is expected to increase interest in Bitcoin as a hedge against these centralized currencies Bitcoin’s journey in 2024 highlights its growing institutional acceptance alongside its inherent market volatility While the approval of Bitcoin ETFs has significantly boosted interest the market remains sensitive to events like exchange collapses and regulatory decisions With the limited supply of Bitcoin and improvements in its transaction efficiency it is expected to remain a key player in the financial world for years to come Whether Bitcoin is currently in a speculative bubble or on a sustainable path to greater adoption will ultimately be revealed over time.

Description

This dataset, titled "Cryptocurrency Market Sentiment & Prediction," is a synthetic collection of real-time crypto market data designed for advanced analysis and predictive modeling. It captures a comprehensive range of features including price movements, social sentiment, news impact, and trading patterns for 10 major cryptocurrencies. Tailored for data scientists and analysts, this dataset is ideal for exploring market volatility, sentiment analysis, and price prediction, particularly in the context of significant events like the Bitcoin halving in 2024 and increasing institutional adoption.

Key Features Overview: - Price Movements: Tracks current prices and 24-hour price change percentages to reflect market dynamics. - Social Sentiment: Measures sentiment scores from social media platforms, ranging from -1 (negative) to 1 (positive), to gauge public perception. - News Sentiment and Impact: Evaluates sentiment from news sources and quantifies their potential impact on market behavior. - Trading Patterns: Includes data on 24-hour trading volumes and market capitalization, crucial for understanding market activity. - Technical Indicators: Features metrics like the Relative Strength Index (RSI), volatility index, and fear/greed index for in-depth technical analysis. - Prediction Confidence: Provides a confidence score for predictive models, aiding in assessing forecast reliability.

Purpose and Applications: - Perfect for machine learning tasks such as price prediction, sentiment-price correlation studies, and volatility classification. - Supports time series analysis for forecasting price movements and identifying volatility clusters. - Valuable for research into the influence of social media and news on cryptocurrency markets, especially during high-impact events.

Dataset Scope: - Covers a simulated 30-day period, offering a snapshot of market behavior under varying conditions. - Focuses on major cryptocurrencies including Bitcoin, Ethereum, Cardano, Solana, and others, ensuring relevance to current market trends.

Dataset Structure Table:

Dataset Statistics Table:

This dataset is a powerful resource for machine learning projects, sentiment analysis, and crypto market research, providing a robust foundation for AI/ML model development and testing.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Bitcoin Volatility: A Leading Indicator of Stock Volatility?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Our extensive historical database captures every significant market movement, from the earliest Bitcoin trades through today's crypto ecosystem, across 350+ global exchanges.

This rich historical dataset serves multiple critical functions: from enabling sophisticated strategy backtesting and long-term trend analysis to supporting academic research and trading pattern identification. Whether analyzing market volatility, studying price correlations, or conducting deep market research, our historical data provides the reliable foundation needed for meaningful cryptocurrency market analysis.

Why work with us?

Market Coverage & Data Types: - Real-time and historical data since 2010 (for chosen assets) - Full order book depth (L2/L3) - Tick-by-tick data - OHLCV across multiple timeframes - Market indexes (VWAP, PRIMKT) - Exchange rates with fiat pairs - Spot, futures, options, and perpetual contracts - Coverage of 90%+ global trading volume - Full Cryptocurrency Investor Data

Technical Excellence: - 99,9% uptime guarantee - Multiple delivery methods: REST, WebSocket, FIX, S3 - Standardized data format across exchanges - Ultra-low latency data streaming - Detailed documentation - Custom integration assistance

CoinAPI serves hundreds of institutions worldwide, from trading firms and hedge funds to research organizations and technology providers. Our commitment to data quality and technical excellence makes us the trusted choice for cryptocurrency market data needs.

On-Chain Metrics.xlsx contains a description of the on-chain metrics. Merged_df.xlsx is the main data source containing the BTC prices, the on-chain metrics and the sentiment scores. btc_twets_new.csv and training.1600000.processed.noemoticon.csv are the data sources for calculating the sentiment scores. Sentiment_Analysis.py contains the code to calculate the sentiment scores. The scores are in Merged_df.xlsx BTC_Prediction.py contains the implementation of the main approach described in the paper, especially in Fig. 11.

The authors examine the relation between price returns and volatility changes in the Bitcoin market using a daily database denominated in various currencies. The results for the entire period provide no evidence of an asymmetric return-volatility relation in the Bitcoin market. They test if there is a difference in the return-volatility relation before and after the price crash of 2013 and show a significant inverse relation between past shocks and volatility before the crash and no significant relation after. This finding shows that, prior to the price crash of December 2013, positive shocks increased the conditional volatility more than negative shocks. This inverted asymmetric reaction of Bitcoin to positive and negative shocks is contrary to what the authors observe in equities. As leverage effect and volatility feedback don’t adequately explain this reaction, they propose the safe-haven effect (Baur, Asymmetric volatility in the gold market, 2012). The authors highlight the benefits of adding Bitcoin to a US equity portfolio, especially in the pre-crash period. Robustness analyses show, among others, a negative relation between the US implied volatility index (VIX) and Bitcoin volatility. Those additional analyses further support their findings and provide useful information for economic actors who are interested in adding Bitcoin to their equity portfolios or are curious about the capabilities of Bitcoin as a financial asset.

Figshare Dataset DescriptionTitle: The Economic Bomb Dataset: Bitcoin Volatility, Institutional Shorting, and ETF Outflows (2021–2024)Description:This dataset supports the research presented in The Economic Bomb: A Strategic Financial Warfare Tactic, which examines Bitcoin's volatility, institutional shorting, and the impact of ETF outflows on market behavior. Covering the period from January 2021 to December 2024, the dataset includes raw financial data, processed analytical outputs, and visualizations that illustrate volatility patterns, delayed market reactions, and potential price manipulation.The dataset is divided into the following components:Raw Data: Daily BTC price movements, ETF holdings and outflows, whale wallet transactions, and institutional shorting positions from Binance, Coinbase, Glassnode, and other sources.Processed Data: Calculated BTC returns, volatility measures, and sentiment scores from social media platforms such as Twitter, Reddit, Google News, and YouTube.Simulations: Monte Carlo simulations, Decker Sentiment-Short Interest Model (DSSIM), GARCH model forecasts, and VAR model analyses that quantify volatility clustering and delayed market responses.Visual Aids: Correlation matrices, heatmaps, and line charts that visualize key patterns, including volatility spikes following ETF outflows and whale wallet movements.This dataset is designed to support research into cryptocurrency volatility, institutional influence, and market manipulation. It is suitable for use in academic studies, financial modeling, and data-driven investment strategies. Detailed captions and preprocessing information are provided to ensure transparency and reproducibility.Keywords: Bitcoin Volatility, Institutional Shorting, ETF Outflows, Whale Wallet Movements, Cryptocurrency Market Manipulation, Monte Carlo Simulation, GARCH Model, VAR Model, Financial Data VisualizationLicense: CC BY 4.0 (Attribution required)DOI: 10.17632/xn9ws8x6j7.2Citation:Decker, Nicolin (2025), The Economic Bomb: A Strategic Financial Warfare Tactic, Mendeley Data, V2, DOI: 10.17632/xn9ws8x6j7.2, Available at SSRN: Link to SSRNContact: Nicolin Decker, Independent Researcher, Email: nicolindecker144@gmail.com

CoinAPI delivers Crypto Options Data and derivatives information from major exchanges. Access real-time and historical crypto market data to analyze volatility, pricing trends, and open interest across option chains.

Crypto Asset Management Market size was valued at USD 1064.87 Million in 2023 and is projected to reach USD 6080.37 Million by 2031, growing at a CAGR of 26.84% from 2024 to 2031.

Global Crypto Asset Management Market Drivers

The market drivers for the Crypto Asset Management Market can be influenced by various factors. These may include:

Growing Adoption of Cryptocurrencies: As more people and organisations use cryptocurrencies for trading and investing, there is an increasing need for these digital assets to be managed effectively. This is what makes advanced crypto asset management systems necessary. Institutional Investment: Big businesses and financial organisations are getting more involved in the bitcoin market. Their presence in the market requires substantial resources and credibility, which makes sophisticated asset management services necessary to manage big investments and regulatory obligations. Technological Advancements: The usability, security, and usefulness of crypto asset management platforms are improved by ongoing developments in blockchain technology and digital finance. This encourages more investors and consumers to use these technologies. Regulatory Developments: Investor trust rises as governments and regulatory organisations set more precise rules and regulations for cryptocurrencies. Regulatory certainty contributes to market expansion by lowering the risks involved in cryptocurrency investments. Security Issues and Solutions: The need for safe asset management solutions is being driven by the increasing awareness of the cybersecurity dangers related to the storage and transactions of cryptocurrencies. There is a specific demand for providers that offer greater security features. Portfolio diversification: Cryptocurrency is becoming a more popular component of investment strategy for investors looking to broaden their holdings. The demand for all-inclusive asset management services that can combine traditional and digital assets is increased by this development. Growth of Decentralised Finance (DeFi): One important factor is the appearance of DeFi platforms, which let people conduct financial transactions without the need for middlemen. For these platforms to securely handle a variety of assets and transactions, they need strong management solutions. Market Volatility and Risk Management: Robust risk management techniques are needed due to the intrinsic volatility of the bitcoin market. Tools for managing cryptocurrency assets let investors keep an eye on and control their holdings, reducing the risk of losses. Increasing Interest in Blockchain Technology: Investment in the cryptocurrency market is driven by a growing interest in blockchain technology beyond cryptocurrencies, including smart contracts and decentralised apps (dApps). Solutions for asset management are essential for navigating this growing ecology. Enhanced Knowledge and Education: As blockchain technology and cryptocurrencies become more widely known, so do educational programmes, more individuals are starting to feel at peace with investing in digital assets. The need for tools to efficiently manage these investments is driven by this rising familiarity.

Description 📊

This dataset provides a comprehensive historical record of Bitcoin price movements in USD over time. The data has been sourced from Yahoo Finance, a reputable financial data provider, and includes a range of valuable information for anyone interested in analyzing or understanding the cryptocurrency market.

Data Columns 📈

1. Date:📅 This column represents the date of each recorded data point. It serves as the timestamp for each observation, allowing users to track Bitcoin's price changes over time.

2. Closing Price (USD):💰 The closing price is the last traded price of Bitcoin in USD at the end of each trading day. It is a crucial metric for investors and traders, as it reflects the market sentiment and overall performance for that specific day.

3. 24h Open (USD):🌄This column represents the opening price of Bitcoin in USD for the given 24-hour trading period. The opening price is the value at which Bitcoin started trading at the beginning of the day, and it can provide insights into market sentiment and potential price trends.

4. 24h High (USD):🚀 The 24-hour high price indicates the highest price level reached by Bitcoin in USD within the given 24-hour trading window. It is valuable for identifying the day's price volatility and potential price resistance levels.

5. 24h Low (USD):📉 This column represents the lowest price level Bitcoin reached in USD during the 24-hour trading period. The 24-hour low is crucial for identifying potential support levels and understanding the cryptocurrency's price range for the day.

Analyzing this dataset can offer insights into Bitcoin's historical price trends, volatility, and potential trading strategies. Researchers and analysts can use this data to perform technical and fundamental analyses, build predictive models, or gain a better understanding of the cryptocurrency market's behavior over time.

However, It's important to note that Bitcoin operates within an open market framework, and any analysis or strategies developed should not be considered as financial advice.

This dataset is your playground for building models, crafting algorithms, and enhancing your data analysis skills. Dive in, explore, and enjoy the learning process. Happy data exploration!🚀📈💡

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

S&P Bitcoin index forecast: Potential Volatility Ahead

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Analysis of ‘Crypto Fear and Greed Index’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/adelsondias/crypto-fear-and-greed-index on 13 February 2022.

--- Dataset description provided by original source is as follows ---

Crypto Fear and Greed Index

Each day, the website https://alternative.me/crypto/fear-and-greed-index/ publishes this index based on analysis of emotions and sentiments from different sources crunched into one simple number: The Fear & Greed Index for Bitcoin and other large cryptocurrencies.

Why Measure Fear and Greed?

The crypto market behaviour is very emotional. People tend to get greedy when the market is rising which results in FOMO (Fear of missing out). Also, people often sell their coins in irrational reaction of seeing red numbers. With our Fear and Greed Index, we try to save you from your own emotional overreactions. There are two simple assumptions:

• Extreme fear can be a sign that investors are too worried. That could be a buying opportunity.
• When Investors are getting too greedy, that means the market is due for a correction.

Therefore, we analyze the current sentiment of the Bitcoin market and crunch the numbers into a simple meter from 0 to 100. Zero means "Extreme Fear", while 100 means "Extreme Greed". See below for further information on our data sources.

Data Sources

We are gathering data from the five following sources. Each data point is valued the same as the day before in order to visualize a meaningful progress in sentiment change of the crypto market.

First of all, the current index is for bitcoin only (we offer separate indices for large alt coins soon), because a big part of it is the volatility of the coin price.

But let’s list all the different factors we’re including in the current index:

Volatility (25 %)

We’re measuring the current volatility and max. drawdowns of bitcoin and compare it with the corresponding average values of the last 30 days and 90 days. We argue that an unusual rise in volatility is a sign of a fearful market.

Market Momentum/Volume (25%)

Also, we’re measuring the current volume and market momentum (again in comparison with the last 30/90 day average values) and put those two values together. Generally, when we see high buying volumes in a positive market on a daily basis, we conclude that the market acts overly greedy / too bullish.

Social Media (15%)

While our reddit sentiment analysis is still not in the live index (we’re still experimenting some market-related key words in the text processing algorithm), our twitter analysis is running. There, we gather and count posts on various hashtags for each coin (publicly, we show only those for Bitcoin) and check how fast and how many interactions they receive in certain time frames). A unusual high interaction rate results in a grown public interest in the coin and in our eyes, corresponds to a greedy market behaviour.

Surveys (15%) currently paused

Together with strawpoll.com (disclaimer: we own this site, too), quite a large public polling platform, we’re conducting weekly crypto polls and ask people how they see the market. Usually, we’re seeing 2,000 - 3,000 votes on each poll, so we do get a picture of the sentiment of a group of crypto investors. We don’t give those results too much attention, but it was quite useful in the beginning of our studies. You can see some recent results here.

Dominance (10%)

The dominance of a coin resembles the market cap share of the whole crypto market. Especially for Bitcoin, we think that a rise in Bitcoin dominance is caused by a fear of (and thus a reduction of) too speculative alt-coin investments, since Bitcoin is becoming more and more the safe haven of crypto. On the other side, when Bitcoin dominance shrinks, people are getting more greedy by investing in more risky alt-coins, dreaming of their chance in next big bull run. Anyhow, analyzing the dominance for a coin other than Bitcoin, you could argue the other way round, since more interest in an alt-coin may conclude a bullish/greedy behaviour for that specific coin.

Trends (10%)

We pull Google Trends data for various Bitcoin related search queries and crunch those numbers, especially the change of search volumes as well as recommended other currently popular searches. For example, if you check Google Trends for "Bitcoin", you can’t get much information from the search volume. But currently, you can see that there is currently a +1,550% rise of the query „bitcoin price manipulation“ in the box of related search queries (as of 05/29/2018). This is clearly a sign of fear in the market, and we use that for our index.

There's a story behind every dataset and here's your opportunity to share yours.

Copyright disclaimer

This dataset is produced and maintained by the administrators of https://alternative.me/crypto/fear-and-greed-index/.

This published version is an unofficial copy of their data, which can be also collected using their API (e.g., GET https://api.alternative.me/fng/?limit=10&format=csv&date_format=us).

--- Original source retains full ownership of the source dataset ---

The Bitcoin (BTC) price again reached an all-time high in 2025, as values exceeded over 117,901.63 USD on July 20, 2025. Price hikes in early 2025 were connected to the approval of Bitcoin ETFs in the United States, while previous hikes in 2021 were due to events involving Tesla and Coinbase, respectively. Tesla's announcement in March 2021 that it had acquired 1.5 billion U.S. dollars' worth of the digital coin, for example, as well as the IPO of the U.S.'s biggest crypto exchange, fueled mass interest. The market was noticeably different by the end of 2022, however, after another crypto exchange, FTX, filed for bankruptcy.Is the world running out of Bitcoin?Unlike fiat currency like the U.S. dollar - as the Federal Reserve can simply decide to print more banknotes - Bitcoin's supply is finite: BTC has a maximum supply embedded in its design, of which roughly 89 percent had been reached in April 2021. It is believed that Bitcoin will run out by 2040, despite more powerful mining equipment. This is because mining becomes exponentially more difficult and power-hungry every four years, a part of Bitcoin's original design. Because of this, a Bitcoin mining transaction could equal the energy consumption of a small country in 2021.Bitcoin's price outlook: a potential bubble?Cryptocurrencies have few metrics available that allow for forecasting, if only because it is rumored that only a few cryptocurrency holders own a large portion of the available supply. These large holders - referred to as 'whales'-are' said to make up two percent of anonymous ownership accounts, while owning roughly 92 percent of BTC. On top of this, most people who use cryptocurrency-related services worldwide are retail clients rather than institutional investors. This means outlooks on whether Bitcoin prices will fall or grow are difficult to measure, as movements from one large whale are already having a significant impact on this market.

Descriptive statistics of Bitcoin return and realized volatility.

Crypto Trading Bot Market Outlook

The global crypto trading bot market size was valued at approximately $1.2 billion in 2023 and is projected to reach $4.5 billion by 2032, reflecting an impressive CAGR of 15.6% over the forecast period. This significant growth is fueled by several factors, including the rising adoption of cryptocurrencies, increasing market volatility, and the growing demand for automation in trading activities.

One of the primary growth factors in the crypto trading bot market is the increasing popularity and acceptance of cryptocurrencies worldwide. As digital assets like Bitcoin, Ethereum, and other altcoins continue to gain mainstream acceptance, more investors are entering the market. This influx of new participants creates a demand for tools that can help manage and optimize trading activities, leading to the increased adoption of crypto trading bots. These automated systems can execute trades based on predefined criteria, helping both novice and experienced traders to capitalize on market opportunities while minimizing risks.

Another driving factor is the heightened market volatility associated with cryptocurrencies. Unlike traditional financial markets, the cryptocurrency market operates 24/7 and is known for its rapid price fluctuations. This volatility can present both significant opportunities and challenges for traders. Crypto trading bots can help navigate this unpredictable landscape by continuously monitoring the market and executing trades in real-time, thus allowing traders to exploit price differentials and mitigate potential losses. The enhanced precision and speed offered by these bots are critical in such a fast-paced environment.

The growing demand for automation in trading activities is also propelling the crypto trading bot market forward. In an era where time is of the essence, automated trading solutions offer a way to streamline trading processes and eliminate the need for constant manual monitoring. By implementing advanced algorithms and machine learning techniques, crypto trading bots can analyze vast amounts of data, identify patterns, and make informed decisions without human intervention. This automation not only improves trading efficiency but also reduces human error, making it an attractive option for both individual and institutional investors.

Bitcoin Trading has become an integral part of the cryptocurrency ecosystem, attracting both retail and institutional investors. As the most recognized and widely traded cryptocurrency, Bitcoin serves as a gateway for many into the world of digital assets. The volatility and liquidity of Bitcoin make it an attractive option for traders looking to capitalize on short-term price movements. With the advent of automated trading solutions, such as crypto trading bots, Bitcoin Trading has become more accessible and efficient. These bots can execute trades based on market signals and predefined strategies, allowing traders to take advantage of Bitcoin's price fluctuations without the need for constant monitoring. The integration of Bitcoin Trading into automated systems highlights the evolving nature of cryptocurrency trading, where technology plays a crucial role in optimizing performance and managing risk.

Regionally, North America holds a significant share of the crypto trading bot market, driven by the high adoption rate of cryptocurrencies and technological advancements in the region. The presence of major market players and favorable regulatory frameworks also contribute to this dominance. Europe and Asia Pacific are also witnessing substantial growth, with increasing awareness and acceptance of digital assets. The Asia Pacific region, in particular, is expected to register the highest CAGR during the forecast period, fueled by the rising number of cryptocurrency exchanges and growing investment in blockchain technology. Meanwhile, Latin America and the Middle East & Africa are also emerging markets, gradually embracing crypto trading and automation technologies.

Bot Type Analysis

The crypto trading bot market is segmented by bot type, including arbitrage bots, market-making bots, trend-following bots, coin lending bots, and others. Each of these bot types offers unique functionalities tailored to different trading strategies and objectives.

Arbitrage bots capitalize on price discrepancies across different cryptocurrency exchanges. By buying low on one exchange and selling high on another, these bots

This repository contains data collected from the bitcoin options exchange Deribit and the R codes used in the following paper: Lai T. Hoang, Dirk G. Baur, 2020, Forecasting Bitcoin Volatility: Evidence from the Options Market.

This dataset appears to be a time series dataset containing financial market data, specifically related to a certain asset or cryptocurrency. The columns in the dataset represent various financial metrics and market attributes. Here's a brief description of each column:

Date (Start-End): This column likely represents the time period for which the data is recorded, with a start and end date for each entry.

Open: The opening price of the asset or cryptocurrency at the beginning of the time period.

High: The highest price reached during the time period.

Low: The lowest price reached during the time period.

Close: The closing price of the asset or cryptocurrency at the end of the time period.

Volume: The trading volume, which typically represents the total number of units of the asset traded during the time period.

Market Cap: The market capitalization, which is often the product of the closing price and the total supply of the asset.

This dataset can be used for various financial and statistical analyses, including studying price trends, volatility, and trading volume over time. It may be particularly useful for analyzing the performance of the asset or cryptocurrency over the given time frame and identifying patterns or insights for investment or trading strategies.