Snehasish CHINARA

XRP: Pioneering Financial Revolution

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Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains the cryptocurrency XRP/Ripple.

Historical context and background

XRP, the digital currency associated with the Ripple network, emerged against the backdrop of a growing interest in blockchain technology and its potential applications beyond cryptocurrencies. The development of Ripple began in 2012 when Jed McCaleb, Chris Larsen, and Arthur Britto joined forces to create a decentralized digital currency system. Ripple Labs, the company behind XRP, aimed to address the inefficiencies in traditional cross-border payments by providing a fast and cost-effective alternative. Unlike Bitcoin, which relies on a proof-of-work consensus mechanism, Ripple utilizes a unique consensus algorithm called the Ripple Protocol Consensus Algorithm (RPCA). The XRP Ledger, the underlying technology, is designed to facilitate quick and secure transactions, making it particularly appealing for financial institutions. Over the years, Ripple has garnered both support and criticism within the crypto community due to its centralized nature and ongoing legal challenges. Nevertheless, its focus on facilitating seamless global transactions has positioned XRP as a significant player in the evolving landscape of digital assets.

XRP Logo

Source: Yahoo! Finance

Figure 1. Key Dates in XRP History

Source: Yahoo! Finance and other internet sources

Key features and use cases

  • Fast and Low-Cost Transactions: One of the primary features of XRP is its speed and cost-effectiveness. The XRP Ledger is capable of processing transactions in just a few seconds, making it significantly faster than traditional banking systems and some other cryptocurrencies. The low transaction fees associated with XRP contribute to its appeal for cross-border payments.

  • Liquidity and Scalability: XRP is designed to handle a high volume of transactions, providing liquidity for financial institutions. This scalability is crucial for the adoption of XRP in large-scale financial applications, including remittances and institutional transfers.

  • Interoperability: Ripple aims to facilitate interoperability between different financial systems. XRP can act as a bridge currency between fiat currencies, enabling seamless and efficient transactions across borders. This interoperability is particularly valuable in the context of global finance.

  • Decentralization with Unique Consensus Algorithm: While Ripple has faced criticism for some aspects of centralization, the XRP Ledger employs the Ripple Protocol Consensus Algorithm (RPCA) for transaction validation. This consensus mechanism is more energy-efficient compared to proof-of-work used by some other cryptocurrencies.

  • Partnerships with Financial Institutions: Ripple has formed partnerships with various financial institutions, including banks and payment service providers. The aim is to leverage XRP for real-time, cross-border payments, reducing settlement times and costs for these institutions.

  • Smart Contracts and Tokenization: Ripple has also explored adding smart contract functionality to the XRP Ledger, expanding its use cases beyond simple transactions. Additionally, the platform has the potential for tokenization of real-world assets, allowing for the representation of various assets on the blockchain.

  • Stability and Predictable Supply: XRP has a fixed supply of 100 billion tokens, with a portion held by Ripple Labs. This fixed supply aims to provide stability and predictability, which could be attractive for businesses and investors.

While XRP has faced regulatory challenges and debates about its decentralization, its unique features and focus on solving real-world financial issues position it as a cryptocurrency with substantial potential in the global financial landscape.

Technology and underlying blockchain

XRP, the cryptocurrency associated with the Ripple network, operates on a distinct technological framework, utilizing a consensus algorithm that sets it apart from traditional proof-of-work systems. At the heart of XRP’s technology is the XRP Ledger, a decentralized blockchain that enables fast and secure transactions. The unique consensus mechanism employed by Ripple is known as the Ripple Protocol Consensus Algorithm (RPCA). Unlike the energy-intensive mining processes seen in proof-of-work systems, RPCA operates on a consensus model that involves a network of independent validators reaching agreement on the order and validity of transactions. This consensus mechanism allows the XRP Ledger to achieve high throughput and swift confirmation times, making it well-suited for the efficient processing of cross-border payments and financial transactions. Additionally, the XRP Ledger supports the issuance of various tokens, potentially expanding its use cases beyond its native cryptocurrency. Despite debates about the decentralization of Ripple, the technology behind XRP continues to evolve, showcasing a commitment to addressing the challenges and opportunities in the rapidly evolving blockchain and cryptocurrency space. Additionally, the platform has explored the integration of smart contract functionality, opening possibilities for more complex and programmable transactions. The focus on scalability, interoperability, and speed positions XRP as a blockchain solution tailored for the demands of the global financial industry, particularly in the context of cross-border payments and remittances.

Supply of coins

The supply dynamics of XRP, the native cryptocurrency of the Ripple network, play a crucial role in shaping its market characteristics. Unlike Bitcoin, which relies on a mining process to gradually release new coins into circulation, XRP was created with its entire supply generated at inception. XRP has a fixed maximum supply of 100 billion coins, a feature that distinguishes it from some other cryptocurrencies with potentially infinite supplies. Notably, a substantial portion of the XRP supply is held by Ripple Labs, the company behind the cryptocurrency. Approximately 55 billion XRP are held in escrow by Ripple Labs, the company behind the development of the Ripple protocol. This escrow mechanism is designed to release a specific amount of XRP into circulation each month, reducing the potential for market manipulation and ensuring a predictable supply trajectory.

This allocation has been a point of discussion and scrutiny within the crypto community, with debates surrounding the potential impact of such centralization on the coin’s decentralization ethos. Ripple has taken steps to address concerns, implementing strategies such as the escrow system, which locks a large amount of XRP in time-released contracts to be gradually released into circulation. The controlled release aims to provide transparency and mitigate concerns related to sudden market influxes. The fixed supply, along with Ripple’s strategic initiatives, contributes to the stability and predictability of XRP in the market, influencing investor perceptions and shaping the overall market dynamics of the cryptocurrency.

Figure 2. Number of XRP Transaction per Day

Source: BitInfoCharts (Ethereum Transactions historical chart)

Historical data for XRP

How to get the data?

The XRP is popular cryptocurrency on the market, and historical data for the XRP such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for XRP on Yahoo! Finance (the Yahoo! code for XRP is XRP-USD).

Figure 3. XRP data

Source: Yahoo! Finance

Historical data for the XRP market prices

Access to historical data on XRP, the cryptocurrency affiliated with Ripple, offers investors valuable insights and tools for decision-making. By analyzing past price trends and patterns, investors can better anticipate potential movements in XRP’s value, aiding in strategic buy or sell decisions. Historical data also serves as a record of XRP’s volatility, allowing investors to assess and manage risks effectively. Examining market sentiment during different periods provides a nuanced understanding of external factors that may impact XRP, such as regulatory developments or technological upgrades. Additionally, historical performance comparisons with other cryptocurrencies or traditional assets help investors evaluate XRP’s relative strength and potential for returns, informing optimal portfolio management. Event analysis around significant occurrences, such as partnerships or regulatory changes, assists in anticipating market reactions to future events. Furthermore, historical data aids in identifying market cycles, supporting investors in aligning their strategies with the prevailing market conditions. Recognizing key support and resistance levels based on historical prices enhances risk management by guiding entry and exit points. While historical data is a valuable tool, investors should blend it with current market analysis and fundamental factors for comprehensive decision-making, considering the inherent unpredictability of the cryptocurrency market.

Figure 4 below represents the evolution of the price of XRP in US dollar over the period Nov 2017 – Dec 2023. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 4. Evolution of the XRP price

Source: Yahoo! Finance

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the XRP.

Download R file

Data file

The R program that you can download above allows you to download the data for the Ethereum from the Yahoo! Finance website. The database starts on December, 2017.

Table 3 below represents the top of the data file for the Ethereum downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for XRP.

Source: computation by the author (data: Yahoo! Finance website)

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Download the Excel file with Ethereum data

Python script to download XRP historical data and save it to an Excel sheet::

import yfinance as yf

import pandas as pd

# Define the ticker symbol for Ethereum

xrp_ticker = “XRP-USD”

# Define the date range for historical data

start_date = “2020-01-01”

end_date = “2022-01-01”

# Download historical data using yfinance

xrp_data = yf.download(xrp_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data

xrp_df = pd.DataFrame(xrp_data)

# Define the Excel file path

excel_file_path = “xrp_historical_data.xlsx”

# Save the data to an Excel sheet

xrp_df.to_excel(excel_file_path, sheet_name=”XRP Historical Data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

Evolution of the Ethereum

Figure 5 below gives the evolution of the Ethereum on a daily basis.

Figure 5. Evolution of the XRP.

Source: computation by the author (data: Yahoo! Finance website).

Figure 6 below gives the evolution of the Ethereum returns from November 09, 2017 to December 31, 2022 on a daily basis.

Figure 6. Evolution of the XRP returns.

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Ethereum

The R program that you can download above also allows you to compute summary statistics about the returns of the Ethereum.

Table 4 below presents the following summary statistics estimated for the Ethereum:

  • The mean

  • The standard deviation (the squared root of the variance)

  • The skewness

  • The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 4. Summary statistics for XRP

Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Ethereum returns

Figure 7 represents the historical distribution of the Ethereum daily returns for the period from November 09, 2017 to December 31, 2022.

Figure 7. Historical XRP distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from November 09, 2017 to December 31, 2022.

Figure 8 below represents the Gaussian distribution of the XRP daily returns with parameters estimated over the period from November 09, 2017 to December 31, 2022.

Figure 9. Gaussian distribution of the XRP returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Ethereum returns

The R program that you can download above also allows you to compute risk measures about the returns of the Ethereum.

Table 5 below presents the following risk measures estimated for the Ethereum:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)

  • The short-term volatility (the standard deviation estimated over the last three months)

  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)

  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)

  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)

  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)

  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)

  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the XRP.

Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the XRP while the study of the right tail is relevant for an investor holding a short position in the XRP.

Why should I be interested in this post?

XRP, the cryptocurrency associated with Ripple, is a compelling subject for students, especially those in finance, economics, business, and technology. Ripple’s focus on revolutionizing cross-border transactions and its unique blockchain technology offer insights into innovations in financial technology. Exploring XRP provides a deeper understanding of blockchain, cryptocurrency markets, regulatory challenges, and the practical applications of decentralized systems. Students can gain valuable knowledge about market dynamics, investment opportunities, and the intersection of technology and finance by delving into the complexities of XRP and its impact on the financial industry.

Related posts on the SimTrade blog

About cryptocurrencies

   ▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

   ▶ Snehasish CHINARA How to get crypto data

   ▶ Alexandre VERLET Cryptocurrencies

   ▶ Youssef EL QAMCAOUIDecentralised Financing

   ▶ Hugo MEYERThe regulation of cryptocurrencies: what are we talking about?

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

   ▶ Jayati WALIA Returns

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for XRP

CoinMarketCap Historical data for XRP

About the author

The article was written in January 2024 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).

Ethereum – Unleashing Blockchain Innovation

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Ethereum – Unleashing Blockchain Innovation

Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains Bitcoin which is considered as the mother of all cryptocurrencies.

Historical context and background

Ethereum is a groundbreaking blockchain platform that emerged in the wake of Bitcoin’s success in 2015. While Bitcoin introduced and popularized the blockchain concept, Ethereum has leveraged this technology more effectively than any other digital currency. Promoters of new projects tend to rely on Ethereum’s tools rather than embark on the lengthy and expensive process of developing a new blockchain. Ethereum was conceived by a young Canadian programmer, Vitalik Buterin, who saw limitations in Bitcoin’s functionality and envisioned a decentralized platform capable of executing smart contracts. Buterin’s idea gained traction in the cryptocurrency community, and he, along with a team of developers, published the Ethereum whitepaper in late 2013. The platform’s official development began in 2014, with a crowdfunding campaign that raised over $18 million in Bitcoin, making it one of the most successful initial coin offerings (ICOs) of its time. Ethereum’s genesis block was mined on July 30, 2015, marking the official launch of the network.

Ethereum’s innovative concept of smart contracts and decentralized applications (DApps) quickly garnered attention within the blockchain and cryptocurrency space. The platform introduced a Turing-complete programming language, enabling developers to create a wide array of decentralized applications. Ethereum’s native cryptocurrency, Ether (ETH), serves as both a digital currency and a utility token within the ecosystem. Over the years, Ethereum has undergone several network upgrades to improve scalability and security, most notably the transition from a proof-of-work (PoW) to a proof-of-stake (PoS) consensus mechanism with the Ethereum 2.0 upgrade. This transition aims to address the network’s scalability issues and reduce its energy consumption, positioning Ethereum as a sustainable and versatile blockchain platform for the future. Today, Ethereum continues to play a pivotal role in the blockchain and decentralized finance (DeFi) space, powering a vast array of projects, including NFT platforms, decentralized exchanges, and decentralized applications that have reshaped the way we think about finance and technology.

Ethereum Logo
Ethereum Logo
Source: Yahoo! Finance .

Figure 1. Key Dates in Ethereum History
Key Dates in Ethereum History
Source: Yahoo! Finance .

Key Features of Ethereum

Smart Contracts

Ethereum is renowned for its pioneering smart contract functionality. Smart contracts are self-executing agreements with predefined rules and conditions, enabling automated and trustless transactions. This feature has broad applications in various industries, including finance, supply chain management, and legal services.

Decentralization

Ethereum operates on a decentralized network of nodes, making it resistant to censorship and single points of failure. This decentralization ensures the security and integrity of the blockchain, with no single entity having control over the network.

Ether (ETH)

Ethereum’s native cryptocurrency, Ether, serves as both a digital currency and a utility token. It’s used to pay for transaction fees, secure the network through staking in Ethereum 2.0, and as a medium of exchange within the ecosystem.

Interoperability

Ethereum is designed to interact with other blockchains and networks, fostering compatibility and collaboration across the blockchain ecosystem. Projects like Polkadot and Cosmos aim to enhance this interoperability.

EVM (Ethereum Virtual Machine)

The Ethereum Virtual Machine is a runtime environment for executing smart contracts. It’s a critical component that ensures the same execution of smart contracts across all Ethereum nodes, making Ethereum’s ecosystem reliable and consistent.

EIPs (Ethereum Improvement Proposals)

Ethereum has a robust governance model for protocol upgrades and improvements, with EIPs serving as the mechanism for proposing and implementing changes. This allows for community-driven innovation and adaptation.

Use Cases of Ethereum

Decentralized Finance (DeFi)

Ethereum is at the heart of the DeFi movement, offering lending, borrowing, trading, and yield farming services through DApps like Compound, Aave, and Uniswap. DeFi has disrupted traditional finance, providing open and inclusive access to financial services.

Non-Fungible Tokens (NFTs)

Ethereum’s ERC-721 and ERC-1155 token standards have fueled the NFT boom. NFTs enable the ownership and trade of unique digital assets, from art and music to virtual real estate and collectibles, all recorded on the blockchain.

Supply Chain Management

Ethereum’s transparent and tamper-proof ledger is used to track and verify the authenticity and provenance of products. This enhances supply chain efficiency and trust, reducing fraud and counterfeiting.

Gaming and Virtual Worlds

Ethereum is the platform of choice for blockchain-based gaming and virtual reality experiences. DApps like Decentraland and Axie Infinity allow users to trade in-game assets and participate in virtual economies.

Tokenization of Assets

Real-world assets, such as real estate, stocks, and commodities, can be tokenized on the Ethereum blockchain, making them more accessible for investment and trading.

Identity Verification

Ethereum can be used to secure and manage digital identities, enhancing privacy and reducing the risk of identity theft.

Social Impact

Ethereum is leveraged for social impact projects, including humanitarian aid distribution, voting systems, and tracking philanthropic donations, ensuring transparency and accountability.

Content Distribution

Ethereum-based projects are exploring decentralized content platforms, enabling creators to have more control over their intellectual property and revenue.

Ethereum’s versatility and ongoing development make it a crucial platform for a wide range of applications, from financial innovation to social change and beyond, driving the evolution of the blockchain and cryptocurrency space.

Technology and underlying blockchain

Ethereum’s underlying technology is rooted in blockchain, a distributed ledger system known for its security, transparency, and decentralization. Ethereum, like Bitcoin, employs a blockchain to record and verify transactions, but it offers a distinct set of features and capabilities that set it apart. At the core of Ethereum’s technology is the Ethereum Virtual Machine (EVM), a decentralized computing environment that executes smart contracts. Smart contracts are self-executing agreements with predefined rules and conditions that automate processes without the need for intermediaries.

Ethereum uses a consensus mechanism known as Proof of Stake (PoS), which is a significant departure from Bitcoin’s Proof of Work (PoW). PoS allows network participants, known as validators, to create new blocks and secure the network by locking up a certain amount of Ether as collateral. This approach is more energy-efficient and scalable compared to PoW, addressing some of the limitations that Bitcoin faces. Ethereum’s blockchain is a public and permissionless network, meaning that anyone can participate, transact, and develop decentralized applications (DApps) on the platform without needing approval.

The Ethereum ecosystem also employs a variety of token standards, with ERC-20 and ERC-721 being the most well-known. ERC-20 tokens are fungible and often used for cryptocurrencies, while ERC-721 tokens are non-fungible and have powered the explosion of NFTs (Non-Fungible Tokens). These standards have facilitated the creation and interoperability of a vast array of digital assets and DApps on the platform. Ethereum’s robust governance model, through Ethereum Improvement Proposals (EIPs), allows the community to suggest and implement changes, ensuring that the platform remains adaptable and responsive to evolving needs and challenges. Ethereum’s groundbreaking technology and active development community have positioned it as a leader in the blockchain space, with far-reaching implications for industries beyond just cryptocurrencies.

Supply of coins

Ethereum initially used a proof-of-work (PoW) consensus algorithm for coin mining, similar to Bitcoin. The process involved miners solving complex mathematical puzzles to validate transactions and add new blocks to the blockchain. Miners competed to solve these puzzles, and the first one to succeed was rewarded with newly minted Ethereum coins (ETH). This process was resource-intensive and required significant computational power.

However, Ethereum has been undergoing a transition to a proof-of-stake (PoS) consensus mechanism as part of its Ethereum 2.0 upgrade. The PoS model doesn’t rely on miners solving computational puzzles but instead relies on validators who lock up a certain amount of cryptocurrency as collateral to propose and validate new blocks. Validators are chosen to create new blocks based on the amount of cryptocurrency they hold and are willing to “stake” as collateral.

This transition to PoS is occurring in multiple phases. The Beacon Chain, which is the PoS blockchain that runs parallel to the existing PoW chain, was launched in December 2020. The full transition to Ethereum 2.0, including the complete shift to PoS, is expected to occur in multiple subsequent phases.

As of Q1 2023, there are approximately 121,826,163.06 Ethereum (ETH) coins in circulation, a key distinction from Bitcoin, which has a capped supply of 21 million. Ethereum, created by Vitalik Buterin, was designed without a specific supply limit, allowing for an unlimited number of coins if mining continues. Despite this, there is a cap of 18 million ETH coins that can be mined annually, equating to around 2 ETH per block. Ethereum Classic (ETC), a separate blockchain resulting from a community dispute, also exists with 135.3 billion coins. The Ethereum blockchain’s size was 175 GB in 2021, considerably smaller than Bitcoin’s 412 GB. Approximately 5750 Ethereum blocks are mined daily, with mining difficulty increasing and around 2,151 active nodes globally, primarily in the USA. Ethereum’s potential to become deflationary is acknowledged, contingent on mining costs exceeding rewards, as stated in a GitHub disclaimer.

Figure 2. Number of Ethereum Transaction per Day
Number of bitcoins in circulation
Source: BitInfoCharts (Ethereum Transactions historical chart).

Historical data for Ethereum

How to get the data?

The Ethereum is the most popular cryptocurrency on the market, and historical data for the Ethereum such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for Ethereum on Yahoo! Finance (the Yahoo! code for Ethereum is ETH-USD).

Figure 4. Ethereum data
Ethereum data
Source: Yahoo! Finance.

Historical data for the Ethereum market prices

Historical data on the price of Ethereum holds paramount significance in understanding the cryptocurrency’s market trends, investor behavior, and overall performance over time. Analyzing historical price data allows investors, analysts, and researchers to identify patterns, cycles, and potential indicators that may influence future price movements. It provides valuable insights into market sentiment, periods of volatility, and the impact of significant events or developments within the Ethereum ecosystem. Traders use historical data to formulate strategies, assess risk, and make informed decisions. Furthermore, the data aids in evaluating the success of protocol upgrades, regulatory changes, and shifts in broader economic conditions, offering a comprehensive view of Ethereum’s evolution. The historical price data of Ethereum serves as a crucial tool for market participants seeking to navigate the dynamic and sometimes unpredictable nature of the cryptocurrency market.

With the number of coins in circulation, the information on the price of coins for a given currency is also important to compute Ethereum’s market capitalization.

Figure 5 below represents the evolution of the price of Ethereum in US dollar over the period Nov 2017 – Dec 2023. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 5. Evolution of the Ethereum price

Source: Yahoo! Finance.

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Ethereum.

Download R file

Data file

The R program that you can download above allows you to download the data for the Ethereum from the Yahoo! Finance website. The database starts on December, 2017.

Table 3 below represents the top of the data file for the Ethereum downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the Ethereum.
Top of the file for the Ethereum data
Source: computation by the author (data: Yahoo! Finance website).

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Download the Excel file with Ethereum data

Python script to download Ethereum historical data and save it to an Excel sheet::

import yfinance as yf
import pandas as pd

# Define the ticker symbol for Ethereum
eth_ticker = “ETH-USD”

# Define the date range for historical data
start_date = “2020-01-01”
end_date = “2022-01-01”

# Download historical data using yfinance
eth_data = yf.download(eth_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data
eth_df = pd.DataFrame(eth_data)

# Define the Excel file path
excel_file_path = “ethereum_historical_data.xlsx”

# Save the data to an Excel sheet
eth_df.to_excel(excel_file_path, sheet_name=”ETH Historical Data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

Evolution of the Ethereum

Figure 6 below gives the evolution of the Ethereum on a daily basis.

Source: computation by the author (data: Yahoo! Finance website).

Figure 6. Evolution of the Ethereum.

Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the Ethereum returns from November 09, 2017 to December 31, 2022 on a daily basis.

Figure 7. Evolution of the Ethereum returns.

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Ethereum

The R program that you can download above also allows you to compute summary statistics about the returns of the Ethereum.

Table 4 below presents the following summary statistics estimated for the Ethereum:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 4. Summary statistics for the Ethereum.
Summary statistics for the Ethereum
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Ethereum returns

Historical distribution

Figure 8 represents the historical distribution of the Ethereum daily returns for the period from November 09, 2017 to December 31, 2022.

Figure 8. Historical Ethereum distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from November 09, 2017 to December 31, 2022. The annualized mean of daily returns is equal to 30.81% and the annualized standard deviation of daily returns is equal to 62.33%.

Figure 9 below represents the Gaussian distribution of the Ethereum daily returns with parameters estimated over the period from November 09, 2017 to December 31, 2022.

Figure 9. Gaussian distribution of the Ethereum returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Ethereum returns

The R program that you can download above also allows you to compute risk measures about the returns of the Ethereum.

Table 5 below presents the following risk measures estimated for the Ethereum:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the Ethereum.
Risk measures for the Ethereum
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Ethereum while the study of the right tail is relevant for an investor holding a short position in the Ethereum.

Why should I be interested in this post?

Ethereum, the pioneering blockchain platform, is an essential topic for management students due to its potential to transform industries, create innovative business opportunities, and disrupt traditional financial systems. Understanding Ethereum’s smart contracts, DeFi ecosystem, NFT market, and global impact can provide students with a competitive edge in a rapidly evolving business landscape, enabling them to navigate emerging trends, make informed investment decisions, and explore entrepreneurship in the digital economy.

Related posts on the SimTrade blog

About cryptocurrencies

▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

▶ Snehasish CHINARA How to get crypto data

▶ Alexandre VERLET Cryptocurrencies

▶ Youssef EL QAMCAOUI Decentralised Financing

▶ Hugo MEYER The regulation of cryptocurrencies: what are we talking about?

About statistics

▶ Shengyu ZHENG Moments de la distribution

▶ Shengyu ZHENG Mesures de risques

▶ Jayati WALIA Returns

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for Ethereum

CoinMarketCap Historical data for Ethereum

About the author

The article was written in December 2023 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).

Bitcoin: the mother of all cryptocurrencies

by

Bitcoin: the mother of all cryptocurrencies

Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains Bitcoin which is considered as the mother of all cryptocurrencies.

Historical context and background

The genesis of Bitcoin can be traced back to the aftermath of the Financial Crisis of 2008, when a growing desire emerged for a currency immune to central authority control. Traditional banks had faltered, leading to the devaluation of money through government-sanctioned printing. The absence of a definitive limit on money creation fostered uncertainty. Bitcoin ingeniously addressed this quandary by establishing a fixed supply of coins and a controlled production rate through transparent coding. This code’s openness ensured that no entity, including governments, could manipulate the currency’s value. Consequently, Bitcoin’s worth became solely determined by market dynamics, evading the arbitrary alterations typical of government-managed currencies.

Furthermore, Bitcoin revolutionized financial transactions by eliminating reliance on third-party intermediaries, exemplified by banks. Users can now engage in direct peer-to-peer transactions, circumventing the potential for intermediaries to engage in risky financial ventures akin to the 2008 Financial Crisis. The process of safeguarding one’s Bitcoins is equally innovative, as users manage their funds through a Bitcoin Wallet. Unlike traditional banks, these wallets operate as personal assets, with users as their own bankers. While various companies offer wallet services, the underlying code remains accessible for review, ensuring customers’ trust and the safety of their deposits.

Bitcoin Logo
Bitcoin Logo
Source: internet.

Figure 1. Key Dates in Bitcoin History
Key Dates in Bitcoin History
Source: author of this post.

Key features and use cases

Examples of areas where Bitcoin is currently being used:

  • Digital Currency: Bitcoin serves as a digital currency for everyday transactions, allowing users to buy goods and services online and in physical stores.
  • Crypto Banking: Bitcoin is used in decentralized finance (DeFi) applications, where users can lend, borrow, and earn interest on their Bitcoin holdings.
  • Asset Tokenization: Bitcoin is used to tokenize real-world assets like real estate and art, making them more accessible and divisible among investors.
  • Onchain Governance: Some blockchain projects utilize Bitcoin for on-chain governance, enabling token holders to vote on protocol upgrades and changes.
  • Smart Contracts: While Ethereum is more widely associated with smart contracts, Bitcoin’s second layer solutions like RSK (Rootstock) allow for the execution of smart contracts on the Bitcoin blockchain.
  • Corporate Treasuries: Large corporations, such as Tesla, have invested in Bitcoin as a store of value and an asset to diversify their corporate treasuries.
  • State Treasuries: Some countries, like El Salvador, have adopted Bitcoin as legal tender and added it to their national treasuries to facilitate cross-border remittances and financial inclusion.
  • Store of Value During Times of Conflict: In regions with economic instability or conflict, Bitcoin is used as a hedge against currency devaluation and asset confiscation.
  • Online Gambling: Bitcoin is widely accepted in online gambling platforms, providing users with a secure and pseudonymous way to wager on games and sports.
  • Salary Payments for Freelancers in Emerging Markets: Freelancers in countries with limited access to traditional banking use Bitcoin to receive payments from international clients, circumventing costly and slow remittance services.
  • Cross-Border Transactions with Bitcoin Gold: Cross-border transactions can often be complex, time-consuming, and costly due to the involvement of multiple intermediaries and the varying regulations of different countries. However, Bitcoin Gold offers a streamlined solution for facilitating global payments, making cross-border transactions more efficient and accessible.

These examples highlight the diverse utility of Bitcoin, ranging from everyday transactions to more complex financial applications and as a tool for economic empowerment in various contexts.

Technology and underlying blockchain

Blockchain technology is the foundational innovation that underpins Bitcoin, the world’s first and most well-known cryptocurrency. At its core, blockchain is a decentralized and distributed ledger system that records transactions across a network of computers in a secure and transparent manner. In the context of Bitcoin, this blockchain serves as a public ledger that tracks every transaction ever made with the cryptocurrency. What sets blockchain apart is its ability to ensure trust and security without the need for a central authority, such as a bank or government. Each block in the chain contains a set of transactions, and these blocks are linked together in a chronological and immutable fashion. This means that once a transaction is recorded on the blockchain, it cannot be altered or deleted. This transparency, immutability, and decentralization make blockchain technology a revolutionary tool not only for digital currencies like Bitcoin but also for a wide range of applications in various industries, from finance and supply chain management to healthcare and beyond.

Moreover, Bitcoin operates on a decentralized network of computers (nodes) worldwide. These nodes validate and confirm transactions, ensuring that the network remains secure, censorship-resistant, and immune to central control. The absence of a central authority is a fundamental characteristic of Bitcoin and a key differentiator from traditional financial systems. Bitcoin relies on a PoW consensus mechanism for securing its network. Miners compete to solve complex mathematical puzzles, and the first one to solve it gets the right to add a new block of transactions to the blockchain. This process ensures the security of the network, prevents double-spending, and maintains the integrity of the ledger. Bitcoin has a fixed supply of 21 million coins, a feature hard-coded into its protocol. The rate at which new Bitcoins are created is reduced by half approximately every four years through a process known as a “halving.” This limited supply is in stark contrast to fiat currencies, which can be printed without restriction.

These technological aspects collectively make Bitcoin a groundbreaking innovation that has disrupted traditional finance and is increasingly studied and integrated into the field of finance. It offers unique opportunities and challenges for finance students to explore, including its impact on monetary policy, investment, and the broader financial ecosystem.

Supply of coins

Looking at the supply side of bitcoins, the number of bitcoins in circulation is given by the following mathematical formula:

Formula for the number of bitcoins in circulation

This calculation hinges upon the fundamental concept of the Bitcoin supply schedule, which employs a diminishing issuance rate through a process known as “halving”.

Figure 2 represents the evolution of the number of bitcoins in circulation overt time based on the above formula.

Figure 2. Number of bitcoins in circulation
Number of bitcoins in circulation
Source: computation by the author.

You can download below the Excel file for the data and the figure of the number of bitcoins in circulation.

Download the Excel file with Bitcoin data

Historical data for Bitcoin

How to get the data?

The Bitcoin is the most popular cryptocurrency on the market, and historical data for the Bitcoin such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for Bitcoin on Yahoo! Finance (the Yahoo! code for Bitcoin is BTC-USD).

Figure 4. Bitcoin data
Bitcoin data
Source: Yahoo! Finance.

Historical data for the Bitcoin market prices

The market price of Bitcoin is a dynamic and intricate element that reflects a multitude of factors, both intrinsic and extrinsic. The gradual rise in market value over time indicates a willingness among investors and traders to offer higher prices for the cryptocurrency. This signifies a rising interest and strong belief in the project’s potential for the future. The market price reflects the collective sentiment of investors and traders. Comparing the market price of Bitcoin to other similar cryptocurrencies or benchmark assets can provide insights into its relative strength and performance within the market.

The value of Bitcoin in the market is influenced by a variety of elements, with each factor contributing uniquely to their pricing. One of the most significant influences is market sentiment and investor psychology. These factors can cause prices to shift based on positive news, regulatory changes, or reactive selling due to fear. Furthermore, the real-world implementations and usages of Bitcoin are crucial for its prosperity. Concrete use cases such as Decentralized Finance (DeFi), Non-Fungible Tokens (NFTs), and international transactions play a vital role in creating demand and propelling price appreciation. Meanwhile, adherence to basic economic principles is evident in the supply-demand dynamics, where scarcity due to limited issuance, halving events, and token burns interact with the balance between supply and demand.

With the number of coins in circulation, the information on the price of coins for a given currency is also important to compute Bitcoin’s market capitalization.

Figure 5 below represents the evolution of the price of Bitcoin in US dollar over the period October 2014 – August 2023. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 5. Evolution of the Bitcoin price
Evolution of the Bitcoin price
Source: computation by the author (data source: Yahoo! Finance).

Python code

Python script to download Bitcoin historical data and save it to an Excel sheet::

import yfinance as yf
import pandas as pd

# Define the ticker symbol and date range
ticker_symbol = “BTC-USD”
start_date = “2020-01-01”
end_date = “2023-01-01”

# Download historical data using yfinance
data = yf.download(ticker_symbol, start=start_date, end=end_date)

# Create a Pandas DataFrame
df = pd.DataFrame(data)

# Create a Pandas Excel writer object
excel_writer = pd.ExcelWriter(‘bitcoin_historical_data.xlsx’, engine=’openpyxl’)

# Write the DataFrame to an Excel sheet
df.to_excel(excel_writer, sheet_name=’Bitcoin Historical Data’)

# Save the Excel file
excel_writer.save()

print(“Data has been saved to bitcoin_historical_data.xlsx”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

The code above allows you to download the data from Yahoo! Finance.

Download the Excel file with Bitcoin data

R code

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Bitcoin.

Download R file

Data file

The R program that you can download above allows you to download the data for the Bitcoin from the Yahoo! Finance website. The database starts on September 17, 2014.

Table 3 below represents the top of the data file for the Bitcoin downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the Bitcoin.
Top of the file for the Bitcoin data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the Bitcoin

Figure 6 below gives the evolution of the Bitcoin from September 17, 2014 to December 31, 2022 on a daily basis.

Figure 6. Evolution of the Bitcoin.
Evolution of the Bitcoin
Source: computation by the author (data: Yahoo! Finance website).

Figure 7 below gives the evolution of the Bitcoin returns from September 17, 2014 to December 31, 2022 on a daily basis.

Figure 7. Evolution of the Bitcoin returns.
Evolution of the Bitcoin return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Bitcoin

The R program that you can download above also allows you to compute summary statistics about the returns of the Bitcoin.

Table 4 below presents the following summary statistics estimated for the Bitcoin:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 4. Summary statistics for the Bitcoin.
Summary statistics for the Bitcoin
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Bitcoin returns

Historical distribution

Figure 8 represents the historical distribution of the Bitcoin daily returns for the period from September 17, 2014 to December 31, 2022.

Figure 8. Historical distribution of the Bitcoin returns.
Historical distribution of the daily Bitcoin returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from September 17, 2014 to December 31, 2022. The annualized mean of daily returns is equal to 30.81% and the annualized standard deviation of daily returns is equal to 62.33%.

Figure 9 below represents the Gaussian distribution of the Bitcoin daily returns with parameters estimated over the period from September 17, 2014 to December 31, 2022.

Figure 9. Gaussian distribution of the Bitcoin returns.
Gaussian distribution of the daily Bitcoin returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Bitcoin returns

The R program that you can download above also allows you to compute risk measures about the returns of the Bitcoin.

Table 5 below presents the following risk measures estimated for the Bitcoin:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the Bitcoin.
Risk measures for the Bitcoin
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Bitcoin while the study of the right tail is relevant for an investor holding a short position in the Bitcoin.

Why should I be interested in this post?

Students would be keenly interested in this article discussing Bitcoin’s history and trends due to its profound influence on the financial landscape. Bitcoin, as a novel and dynamic asset class, presents a unique opportunity for students to explore the evolving world of finance. By delving into Bitcoin’s past, understanding its market trends, and assessing its impact on global economies, students can equip themselves with the knowledge and skills needed to navigate a financial landscape that is increasingly intertwined with cryptocurrencies and blockchain technology. Moreover, this knowledge can enhance their career prospects in an industry undergoing significant transformation and innovation.

Related posts on the SimTrade blog

About cryptocurrencies

   ▶ Snehasish CHINARA How to get crypto data

   ▶ Alexandre VERLET Cryptocurrencies

   ▶ Youssef EL QAMCAOUI Decentralised Financing

   ▶ Hugo MEYER The regulation of cryptocurrencies: what are we talking about?

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

   ▶ Jayati WALIA Returns

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for Bitcoin

CoinMarketCap Historical data for Bitcoin

About the author

The article was written in September 2023 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).

How to get crypto data

by

How to get crypto data

Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains how to get crypto data.

Types of data

Number of coins

The information on the number of coins in circulation for a given currency is important to compute its market capitalization. Market capitalization is calculated by multiplying the current price of the cryptocurrency by its circulating number of coins (supply). This metric gives a rough estimate of the cryptocurrency’s total value within the market and its relative size compared to other cryptocurrencies. A lower circulating supply often implies a greater level of scarcity and rarity.

For cryptocurrencies (unlike fiat money), the number of coins in circulation is given by a mathematical formula. The number of coins may be limited (like the Bitcoin) or unlimited (like Ethereum and Dogecoin) over time.

Cryptocurrencies with limited supplies, such as Bitcoin’s maximum supply of 21 million coins, can be perceived as more valuable due to their finite nature. Scarcity can contribute to investor interest and potential price appreciation over time. A lower circulating supply might indicate the potential for future adoption and value appreciation, as the limited supply can create scarcity-driven demand, especially if the cryptocurrency gains more utility and usage.

Bitcoin’s blockchain also relies on a key equation to steadily allow new BTC to be introduced. The equation below gives the total supply of bitcoins:

Total supply of bitcoins

Figure 1 below represents the evolution of the supply of Bitcoins.

Figure 1. Evolution of the supply of Bitcoins

Source: computation by the author.

Market price of a coin

The market price of a cryptocurrency in the market holds crucial insights into how well the cryptocurrency is faring. Although not the sole factor, the market price significantly contributes to evaluating the cryptocurrency’s performance and its prospects. The market price of a cryptocurrency is a dynamic and intricate element that reflects a multitude of factors, both intrinsic and extrinsic. The gradual rise in market value over time indicates a willingness among investors and traders to offer higher prices for the cryptocurrency. This signifies a rising interest and strong belief in the project’s potential for the future. The market price reflects the collective sentiment of investors and traders. Comparing the market price of a cryptocurrency to other similar cryptocurrencies or benchmark assets like Bitcoin can provide insights into its relative strength and performance within the market. A rising market price can indicate increasing adoption of the cryptocurrency for various use cases. Successful projects tend to attract more users and real-world applications, which can drive up the price.

The value of cryptocurrencies in the market is influenced by a variety of elements, with each factor contributing uniquely to their pricing. One of the most significant influences is market sentiment and investor psychology. These factors can cause prices to shift based on positive news, regulatory changes, or reactive selling due to fear. Furthermore, the real-world implementation and usage of a cryptocurrency are crucial for its prosperity. Concrete use cases such as Decentralized Finance (DeFi), Non-Fungible Tokens (NFTs), and international transactions play a vital role in creating demand and propelling price appreciation. Meanwhile, adherence to basic economic principles is evident in the supply-demand dynamics, where scarcity due to limited issuance, halving events, and token burns interact with the balance between supply and demand.

With the number of coins in circulation, the information on the price of coins for a given currency is also important to compute its market capitalization.

Figure 2 below represents the evolution of the price of Bitcoin in US dollar over the period October 2014 – August 2023. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 2. Evolution of the Bitcoin price
Evolution of the Bitcoin price
Source: computation by the author (data source: Yahoo! Finance).

Trading volume

Trading volume is crucial when assessing the health, reliability, and potential price movements of a cryptocurrency. Trading volume refers to the total amount of a cryptocurrency that is bought and sold within a specific time frame, typically measured in units of the cryptocurrency (e.g., BTC) or in terms of its equivalent value in another currency (e.g., USD).

Trading volume directly mirrors market liquidity, with higher volumes indicative of more liquid markets. This liquidity safeguards against drastic price fluctuations when trading, contrasting with low-volume scenarios that can breed volatility, where even a single substantial trade may disproportionately shift prices. Price alterations are most reliable and meaningful when accompanied by substantial trading volume. Price movements upheld by heightened volume often hold greater validity, potentially pointing to more pronounced market sentiment. When price surges parallel rising trading volume, it suggests a sustainable upward trajectory. Conversely, low trading volume amid rising prices may hint at a forthcoming correction or reversal. Scrutinizing the correlation between price oscillations and trading volume can uncover potential divergences. For instance, ascending prices coupled with dwindling trading volume may suggest a weakening trend.

Figure 3 below represents the evolution of the monthly trading volume of Bitcoin over the period October 2014 – July 2023.

Figure 3. Evolution of the trading volume of Bitcoin
Evolution of the trading volume of Bitcoin
Source: computation by the author (data source: Yahoo! Finance).

Bitcoin data

You can download the Excel file with Bitcoin data used in this post as an illsutration.

Download the Excel file with Bitcoin data

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Python script to download Bitcoin historical data and save it to an Excel sheet:

import yfinance as yf
import pandas as pd

# Define the ticker symbol and date range
ticker_symbol = “BTC-USD”
start_date = “2020-01-01”
end_date = “2023-01-01”

# Download historical data using yfinance
data = yf.download(ticker_symbol, start=start_date, end=end_date)

# Create a Pandas DataFrame
df = pd.DataFrame(data)

# Create a Pandas Excel writer object
excel_writer = pd.ExcelWriter(‘bitcoin_historical_data.xlsx’, engine=’openpyxl’)

# Write the DataFrame to an Excel sheet
df.to_excel(excel_writer, sheet_name=’Bitcoin Historical Data’)

# Save the Excel file
excel_writer.save()

print(“Data has been saved to bitcoin_historical_data.xlsx”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

APIs

Calculating the total number of Bitcoins in circulation over time
Access – Bitcoin Blockchain data
By running a Bitcoin node or by using blockchain data providers like Blockchain.info, Blockchair, or a similar service.

Extract Block Data: Once you have access to the blockchain data, you would need to extract information from each block. Each block contains a record of the transactions that have occurred, including the creation (mining) of new Bitcoins in the form of a “Coinbase” transaction.

Calculate Cumulative Supply: You can calculate the cumulative supply of Bitcoins by adding up the rewards from each block’s Coinbase transaction. Initially, the block reward was 50 Bitcoins, but it halves approximately every four years due to the Bitcoin halving events. So, you’ll need to account for these halving in your calculations.

Code – python

import requests

# Replace ‘YOUR_API_KEY’ with your CoinMarketCap API key
api_key = ‘YOUR_API_KEY’

# Define the endpoint URL for CoinMarketCap’s API
url = ‘https://pro-api.coinmarketcap.com/v1/cryptocurrency/quotes/latest’

# Define the parameters for the request
params = {
‘symbol’: ‘BTC’,
‘convert’: ‘USD’,
‘CMC_PRO_API_KEY’: api_key
}

# Send the request to CoinMarketCap
response = requests.get(url, params=params)

# Parse the response JSON
data = response.json()

# Extract the circulating supply from the response
circulating_supply = data[‘data’][‘BTC’][‘circulating_supply’]

print(f”Current circulating supply of Bitcoin: {circulating_supply} BTC”)

## Replace ‘YOUR_API_KEY’ with your actual CoinMarketCap API key.

Why should I be interested in this post?

Cryptocurrency data is becoming increasingly relevant in these fields, offering opportunities for research, data analysis skill development, and even career prospects. Whether you’re aiming to conduct research, stay informed about the evolving financial landscape, or simply enhance your data analysis abilities, understanding how to access and work with crypto data is an asset. Plus, as the cryptocurrency industry continues to grow, this knowledge can open new career paths and improve your personal finance decision-making. In a rapidly changing world, diversifying your knowledge with cryptocurrency data acquisition skills can be a wise investment in your future.

Related posts on the SimTrade blog

▶ Alexandre VERLET Cryptocurrencies

▶ Youssef EL QAMCAOUI Decentralised Financing

▶ Hugo MEYER The regulation of cryptocurrencies: what are we talking about?

Useful resources

APIs

CoinMarketCap Source of API keys and program

CoinGecko Source of API keys and Programs

CryptoNews Source of API keys and Programs

Data sources

Yahoo! Finance Historical data for Bitcoin

Coinmarketcap Historical data for Bitcoin

Blockchain.com Market Data and charts on Bitcoin history

About the author

The article was written in October 2023 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, (2022-2024).

My Experience as an External Junior Consultant with Eurogroup Consulting

by

My Experience as an External Junior Consultant with Eurogroup Consulting

Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) shares his experience as an External Junior Consultant with Eurogroup Consulting, which is a consulting company specialized in organization and operations (supply chain).

About Eurogroup Consulting

Eurogroup Consulting, founded in 1982, is a French consulting firm with a European approach to management, strategy and organization. With a focus on freedom to take risks, requirements of the clients and the projects, and solidarity to the success of their entrepreneurial partners, Eurogroup consulting has been able to expand its network to 16 countries and clientele to all sectors of activity. They have grown significantly in the areas of banking and finance, business, insurance and welfare, logistics and transportation, retail, energy and the environment, and public sector, including healthcare. Today, Eurogroup Consulting stands out as a highly reputable and able partner for companies seeking all-encompassing solutions and knowledgeable advisory in the areas of Digital, Operational Excellence, and Transitions.

Eurogroup Consulting Logo
Eurogroup Consulting Logo
Source: Eurogroup Consulting.

Junior Consultant Experience

As a part of my Master in Management program at ESSEC Business School, I and a few other students a ESSEC (my team) collaborated as an External Junior Consultant with Eurogroup Consulting for a consulting project in the aviation sector based in Singapore. With my team, I closely worked with the managing partner of Eurogroup Consulting in Singapore to offer strategic recommendations to one of the firm’s clients in the aviation sector dealing with logistics (for the maintenance, repair and overhaul (MRO) of airplanes). Our focus was on addressing the real-world challenges faced by the aviation industry in the post-Covid era in the Asia-Pacific region.

My project with Eurogroup Consulting dealt with logistics and supply chain within the aviation sector. Efficient logistics and supply chain management are vital for businesses to remain competitive in today’s globalized marketplace as they ensure the efficient flow of goods, services and information from the point of origin to the point of consumption.

Our focus was on Contract Logistics in the aviation sector, which is a type of third-party logistics (3PL) service where a company delegates certain aspects of its supply chain operations to a specialized provider. This provider, known as the contract logistics provider, oversees a portion or all the company’s supply chain, which includes transportation, distribution, and related activities, as per the contractual agreement. The primary objective of contract logistics is to enhance the efficiency of the customer’s supply chain, reduce expenses, and optimize overall performance. By leveraging expertise, resources, and technology, contract logistics providers enable clients to concentrate on core business activities while entrusting the management of their logistics operations to the specialized service. Contract logistics providers provide services such as warehouse management, inventory management, order fulfillment, distribution and transportation management. In the aviation sector, contract logistics play an important role in offering services like space part logistics. Airlines face challenges with “Inoperable parts” (INOPs), which necessitate costly replacements or risk grounding the aircraft indefinitely. Major companies provide essential services to address this spare parts availability issue, such as Order Tracking & Tracing, spare parts storage management, advanced stock organization, and repair logistics management.

My missions

The objective my project was to achieve the following:

  • Identify the post-Covid supply chain strategies of major multinational corporations (MNCs) in the aviation sector, including the evolution of their supply chain footprints and their expectations from contract logistics providers (an intermediary between the different manufacturers and an airline company).
  • Evaluate the current positioning and services offered by prominent contract logistics providers and anticipate how their positioning and offerings might evolve in the future.
  • Recommend new potential offerings and analyze their suitability and key factors for success.

Required skills and knowledge

As a part of a cross-functional team of ESSEC students to achieve the shared project objectives through efficient cooperation, and decision-making, I gained an understanding of the aerospace Third Party Logistic (3PL) and Maintenance, Repair and Overhaul (MRO) industry in the Asia-Pacific region as we conducted comprehensive market research. We gathered and analysed large sets of data related to the aviation contract-logistics market, customers, competitors, and industry trends to identify growth opportunities. Following the analysis, we had weekly meetings with the managing partner of Eurogroup consulting, a professor-mentor of the team at ESSEC and the client to discuss our approach to the problem statement, challenges faced by the team to gather access to information, since aviation industry is well-known for its confidentiality norms, and the assessments produced after detailed analysis of the data. Attending the weekly team-mentor meetings was vital to our learning, providing us with first-hand exposure to the real-life operations within a consulting firm. In these meeting we decided upon the objective targets for the coming weeks and how to address the challenges faced this week.

As a junior consultant, I engaged with subject matter experts in the region in order to gain a holistic understanding of the impact of Covid-19 on the aviation contract-logistics industry. I conducted detailed financial statement analysis to understand how the larger players and competition were leveraging their cash flows, and debt to counter the crisis caused on the industry by the pandemic. In order to measure the risk of the competitors of the client, we conducted a fundamental calculation of Altman’s Z-Score and developed a credit rating model based on key financial indicators, both quantitative and qualitative, in Excel. This allowed us to scrutinize the key players in the current market and identify competitors to be focused on. Based on our discussions with experts, and analysis conducted, we identified the gap in the service offerings which allowed us to provide strategic recommendations for the client company. This 3-month long learning-by-doing experience gave me immense exposure to the operations of a consulting firm and the way they respect the needs of the stakeholders of the project.

What I learned

Key Learning Outcomes of this project :

  • To utilise evidence-based conclusions and strategic thinking to propose new strategic initiatives that aligned with industry innovations and key success factors.
  • To analyse corporate information and financial statements, preparing pitch-books and presentations while collaborating with stakeholders.
  • To define the value chain of aviation contract-logistics industry in Asia-Pacific region and observe potential channels to expand.
  • To develop custom credit rating tool based on key performance indicators.

Concepts related my internship

Third-Party Logistics in Aviation Sector

Third-Party Logistics (3PL) is a crucial aspect of Logistics and Supply Chain Management, that has transformed how businesses handle the transportation and storage of products and services. Through strategic outsourcing, companies delegate specific logistics tasks to external service providers, known as 3PL providers. These service providers streamline supply chain processes, resulting in increased efficiency, cost reduction, and improved overall performance. Within the aviation sector, 3PL is crucial for aiding airlines, aircraft manufacturers, and associated enterprises with intricate global logistics. Due to the complexity and time-sensitivity of aviation operations, 3PL providers offer customized solutions to address the unique demands and challenges of the industry. 3PL companies in the aviation industry offer a range of essential services to streamline operations. These include arranging the transportation of aviation-related cargo and goods, managing efficient warehousing and inventory systems for quick access to items, handling customs clearance for international shipments, ensuring prompt last-mile delivery to designated destinations, managing the distribution of critical spare parts for airlines’ maintenance facilities worldwide, and facilitating smooth transportation of large components and sub-assemblies for aircraft manufacturers. These services contribute significantly to the industry’s efficiency and help reduce aircraft downtime, making them indispensable partners for aviation businesses.

Aviation 3PL Services:

  • Freight Transportation: 3PL companies arrange timely transport of aviation cargo to airports, maintenance facilities, and aircraft assembly lines.
  • Efficient Warehousing: These providers manage aviation-related inventory in well-organized warehouses, reducing lead times.
  • Customs Compliance: 3PLs handle international shipments’ customs documentation, ensuring smooth clearance.
  • Last-Mile Delivery: They ensure prompt delivery of aviation components to their destinations.
  • Spare Parts Distribution: Airlines rely on 3PLs for critical spare parts distribution, minimizing aircraft downtime.
  • Aircraft Manufacturing Support: Specialized 3PLs facilitate smooth production by transporting large components for aircraft manufacturers.

Aviation companies benefit from the expertise of 3PL providers in handling complex logistics. Outsourcing these services saves on capital investments and allows them greater flexibility in scaling services based on demand. 3PL providers’ extensive network aids in smoother international operations for the customers.

Credit risk

The evaluation of credit risk holds significant importance in financial risk management, especially concerning lending and investment activities. It pertains to the potential financial loss that a lender or investor might encounter in the event of non-payment or failure of a borrower or counterparty to fulfil their financial commitments. Credit risk occurs when people, companies, or governmental entities take loans or offer credit with the possibility that they might be unable to repay the borrowed amount according to the agreed terms.

Several key concepts allow us to gauge the risk involved with an investment and make better decisions. The Probability of Default (PD) is a measure that evaluates the probability of a borrower being unable to fulfil their contractual obligations and defaulting. Although defaulting doesn’t always result in immediate losses, it can raise the risk of bankruptcy and eventual losses. PD is expressed as a percentage, with higher percentages indicating a higher risk of default. Loss Given Default (LGD) is a commonly used expression to describe the ‘loss severity’ of an investment. It calculates the proportion of an exposure (such as a bond or loan equivalent) that is expected to remain unrecovered if a default occurs. It is a percentage of the outstanding debt or investment that is not recoverable after a default occurs.

Credit agencies are responsible for assigning credit ratings to both corporations and governments based on their ability to fulfil financial obligations. These credit ratings serve as indicators for lenders regarding the entity’s capacity to repay loans. Each credit agency employs slightly varied approaches in determining credit ratings. On the other hand, credit scores pertain to individuals and reflect their creditworthiness, considering their credit history and financial conduct. Credit risk models play a vital role in the financial industry as they employ mathematical techniques to foresee the probability of default, evaluate potential losses, and handle credit risk. These sophisticated tools aid both financial institutions and investors in making well-informed choices concerning lending and investment matters. As the global economy continues to evolve, understanding and managing credit risk will remain paramount for safeguarding financial stability and ensuring sustainable growth in lending and investment sectors. By employing comprehensive credit risk analysis, stakeholders can navigate potential challenges, capitalize on opportunities, and foster a resilient financial landscape for the future.

The evaluation of credit risk had a vital role in the extensive market research conducted for the top players in the aviation contract logistics segment. Although credit risk analysis mainly concentrates on appraising the creditworthiness of potential collaborators or customers, it offered valuable insights that prove beneficial for competitive intelligence and market research objectives. Conducting credit risk analysis on companies within the industry allowed for the identification of major players and their market position. Assessing financial stability, including liquidity, profitability, and debt levels, helped evaluate potential investment opportunities and market disruptions. Additionally, studying competitors’ credit risk provided insights into their market share, customer base, and potential risks of default or bankruptcy. Understanding their financial strength aided in formulating effective strategies for competitive positioning in the aviation contract logistics niche.

Corporate Risk Management

In order to mitigate various types of financial risks, such as credit risk, market risk, liquidity risk, and operational risk, investors and management can use risk analysis to identify, measure, and mitigate these risks effectively. Instabilities and losses in financial markets generally caused by fluctuations in stock prices, currencies, interest rates and more lead to rise in financial risks. Market risk reflects the fluctuations of interest rates, currencies, and prices of raw materials. Probability of failing to pay creditors such as banks or lenders leads to credit risk. Liquidity risk is the inability of a company to meet its short-term financial obligations (to pay the salaries of its employees, to settle the invoices to its suppliers, to pay back the capital and interests to the bank, to pay the taxes to the State, etc.) and is generally signs of cashflow inefficiencies. Flawed policies, processes, events or systems disrupt business operations and are known to cause operational risks. Financial risks are measured by calculating specific ratios that indicate the overall health of a company, which are then compared against the industry benchmark.

The following table provides some of the important financial ratios used to estimate the risk of a company. High financial risk is implied by high or low measure according to the ratio.

Table 1. Financial ratios
Financial ratios
Source: The author.

Ratios are most useful when compared between companies in similar sectors and over time. Multiple measurements may be necessary for each given firm to fully comprehend the financial risk.

Why should I be interested in this post?

Working closely with subject matter experts and engaging in financial statement analysis to assess the impact of Covid-19 on the various industries equipped us with valuable skills and knowledge in financial analysis and risk assessment. Additionally, learning to calculate Altman’s Z-Score and developing a credit score model allowed us to evaluate the financial health of companies, a crucial skill in the finance industry. The exposure to strategic decision-making, data analysis, and client interactions during this consulting project helped me develop problem-solving capabilities and communication skills, which are highly sought-after attributes in the finance job market. Overall, this hands-on experience provided me with practical experience for finance roles, especially in consulting firms.

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Useful resources

Eurogroup Consulting

Financial Risk – Allianz Trade

Financial Risk – Deloitte

About the author

The article was written in August 2023 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).