This thesis is intended to contribute to three goals: analyse Coinbase, derive recommendations for the cryptocurrency exchange’s management, potential investors, and other cryptoeconomy participants, and create a better understanding of the crypto-industry and an enhanced acceptance of cryptocurrencies. For these purposes, Coinbase was used as a single case study and analysed qualitatively and quantitatively. A Five C’s analysis was applied in the qualitative part, complemented by SWOT and PESTLE analyses and Porter’s Five Forces. The quantitative analysis, in turn, consisted of eleven key ratios that were compared to Nasdaq’s and Intercontinental Exchange’s ratios.
Coinbase’s Nasdaq listing is a caesura for the cryptoeconomy since it is the first listing of a major cryptocurrency exchange in the USA. Coinbase’s opening share price exceeds the reference price by more than 50%, resulting in Coinbase’s valuation to top the aggregated value of the two well-established, traditional exchanges Intercontinental Exchange and Nasdaq. Given this listing’s significance and size under consideration of Coinbase’s relatively short existence and small revenue size, the question emerges whether the valuation is caused by Coinbase’s business model or the cryptocurrency hype.
Table of Content Page
Index of Figures
Index of Tables
Index of Appendices
Index of Abbreviations
1 Introduction
1.1 Relevance of the topic and purpose of the thesis
1.2 Structure and approach of the thesis
1.3 Terminology
1.3.1 Exchange
1.3.2 Cryptocurrencies, blockchain and cryptocurrency exchanges
2 Methodology
2.1 Research design and strategy
2.2 Research instruments
2.2.1 Qualitative instruments
2.2.2 Quantitative instruments
3 Analysis of Coinbase
3.1 Qualitative findings
3.1.1 Company
3.1.2 Customers
3.1.3 Competitors
3.1.4 Collaborators
3.1.5 Context
3.2 Quantitative findings
4 Discussion and recommendations
4.1 Answers to the research questions
4.2 Recommendations
5 Conclusion
Bibliography
Index of Figures
Figure 1: Revenue structure of stock exchanges (Compiled by the author based on OECD, 2016)
Figure 2: Operation of a decentralised fully on-chain exchange (Svec et al., 2020, p. 101)
Figure 3: Operation of a hybrid exchange (Svec et al., 2020, p. 102)
Figure 4: Types of secondary data (Saunders et al., 2009, p. 259)
Figure 5: Coinbase's balance sheet (Compiled by the author based on Coinbase, 2021a and Yahoo, 2021a)
Figure 6: Coinbase's income statement (Compiled by the author based on Coinbase, 2021a and Yahoo, 2021a)
Figure 7: Overview of the calculated ratios (Compiled by the author based on Coinbase, 2021a, Unlimited Consulting and Auditing Partnership, 2021, Macrotrends, 2021a, and Macrotrends, 2021c)
Index of Tables
Table 1: Key decision criteria for a selection of different research strategies (Compiled by the author based on Yin, 2013 and Saunders et al., 2009)
Table 2: Overview of key issue of the six categories of the PESTLE analysis (Compiled by the author based on Warner, 2010 and Perera, 2017)
Table 3: Coinbase's series funding rounds (Compiled by the author based on Craft, n.d., Crunchbase, n.d., and Levy, 2021)
Index of Appendices
Appendix I: Figure 2: Operation of a decentralised fully on-chain exchange (Svec et al., 2020, p. 101)
Appendix II: Figure 3: Operation of a hybrid exchange (Svec et al., 2020, p. 102)
Appendix III: Overview of the seven additional types of research strategies (Saunders et al., 2009; Yin, 2013).
Appendix IV: Table 1: Key decision criteria for a selection of different research strategies (Compiled by the Author based on Yin, 2013 and Saunders et al., 2009)
Appendix V: Figure 4: Types of secondary data (Saunders et al., 2009, p. 259)
Appendix VI: Table 2: Overview of key issue of the six categories of the PESTLE analysis (Compiled by the author based on Warner, 2010 and Perera, 2017)
Appendix VII: Table 3: Coinbase's series funding rounds (Compiled by the author based on Craft, n.d., Crunchbase, n.d., and Levy, 2021)
Appendix VIII: Figure 5: Coinbase's balance sheet (Compiled by the author based on Coinbase, 2021a and Yahoo, 2021a)
Appendix IX: Figure 6: Coinbase's income statement (Compiled by the author based on Coinbase, 2021a and Yahoo, 2021a)
Appendix X: Figure 7: Overview of the calculated ratios (Compiled by the author based on Coinbase, 2021a, Intercontinental Exchange, 2021, Nasdaq, 2021, Unlimited Consulting and Auditing Partnership, 2021, Yahoo 2021b, Yahoo, 2021c, Macrotrends, 2021a, and Macrotrends, 2021c)
Abstract
Coinbase's Nasdaq listing is a caesura for the cryptoeconomy since it is the first listing of a major cryptocurrency exchange in the USA. Coinbase's opening share price exceeds the reference price by more than 50%, resulting in Coinbase's valuation to top the aggregated value of the two well-established, traditional exchanges Intercontinental Exchange and Nasdaq. Given this listing's significance and size under consideration of Coinbase's relatively short existence and small revenue size, the question emerges whether the valuation is caused by Coinbase's business model or the cryptocurrency hype.
This thesis is intended to contribute to three goals: analyse Coinbase, derive recommendations for the cryptocurrency exchange's management, potential investors, and other cryptoeconomy participants, and create a better understanding of the crypto-industry and an enhanced acceptance of cryptocurrencies. For these purposes, Coinbase was used as a single case study and analysed qualitatively and quantitatively. A Five C's analysis was applied in the qualitative part, complemented by SWOT and PESTLE analyses and Porter's Five Forces. The quantitative analysis, in turn, consisted of eleven key ratios that were compared to Nasdaq's and Intercontinental Exchange's ratios. The analysis portrayed a fast-growing company that continuously expanded its core offering for its global retail and institutional customer base to a wallet, an exchange, and merchant tools by heavy investment in development. However, the results also illustrated Coinbase's strong reliance on transaction revenues. This dependence in addition to regulatory pressure, intensifying competition, and the market's fluctuations and maturing, might endanger the currently firm financial position in the future.
Index of Abbreviations
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1 Introduction
In spring 2021, the cryptocurrency market was experiencing a boom phase (Kharpal, 2021; Nagarajan, 2021).1 One primary driver was a Bitcoin rally, which resulted in the leading cryptocurrency in terms of market capitalisation reaching a $1 trillion market capitalisation within 12 years. This pace is 3.5 times faster than Apple and twice as fast as Amazon. Additionally, Ether, the second-largest cryptocurrency, reached its all-time high, which led to the aggregate cryptocurrency market capitalisation topping $2 trillion on April 6th, 2021. The COVID-19 pandemic can be considered one of the main reasons for the bullish cryptocurrency market as the trading volumes of the largest cryptocurrencies significantly increased in January 2020, considering the period from January 1st, 2019 to March 31st, 2020 (Corbet, Hou, Hu, Larkin, & Oxley, 2020; Pinto-Gutiérrez, 2021).
On April 14th, 2021, cryptocurrency history -again- was made with Coinbase Global, Inc. (Coinbase) becoming the first major cryptocurrency start-up and the biggest US cryptocurrency exchange being listed on a US stock market (Griffith, 2021; Deutsche Welle, 2021). To enter the Nasdaq, Coinbase used a direct listing approach instead of an initial public offer (Coinbase, 2021b; Deutsche Welle, 2021). Nasdaq initially set a reference price of $250 per share for the stocks of Coinbase, which trade under the ticker "COIN" (Wang, 2021). This equals to a $49.19 billion valuation. However, the stock opened at $381 per share, i.e., more than 52% above the reference price, corresponding to a valuation of Coinbase at $99.6 billion on a fully diluted basis (Wilhelm, 2021). This market capitalisation even exceeded the aggregate valuation of Nasdaq (approximately $25.89 billion) and Intercontinental Exchange (ICE) (approximately $65.24 billion) -the company that owns and operates the New York Stock Exchange (NYSE)- on April 14th, 2021, and placed Coinbase in the list of the 100 most valuable companies in the US (Macrotrends, 2021b; Macrotrends, 2021d; Giles, 2021).
Coinbase is not the first crypto-related company entering the stock exchange parquet. In 2018, for instance, Argo Blockchain was the first crypto-company being listed on the London Stock Exchange (Smith, 2018). Although only roughly ten months old, the crypto-mining company raised approximately £25 million and was valued at £47 million. After applying to be crosstraded publicly on the US OTCQB Venture market in December 2020, on February 24th, 2021, Argon Blockchain started to be traded in the highest over-the-counter (OTC) tier, OTCQX, in the US and is valued at £553.55 million on April 24th, 2021 (London Stock Exchange, 2021a; London Stock Exchange, 2021b).
During an earlier peak of the cryptocurrency market in late the 2017 and early 2018, the hype around cryptocurrencies and blockchain was so immense that stocks of companies that rebranded themselves to be considered affiliated with cryptocurrencies gained massively (Shapira & Leinz, 2017). This development even resulted in the US Securities and Exchange Commission (SEC) issuing a warning to companies regarding such a practice (Clayton, 2018). One of the most famous examples of this trend was Long Blockchain Corp, formerly known as Long Island Iced Tea Corp. The stocks of this beverage company spiked 500% in a day after its rebranding. In April 2018, however, the company was delisted from Nasdaq due to its inability to meet the exchange's rule of maintaining a market capitalisation above $35 million for ten consecutive business days and was investigated by the Federal Bureau of Investigation and the SEC (Tepper, 2018; Floyd, 2018; SEC, 2021; United States District Court for the Southern District of California, 2019; Palmer, 2019). As the rise and fall of Long Blockchain Corp. illustrate, even already exchange-listed companies can misuse the hype around the blockchain and cryptocurrencies to commit fraud.
Nevertheless, Coinbase's listing can be considered an ushering in a new era since it is the first cryptocurrency exchange to be publicly listed on a US stock exchange with large competitors like Kraken or Bakkt, a subsidiary of ICE, expected to follow soon (Giles, 2021; Akhtar, 2021; Browne, 2021).
1.1 Relevance of the topic and purpose of the thesis
Although Coinbase's listing can be examined a milestone for the crypto-sector, the effects on the individual cryptocurrencies and for the whole industry are still uncertain (Tepper, 2021; Domm, 2021; Magas, 2021).
With Coinbase, a company with the mission "to create an open financial system for the world" (Armstrong, 2017), entering the traditional financial market, the cryptocurrency market can be considered to be easier accessible for mainstream investors. However, the valuation of Coinbase in the range between $49 and $100 billion, i.e., in the latter scenario higher than of its established, traditional competitors Nasdaq and ICE combined, might be unreasonable and only driven by an unsubstantiated hype for cryptocurrencies (Kaminska, 2021; Trainer & Guske II, 2021).
Therefore, the purpose of this paper is to analyse the cryptocurrency exchange Coinbase, its business model, and its competitive situation to assess the valuation and develop strategic recommendations. Thereby, the paper is intended to contribute to a better understanding of the crypto-industry -particularly cryptocurrency exchanges- and an enhanced acceptance of cryptocurrencies as an investment asset. To holistically address this objective, the following research questions will be answered:
Research question one: What is Coinbase's competitive situation?
Research question two: What are Coinbase's competitive advantages and how can it improve its competitive positioning?
1.2 Structure and approach of the thesis
For a comprehensive analysis of the topic, the author first introduces this paper's research design and strategy in Chapter 2. Here, the reasoning for pursuing a case study strategy and relying on secondary data is also outlined. Afterwards, the theoretical frameworks used to evaluate Coinbase are presented. The author applies both qualitative and quantitative instruments to examine the cryptocurrency exchange holistically. Therefore, for the qualitative analysis, the Five C's analysis is introduced. Furthermore, to support the Five C's analysis, the concepts of the SWOT analysis, the PESTLE analysis, and Porter's Five Forces are described. For the quantitative evaluation, the description and calculation of eleven key ratios, including the EBITDA margin and Return on Equity, are introduced. This chapter is used as a foundation for the analysis of Coinbase in the subsequent chapter.
The qualitative part of the third chapter mainly consists of a Five C's analysis of Coinbase. To create an overview of the company, a SWOT analysis is used. Moreover, both a PESTLE analysis and Porter's Five Forces are conducted to assess Coinbase's industry environment. This section is followed by a quantitative analysis of Coinbase relying on the methods introduced in Chapter 2. Thus, several key ratios are calculated. To evaluate Coinbase's financial position, the ratios are compared to the cryptocurrency exchange's main traditional competitors, ICE and Nasdaq, and examined over time.
Chapter 4 contains the summary and discussion of the findings. Based on these results, the two research questions posed in sub-chapter 1.1 are answered and recommendations are compiled. Finally, in the fifth chapter, a conclusion of this paper is drawn.
1.3 Terminology
In this subsection, the main terms used in this thesis are defined and explained in detail, namely exchange and cryptocurrencies, blockchain, and cryptocurrency exchanges. This sub-chapter intends to provide a basis for a better illustration of Coinbase's business model and context.
1.3.1 Exchange
In general, an exchange is an organised and strongly regulated platform on which market participants can conduct transactions (Mishkin & Eakins, 2018; Scherbaum, 2020). A variety of products can be traded on exchanges. For example, stocks can be traded like on the NYSE, or commodities, such as raw materials, can be traded like on the Chicago Board of Trade.
Exchanges have been important in economic history for centuries (Scherbaum, 2020). The first stock exchange was founded in Bruges in 1409. However, this particular stock exchange was not established in a permanent location until 1513. In these days, the majority of trades were bills of exchange to facilitate cross-border transactions. Two of Coinbase's main competitors, the NYSE and the Nasdaq, are also considered milestones in the history of stock exchanges. The former, founded in 1792, was the first stock exchange across the Atlantic, while the latter, founded in 1971, was the first fully computerised stock exchange in the world. Besides their impact on history, these exchanges are still important today. In April 2021, the World Federation of Exchanges listed 83 stock exchanges (World Federation of Exchanges, 2021). Of those 83 exchanges, the NYSE and the Nasdaq are the stock exchanges with the largest domestic market capitalisations capturing approximately $24.7 trillion and $21.0 trillion, respectively.
According to Conant (1914), stock exchanges historically have two main functions: to create the largest possible market for securities and to record their current value with greater certainty. Furthermore, exchanges match the various demanders and providers of capital and improve the market's liquidity (Scherbaum, 2020; Mishkin & Eakins, 2018; Nabben & Rudolph, 1994). The demand side needs to raise capital for investments that are considered profitable in the future, whereas the supply side seeks to invest non-utilised capital at a profit, taking into account and pricing in the risk associated with the investment. The strong regulations of exchanges guarantee fair pricing. Due to its function, exchanges are one pillar of the secondary financial market2. The second pillar is the OTC market. Here, in contrast to an exchange, there is not one central location where buyers and sellers meet, but dealers with an inventory of securities sell to interested buyers contacting them directly. Examples of OTC markets are foreign exchange or the US government bond market.
Traditionally, an exchange was either an auction or a dealer's market (Mishkin & Eakins, 2018). In an auction market like the NYSE, trading and liquidity are facilitated by a single specialist in a centralised location, while a dealer's market, like the Nasdaq, is characterised by the existence of multiple market makers who provide transparency and liquidity as they publish their bid and ask prices. Transactions are then conducted through the dealers. In the 1990s, however, the transaction volumes handled through alternative trading systems grew rapidly (Conrad, Johnson, & Wahal, 2003). In 2018, the SEC estimated that alternative trading systems account for approximately 11.4% of the US trading volume (SEC, 2018). These systems eliminate the need for intermediaries (Mishkin & Eakins, 2018). Instead, buyers and sellers conduct transactions directly with one another, thereby achieving lower costs as well as faster, more time-flexible, and more transparent transactions.
Since the beginnings of exchanges, their operators have transformed their business models from providing only an organised, regulated, and central location for conducting transactions into becoming service providers that offer capital market participants various services, products and information (Nabben & Rudolph, 1994). Amid this transformation as well as increasing liberalisation and globalisation of trade and capital flows, exchange operators have also entered into competition with equivalent entities. ICE, for instance, has been attempting to persuade Microsoft's management to abandon Nasdaq and get listed on the NYSE for many years (Mishkin & Eakins, 2018). Moreover, the revenue structure of stock exchange operators has changed (OECD, 2016). In 2014, nearly 50% of the revenue of stock exchanges came from trading fees, including 26% through cash and capital market trading and 22% through derivatives and OTC markets trading. Additional income was generated by IT and market data services (19%), post trade services (16%), and listing and issuer services (8%). The change is mostly manifested in the increase of the derivatives and OTC markets trading by 7% compared to 2004, whereas listing fees decreased by 6% during the same time. Figure 1 illustrates the
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Figure 1: Revenue structure of stock exchanges (Compiled by the author based on OECD, 2016)
1.3.2 Cryptocurrencies, blockchain and cryptocurrency exchanges
Although the idea of an alternative, digital currency was brought up before, the concept of the digital currency Bitcoin, introduced by a whitepaper published by the pseudonymous “Satoshi Nakamoto” in 2008, was ground-breaking since it described an open-source currency without a central point of trust (Härdle, Campbell, & Reule, 2020). As Bitcoin was the first and is still the largest cryptocurrency in terms of market capitalisation, other cryptocurrencies are seen as alternatives to it and, thus, called altcoins (Aysan, Khan, & Topuz, 2021).
Cryptocurrencies are digital and decentralised assets, meaning they do not have a central authority like a central bank acting as governing authorities (Härdle et al., 2020; Urquhart & Yarovaya, 2020). They are mediums of exchange -like traditional currencies- relying on cryptography to secure and validate peer-to-peer transactions and transfers of assets and to control the generation of additional units. Furthermore, cryptocurrencies have no intrinsic value, but their value is created by the belief of sufficient users in the currency and forces of the market, i.e., supply and demand. Many cryptocurrencies have further, often unique features and rules, but according to Härdle et al. (2020), cryptocurrencies can be broadly divided into seven categories:
- Transaction mechanisms: these cryptocurrencies are only designed for transactions, i.e., as substitutes for traditional currencies. Examples include Bitcoin or Litecoin.
- Distributed computation token3 : tokens like Ether are earned by users who provide their computing resources to run small computer programmes on the nodes redundantly.
- Utility token: utility tokens are programmable blockchain assets that are bought with the means for future usage. Examples for utility tokens are Golem or Storj.
- Security token: these tokens are bought to generate a return on investment and represent bonds, stocks or other financial assets.
- Fungible tokens: fungible tokens are defined by the interchangeability with any samevalued asset.
- Nonfungible tokens: in contrast to fungible tokens, nonfungible tokens are unique due to the underlying data, which means that these tokens have different values.
- Stablecoins: cryptocurrencies that are either uncollateralised or collateralised with crypto- or fiat currencies or assets.
Most cryptocurrencies are based on the blockchain, although there are also examples, like IOTA, that rely on other technologies (IOTA Foundation, n.d.; Urquhart & Yarovaya, 2020). However, due to the limitations and the focus of this paper, the author will only provide a broad description of the blockchain since the majority of cryptocurrencies are utilising blockchain and an in-depth distinction would not be relevant, as also cryptocurrencies with other underlying technology are traded on Coinbase. In general, a blockchain is a recordkeeping system that is shared, i.e., distributed (PwC, n.d.; Härdle et al., 2020). The data of a blockchain are stored in sub-elements called blocks. A chain is formed through a one-way cryptographic hashing function, a mathematical algorithm that transmutes input into output called digest or hash. Each block's content is summarised in the hash at the end of the block. This hash is then repeated as the first code line of the following block, which guarantees the block's integrity. In case of inconsistency between the digest and the first code line in the following block, the succeeding block is rejected and replaced with a valid block. Cryptocurrencies generally utilise the blockchain as it increases transparency, allows traceability of data and cost reduction through efficiency improvement, and increases trust and security because of the inalterability of the blockchain technology (PwC, n.d.; IBM, n.d.; Härdle et al., 2020).
With cryptocurrencies attracting more and more users, marketplaces, i.e., exchanges, were developed (Svec, Foley, & Aspris, 2020). There are two main types of cryptocurrency exchanges - centralised and decentralised exchanges. Most exchanges, including major players like Binance or Coinbase, are centralised and, thus, very similar to traditional exchanges like the Nasdaq or NYSE. In fact, CoinMarketCap (2021) listed 310 spot, 38 derivatives, and 71 decentralised not mutually exclusive cryptocurrency exchanges in June 2021. Centralised exchanges are characterised by one trusted counterparty that provides private keys to hot wallets -addresses for deposits and withdrawals controlled by the exchange- and is responsible for accepting withdrawals and deposits in crypto- and fiat currencies and for the operation of the centralised limit order book (Svec et al., 2020). Moreover, these exchanges are accountable for the deposits within the market and keeping track of the ownership status of the cryptocurrencies held within their system. They also must comply with the so-called “Know Your Customer”4 regulations. These exchanges can also choose which assets are tradable on their platform and which markets they create by enabling currency pairs, such as Ether and Euro or Bitcoin and Ether. Although centralised exchanges bear the advantage of one responsible organisation, they are threatened by potential hackings or bankruptcy. Decentralised exchanges, in turn, are typified by no single controlling and operating entity, which results in an in-hackability. Examples of major, decentralised exchanges are Bisq or 0x. Their development was enabled by the possibility of smart contracts5 in the Ethereum network, which allows the coding of limit orders as self-contained contracts. The first decentralised exchanges processed all entries, executions, and cancellations of orders on the Ethereum blockchain. Users can monitor all available orders of a virtual limit order book -an aggregation of self-contained contracts- to rank them according to their price preference and select which orders to interact with. Appendix I provides an overview of the operation of a decentralised, fully on-chain exchange.
A recent trend is the upcoming of hybrid exchanges (Svec et al., 2020). These exchanges have a centralised organisation collecting all order entries, changes, and cancellations off-chain -like centralised exchanges-, but clearing and custody are processed on the Ethereum blockchain. On the one hand, this creates a single point of failure; on the other hand, the centralisation allows faster transaction confirmation and cost reduction due to eliminating miner costs for updating stale limit orders. Appendix II illustrates the operation of a hybrid exchange.
Cryptocurrency exchanges generate revenue with different types of fees (Stone, 2021). There are three types of fees depending on the user's behaviour. Trading fees are the primary income generator of exchanges and are charged for trades. Most exchanges rely on the maker-taker model, which results in higher fees for immediate transactions and lower fees for liquidity providers (Svec et al., 2020). An average-sized transaction causes a transaction fee ranging between 0 and 15 basis points for liquidity providers and between 10 and 30 basis points for liquidity consumers, although the fee strongly depends on the traded currency. Deposit and withdrawal fees are not levied by all exchanges (Stone, 2021). The latter ones usually are limited to cover the blockchain transaction costs; however, some exchanges might charge additional fees based on the type of withdrawal, i.e., as fiat currency or cryptocurrency, and the user's country. Lastly, exchanges that offer margin trading typically levy interest, borrowing, and liquidation fees dependent on the interest rate and the borrowed amount.
2 Methodology
The author describes both the research design and strategy and the research tool used in this paper in the following chapter. First, the theoretical foundation is laid by outlining the design and strategy of a case study thesis. Thereafter, the author delineates the various qualitative and quantitative frameworks that form the basis of the analysis of Coinbase.
2.1 Research design and strategy
Following Saunders, Lewis, and Thornhill (2009) and Yin (2013), research design is the process of converting research questions into a research project. The research design depends on the research questions and contains the purpose of the research, determines the research strategy, specifies the sources, and considers potential constraints, for instance, due to limited access to data.
Generally, research can have the objective to be either exploratory, descriptive or explanatory (Saunders et al., 2009). Exploratory studies aim to clarify the understandings of phenomena and to create new insights and are flexible. They build the foundation for future, more in-depth research. The goal of descriptive studies, in turn, is to present a detailed profile of situations, events, or persons based on extensive knowledge about the to-be-researched phenomena. Lastly, researchers conducting explanatory research focus on problems or situations to establish causal links between variables. The author considers the primary purpose of this thesis to be exploratory since the research can be used as the groundwork for future studies about cryptocurrency companies entering the traditional financial market.
Although some research strategies can be allocated to either exploratory, descriptive or explanatory research, each strategy can be used for each research objective in general (Saunders et al., 2009; Yin, 2013). There are eight types of research strategies a researcher can follow. However, due to the limitations of this paper, the author will shortly outline only the one used in this thesis hereunder. An overview of the other seven strategies is provided in Appendix III.
- Case study: By following a case study strategy, a researcher is conducting an empirical inquiry of a specific, current phenomenon within its actual environment. It is useful to gain an in-depth understanding of both the processes and the context of the researches and this particular strategy is mainly used for either explanatory or exploratory research. Pursuing a case study strategy, a researcher can choose from a broad range of data collection techniques, including, for instance, documentary analysis or interviews. Generally, four case study strategies based on two dimensions are distinguished. On the one hand, a researcher can either decide to adopt a single case or multiple case study approach. The former often is chosen when the case is critical or unique, when it is used to analyse a phenomenon that was an uncommon research topic before or when the case is very typical. Covering multiple cases, i.e., more than one, might be reasonable if the researcher wants to generalise his findings from the first case. On the other hand, the second dimension addresses the unit of the analysis and distinguishes holistic or embedded cases. While holistic case studies are only covering an organisation as a single unit, embedded case studies, in turn, differentiate the organisation or organisations into logical sub-groups like departments.
According to Yin (2013), to decide on an appropriate research strategy, three criteria must be analysed and matched. Firstly, the suitability of a strategy for an individual research project depends on the form and the possibility to answer the stated research questions. Case studies, for instance, are best use for answering “how” and “why” questions. Secondly, the researcher has to consider whether there is control of behaviour events required with only experiments giving researchers the control to intervene or manipulate behaviour directly. Lastly, the degree of focus in contemporary events is a critical decision criterion. Table 1 in Appendix IV summarises the criteria for a selection of strategies.
After analysing the key decision criteria stated by Yin (2013), the author decided to follow a single, holistic case study strategy. This methodology is considered appropriate since the research questions established in subsection 1.1 are “what” and “how” questions. Moreover, since there is no control of behavioural events required, a case study strategy is adequate. Additionally, as Coinbase was listed on April 14th, 2021, the research covers a contemporary event as the editing period of this thesis lasts from February 2021 to July 9th, 2021. Moreover, although the pursuit of a multiple case study strategy should be preferred to a single case study strategy in general, for this thesis, a single case study strategy was chosen due to the unique character of Coinbase's listing (Yin, 2013). As Coinbase is the first major cryptocurrency exchange listed on a US stock exchange, the cryptocurrency company is a forerunner with no direct competitors usable for a multiple case study strategy.
Regarding the main type of data source, Saunders et al. (2009) distinguish two types of data: primary and secondary data. Primary data are defined as the collection of new data for a specific objective. Secondary data, in turn, contain raw data as well as published summaries and have already been collected prior to the research objective. Sources of secondary data are organisations -for instance, in the form of payroll details or accounts of sales of goods or services-, quality daily newspapers -for example, by way of reports about share prices-, consumer research organisations, and trade organisations. Secondary data can include both qualitative and quantitative data. Qualitative refers to collecting or analysing data, which generates or uses non-numerical data, whereas quantitative describes a way of collecting or analysing data, which generates or uses numerical data. Following the classification of Saunders et al. (2009), there are three sub-groups of secondary data: documentary, survey-based and compiled from multiple source data. Documentary data include both written and nonwritten materials. Examples of written materials are books, newspapers, reports to shareholders, and administrative and public records, while non-written materials can, for instance, be video or voice recordings. Survey-based data are data gathered through the survey strategy, which have already been analysed for their initial objective and made available as compiled data tables or raw data matrices. The final sub-group is multiple source data, which are combinations of data sets to form a new data set. These sets can be compiled in two ways. The sets are timeseries based, i.e., extracted and combined of selected comparable variables from several surveys or the same survey, which has been repeated several times. The second approach is area-based, i.e., the different sources have an identical geographical basis. Figure 4 in Appendix V provides an overview of the different types of secondary data, including examples for each.
Secondary data is most used for survey research or case studies (Saunders et al., 2009). Therefore, the author considers the application of secondary data of all types as appropriate. Precisely, the main secondary data sources will be written materials and multiple source.
2.2 Research instruments
Hereafter, the qualitative and quantitative instruments, which are used to analyse Coinbase, are introduced. Due to the limitations of this thesis as well as to the usage of multiple frameworks to address potential loopholes and weaknesses of the individual tools, a discussion of advantages and disadvantages of the individual frameworks is not included.
2.2.1 Qualitative instruments
Overall, four qualitative instruments will be presented below and used in Chapter 3 to analyse Coinbase. First in this section, an overview of the Five C's analysis is provided. Subsequently, the SWOT analysis is introduced. In addition, the concept of the PESTLE analysis is outlined. The section is closed with an introduction to Porter's Five Forces framework.
Due to the similarity of the external factors of the SWOT analysis -opportunities and threatsand both the PESTLE analysis and Porter's Five Forces model, the author will focus primarily on the internal factors -strengths and weaknesses- in the company analysis of the Five C's model in Chapter 3 to avoid redundancy. The PESTLE analysis, in contrast, will be used to assess the context of Coinbase's industry, whereas Porter's Five Forces will be adopted mainly to analyse the competitive position of Coinbase. Potential limitations of the individual tools will not be discussed due to the number of frameworks used and the restrictions of this paper.
2.2.1.1 Five C's analysis
Originally, the Five C's analysis is part of a company's marketing strategy as it is utilised to identify the target market (Dolan, 1997; Chernev, 2018). However, since it is applicable to create a holistic overview of the researched firm and major stakeholders, the Five C's framework will be used as the main qualitative tool of this thesis. In particular, the framework is applied to analyse five important areas: the company, customers, competitors, collaborators, and context (Dolan, 1997; Chernev, 2018). Each of the areas is briefly described below.
The company is the element that creates, provides and manages a specific offer (Chernev, 2018). The company can have one or multiple functions including manufacturing and selling actual goods, acting as a retailer or providing a service. To create market value, a company depends on two factors - its goals and its profile. The former describes the results the company is planning to achieve with its offer and can be either strategic or monetary. The latter, in turn, includes the features of a company like employees, know-how or access to capital. For a comprehensive company analysis, it is also essential to understand the strengths and weaknesses of the company, its financial position, manufacturing capability, and other assets (Dolan, 1997).
Customers form the second C of the analysis. The company aims to fulfil the needs of its target customers, which can be both organisations and individuals (Chernev, 2018). Customers are characterised by their needs and profiles. Customers have particular needs that the company tries to address with its offer. Customer profiles, in turn, include attributes such as demographics and behaviours of the customers.
Competitors are companies that offer the same customers a solution to the same need as the company and, therefore, do not have to operate in the exact same industry as the company (Chernev, 2018). This category includes both current and potential competitors (Dolan, 1997). As for the company, it is important to detect strengths and weaknesses and to analyse the goals and strategies of the competitors.
Fourth, collaborators are partners that enable the company to create value for its target customers (Chernev, 2018). In general, collaborators can be either downstream, such as retailers, or upstream suppliers (Dolan, 1997). The selection of collaborators depends on the supplementary nature of the resources provided by the collaborators and the resources needed to solve the customer's needs (Chernev, 2018). As collaborators often are essential for a company's success, understanding their support requirements, relationships with the company's competitor, and financial positions is crucial (Dolan, 1997).
The Five C's framework is concluded with a context analysis (Dolan, 1997; Chernev, 2018). The context is equivalent to the environment a firm is operating in and it sets the boundaries. As the environment is undergoing constant change, its spotting ahead of the competition is an important competitive advantage. Generally, the context of a company poses both opportunities and threats and is shaped by five factors:
- Political and regulatory context, which comprises laws and other regulations like taxes.
- Economic context, which describes the macroeconomic status of the country or countries the company operates in. It is analysed by indicators such as inflation and economic growth.
- Socio-cultural context, which includes the value systems, religions, language, beliefs and attitudes as well as demographic and social developments.
- Technological context, which comprises new skills, processes, techniques, and methods that are usable for offering the solution to the customers' needs.
- Physical context, which contains external factors such as climate, geographic location, natural resources or health trends.
2.2.1.2 SWOT analysis
The SWOT analysis is an important part of the strategic planning and management process (Miles, 2013; Gürel & Tat, 2017). The two-dimensional tool combines internal and external analysis since it explores internal strengths (S) and weaknesses (W) as well as external opportunities (O) and threats (T) (Yeates, Cadle, Eva, Hindle, Paul, Rollason & Turner, 2014; Miles, 2013). Hereafter, the four components of the SWOT analysis are described in more detail.
Organisational strengths are value-adding characteristics, which result in competitive advantages (Miles, 2013; Gürel & Tat, 2017). Strengths can be skills, resources or abilities and are crucial in reaching a company's goals. Organisational weaknesses, in turn, are the lack or inferiority of internal properties and abilities compared to the competition. Weaknesses reduce a company's efficiency and effectiveness and cause competitive disadvantages. Both strengths and weaknesses can result from, for example, human resources, technology, or location and are -at least partly- in the control of the company.
Environmental opportunities and threats, however, are mostly beyond the control of the firm, and, therefore, are external factors (Miles, 2013; Gürel & Tat, 2017). Opportunities are favourable conditions, times or situations for an action that might result in potential advantages for companies. In contrast, environmental threats are adverse conditions, times or situations that endanger the execution of an activity impede or even make it impossible to achieve the firm's objectives. According to Gürel and Tat (2017), opportunities and threats result from changes in politics, economy, society, technology, legal system, environment, culture, government, demography, and competitive situation.
2.2.1.3 PESTLE analysis
In contrast to the SWOT analysis, the PESTLE analysis is evaluating exclusively the external environment of an industry or a company by taking six context categories -political (P), economic (E), socio-cultural (S), technological (T), legal (L), and environmental (E)- into account (Perera, 2017). They are briefly outlined below.
The political environment is influenced by changes and decisions in the political arena and includes factors like political stability of a country, government actions, subsidies and changes of or the impact of policies including fiscal, monetary, and exchange-rate (Warner, 2010; Perera, 2017). Main actors in the political context are not only local or national governments, but also governmental and regulatory agencies, like the SEC, and international regulatory organisations, like the World Trade Organisation (Warner, 2010).
According to Perera (2017), the second category has to be considered the most important for a company's success. Here, developments and changes in the economic context of a firm are analysed by exploring macroeconomic indicators and economic impact factors (Warner, 2010; Perera, 2017). These impact indicators include, for instance, inflation rates, employment rates, exchange rates or interest rate direction forecasts.
The status and change of both the beliefs and values and the demographics of a country are considered in the analysis of the socio-cultural environment (Warner, 2010; Perera, 2017). Although shifts in values and beliefs are difficult to identify, they can strongly impact an industry both in short- and long-term as the upcoming of stronger environmental protection demand illustrates. Additional values and beliefs are, for example, religious beliefs, norms or traditions. Demographics, in turn, are easier to identify, since these are statistics about the structure of a population, and include, for instance, the size of the age cohorts or the income distribution.
With technology being integral in nearly every industry today, the fourth step in the analysis is of essential importance (Warner, 2010; Perera, 2017). It is crucial to consider not only technological changes within the own sector, i.e., how one particular industry is attempting to solve customers' problems, but also outside of the industry, since innovations can change the rules of business from the outside. The upcoming of the Internet, for example, reduced the need for intermediaries in many industries. Furthermore, sector borders can become blurred with formerly separated industries converging. Results are both new threats, for instance, in the form of new competitors, and new opportunities, for example, with additional potential customers.
The legal environment can, in some cases, overlap with the political context of a company (Warner, 2010). However, following Perera (2017), legal factors form the fifth category of the PESTLE analysis. In contrast to the political environment, here guidelines, acts, rules as well as laws and regulations relevant for the company are considered.
Finally, the PESTLE tool is closed with an analysis of the environmental context of the company (Perera, 2017). In the past, this step was more important for manufacturing firms since it includes the considerations of the carbon footprint or waste disposal mechanisms as well as of geographical factors like raw material availability. However, due to the increasing pressures of the climate change and sustainability concerns, the environmental aspects should be included in the analysis of service companies, as well. Table 2 in Appendix VI provides an overview of important issues for each of the six categories of the PESTLE analysis.
2.2.1.4 Porter's Five Forces
The Five Forces framework was originally developed by M. Porter to analyse the impact factors on a specific industry's profitability (Warner, 2010). However, due to the structured and holistic approach, the author considers the use of the tool appropriate for the assessment of the industry and Coinbase's competitive situation. In particular, Porter (1979) developed a model in which the bargaining powers of customers and of suppliers, the threats of new entrants and of substitutes, and the rivalry define the state of the industry's competition as the five dominant forces. This competition can range from mild to intense and determines the profit potential of a sector. Moreover, the importance and impact of each single force depend on the particular sector and can change over time. In the following, the Five Forces are characterised succinctly. The severity of the threat of new entrants is determined by the presence and degree of six possible barriers and by the expected reaction of existing competitors (Porter, 1979; Warner, 2010). Porter (1979) identified the following sources of entry barriers:
- Economies of scale: these economies can appear as barriers in nearly each area of a company and can discourage new entrants by requiring the contender to either accept a cost disadvantage or enter on a large scale. According to Warner (2010), economies of scale can be technical6, purchasing7, financial8, managerial9 or marketing10.
- Product differentiation: customers might value a product or service and be willing to pay more and stay loyal to a brand. This causes new entrants to have to invest strongly to surmount this brand loyalty, and, therefore, can be seen as a barrier.
- Capital requirements: incumbents have an additional advantage due to their already established position and the industry's barriers. New entrants have to overcome this barrier in the form of heavy upfront investment, which is an obstacle itself.
- Cost disadvantages independent of size: in addition to economies of scale, incumbents can also have cost advantages caused by effects of the learning and experience curve, access to raw materials, favourable locations, proprietary technology, the possibility to purchase assets at pre-inflation prices or government subsidies.
- Access to distribution channels: this barrier results from the difficulties in establishing distribution channels, especially if the distribution of the new product has to come at the displacement of incumbents' products.
- Government policy: a final barrier can come from the government in the form of regulations, for instance, by limiting access to raw materials, license requirements or safety regulations.
Entrants will not represent a serious threat, if the entry barriers are stringent and new entrants can expect strong retaliation from the incumbents (Porter, 1979; Warner, 2010).
The second force to consider is the bargaining power of suppliers (Porter, 1979; Warner, 2010). Suppliers are powerful if they are concentrated, i.e., there are only a few suppliers available, since the industry has to compete for a small number of suppliers, which results in higher purchasing prices. Furthermore, the power of suppliers is high if there are not many or no substitutes at all available or if buyers wanting to change their supplier are facing extensive switching costs. This increases the suppliers' power because it diminishes the ability of focus industry firms to look for alternative sources. A third reason for powerful suppliers is a credible threat of forward integration, i.e., the threat of the supplier entering the industry as a new competitor. Moreover, if the industry is rather unimportant for the supplier in terms of revenue, this increases the suppliers' power as they are not strongly tied to the fortunes of the industry. Similar to the bargaining power of suppliers, the bargaining power of buyers is high if buyers are more concentrated than the industry participants or if they buy in large quantities (Porter, 1979; Warner, 2010). Furthermore, following the same reasoning as for suppliers, standardised or undifferentiated products lead to high buyer power. A credible threat of backward integration into the focal industry from the buyers increases their power. Lastly, if the purchases from the industry constitute a significant part of the buyer's total costs or the purchased product is important for the quality of the products and services, buyers are more likely to be price sensitive.
The fourth force is the threat of substitutes (Porter, 1979; Warner, 2010). Substitutes reduce the profitability of an industry as they limit the prices an industry can charge for its products and services. The threat of substitutes is especially high if the switching costs are low, i.e., if customers can purchase substitutes without having to consider sunk costs. Additionally, substitutes are powerful if the price and/or quality performance of the substitute is very attractive compared to the industry.
Last, competition between incumbents is considered the fifth force (Porter, 1979; Warner, 2010). According to Warner (2010), the profitability of an industry decreases with increasing rivalry since companies are forced to compete on the basis of price. One main factor analysing the intensity of an industry's rivalry is the number and size of competitors within the industry (Porter, 1979; Warner, 2010). If there are many companies or the rivals are of similar size or power, the rivalry is considered intensive. Furthermore, rivalry is considered fierce if the industry growth is slow, for instance lower than the GDP growth, as competitors aiming for expansion have to fight for market shares. Moreover, following the rationale of buyers' and suppliers' powers, rivalry is more intensive if the products are standardised or have low switching costs. Also, the probability of intense rivalry is high if the industry is characterised by high fixed costs or perishable goods since companies are forced to create high sales volumes to cover the fixed costs. Another factor of fierce rivalry can come from the background of the competitors. If the companies have different strategies and origins, they are more likely to compete more intensively. The strategic relevance of the industry for the companies can also play a decisive role. If the industry consists of less diversified companies, the strategic stakes are higher, which also leads to higher intensity, as the survival of the companies is directly dependent on the industry. Finally, the exit barriers of an industry influence the rivalry. The higher the exit barriers, like very specialised assets, the more intensive the competition. This results from the fact that companies will continue operating in the industry even though they might generate low or even negative results due to sunk cost fallacy.
2.2.2 Quantitative instruments
The quantitative analysis of Coinbase will be conducted by an evaluation based on comparables. Although the usage of multiples is a theoretically less well-founded strategy, it is a pragmatic, practically relevant approach based on the actual prices of companies compared to the theoretic, comprehensive discounted cash flow method that relies on the forecasts of future cash flows (Schmidlin, 2014; Berk & DeMarzo, 2017). Also, when using ratios, it is essential to consider their development over time and compare them with those of peers in the same industry. Therefore, the author will compare Coinbase's margins for 2019 and 2020 to ICE and Nasdaq since no other cryptocurrency exchange has published its financial data yet. Pursuing the comparables approach is considered appropriate since the thesis aims to be relevant for practitioners and to examine Coinbase compared to traditional exchange operators. A general evaluation of the exchange industry is not in the scope of the work. The commutation and application of eleven key ratios provide an in-depth analysis of the company and enhances the comparability.
In general, there are four categories of financial ratios distinguished: capital structure or leverage ratios, activity or efficiency ratios, profitability ratios, and liquidity ratios (Miller, 1997; Ginter, Swayne, & Duncan, 1997; Kulkarni & Mahajan, 2008). Leverage ratios are used to assess the capital structure, i.e., the composition of debt, assets, and equity, of the company and, thus, to analyse the financial risk of the firm (Engle, 2010). In this thesis, the Debt/Asset and Debt/Equity ratios are used as leverage ratios. Activity ratios, in turn, are used to examine the pace of transforming assets into sales and measure asset management efficiency (Kulkarni & Mahajan, 2008). The Asset turnover ratio, as well as the Accounts Receivable Days and Accounts Payable Days are used to analyse the efficiency of Coinbase. The third category of ratios is concerned with the overall economic performance of a company and is a measurement if and to what degree the income streams surpass the expenses of a firm (Miller, 1997; Ginter, Swayne, & Duncan, 1997). These ratios are the core of this thesis's quantitative analysis and include the Return on Equity, Operating Profit margin, EBITDA margin, and Earnings per share (EPS). Finally, liquidity ratios are used to assess the short-term solvency or financial strength of a company by describing the capability of a company to meet its short-term obligations (Kulkarni & Mahajan, 2008). Here, the author uses the Current and the Quick ratio. A short
overview of the ratios and their calculations is provided below.
2.2.2.1 Debt/Asset ratio
The Debt/Asset ratio is used to measure the value of the total amount of debt compared to the total value of the assets (Engle, 2010). Generally, smaller values of this ratio are considered more favourable in terms of financial stability and solvency. According to the formula, a value exceeding 1 represents an insolvent firm since the value of all assets is smaller than the value of the debt.
2.2.2.2 Debt/Equity ratio
The Debt/Equity ratio is closely monitored by both investors and creditors (Bragg, 2012). The ratio indicates to what degree a company's management is using equity rather than debt to fund its operations. The importance for lenders comes from the risk of not being repaid if the ratio is excessively high. As creditors prefer less risky companies, a lower ratio is favourable.
2.2.2.3 Asset turnover ratio
Asset turnover is an efficiency ratio, which implies how many units of a currency of the revenue are generated per invested unit of currency (Ginter, Swayne, & Duncan, 1997; Schmidlin, 2014). This means that high asset turnover ratios are preferred as they indicate more efficient resource management as the capital flow back into the company is faster.
Formula of the Asset turnover ratio:
Total Revenue
Total Assets
2.2.2.4 Accounts Receivable Days
Accounts Receivable Days is a measurement of the time the accounts receivable of a company are outstanding, i.e., how long it takes a company to convert its sales into cash (Berk & DeMarzo, 2017). A high ratio can cause concerns as the company needs a long time to collect its money; however, a more extended payment period can also be used to attract customers through favourable credit terms.
Formula of the Accounts Receivable Days:
2.2.2.5 Accounts Payable Days
Accounts Payable Days are an indicator of a company's efficiency (Bragg, 2012; Berk & DeMarzo, 2017). They measure a company's capacity to pay invoices promptly. While a low number of days can indicate financial health, since the company is paying bills earlier than needed, the low number can also be incentivised by early payment discounts. A high number of days, in turn, can signal that the focal company has insufficient cash flow to pay its invoices.
Formula of the Accounts Payable Days:
2.2.2.6 Return on Equity
The Return on Equity is one of the most important profitability ratios for investors (Schmidlin, 2014; Ginter, Swayne, & Duncan, 1997). A low Return on Equity implies an overvaluation of the company's assets or an inefficient capital use. However, a high ratio can result from debt- financed share buy-backs and, thus, the Return on Equity should not be used as only profitability ratio (Bragg, 2012).
Formula of the Return on Equity:
2.2.2.7 Operating Profit margin
The Operating Profit margin is a measure of the core operations' profitability since it excludes additional income and the impact of extraordinary items, such as the sale of assets (Bragg, 2012; Ginter, Swayne, & Duncan, 1997). In general, a high Operating Profit margin is more favourable than a low ratio.
Formula of the Operating Profit margin:
2.2.2.8 EBITDA margin
The EBITDA margin is an indicator of the efficiency of a company's operating model (Choudhary, 2020). It measures the generated operating cash in relation to the revenue and is preferred to the net profit margin since it excludes unique and non-operating impacts like taxes (Tarver, 2019). In general, a high EBITDA margin indicates low operating expenses compared to the revenue.
Formula of EBITDA margin:
2.2.2.9 Earnings per share
EPS is one of the main ratios used to compare the profitability of public companies (Bragg, 2012). It is a measure of the net profit of a company per outstanding common share. Generally, a higher EPS implies a more profitable company.
Formula of Earnings per share: : :
2.2.2.10 Current ratio
The Current ratio is a liquidity indicator that shows whether a company can meet its short-term financial obligations by generating revenue through its current assets, i.e., its working capital (Berk & DeMarzo, 2017; Ginter, Swayne, & Duncan, 1997). In general, a Current ratio above 1 implies that a firm has sufficient liquidity for precisely one year but no reserves for adverse developments (Engele, 2010). Therefore, higher Current ratios, especially above 2, are considered beneficial.
Formula of the Current ratio:
2.2.2.11 Quick ratio
In contrast to the Current ratio, the Quick ratio excludes inventory, resulting in an even stricter short-term focused liquidity ratio (Bragg, 2012; Ginter, Swayne, & Duncan, 1997). A Quick ratio between 90% and 100% is considered optimal since an excessive ratio implies that too much cash is bound up in the business (Schmidlin, 2014).
Formula of the Quick ratio: :——
3 Analysis of Coinbase
In the following chapter, Coinbase is analysed using both qualitative and quantitative frameworks described in section 2.2.
3.1 Qualitative findings
As described in section 2.2.1, the author used four qualitative frameworks: the Five C's analysis, SWOT analysis, PESTLE analysis, and Porter's Five Forces model, to analyse Coinbase. The Five C's analysis provided a structure into which the other frameworks were integrated. In this way, the Strengths and Weaknesses from the SWOT analysis were incorporated into the Company description. On the other hand, Porter's Five Forces were applied to describe the Competition, while the PESTLE analysis was used for the global Context. The PESTLE factors then were classified either as Opportunities or as Threats. Below, the findings are presented.
3.1.1 Company
Coinbase, founded in 2012 by Brian Armstrong -a former software developer at IBM and Airbnb and an early cryptocurrency adopter-, who is also the current CEO, and Fred Ehrsam - a former foreign exchange trader at Goldman Sachs-, is an online platform that enables customers to buy, sell, transfer, and store digital currencies (Coinbase, n.d.a; Coinbase, n.d.e; CB Information Services, 2018). Particularly, Coinbase offers three distinct services (CB Information Services, 2018; Armstrong, 2017). Firstly, Coinbase offers the Global Digital Asset Exchange called Coinbase Pro, an order book exchange for more advanced, large-volume traders, such as institutional players. The Global Digital Asset Exchange trades determine the mid-market price and provide Coinbase with a secure internal liquidity source. These functions are important for the second service - Coinbase's brokerage. Coinbase is also operating a brokerage in the form of an exchange for retail investors. These can buy and sell cryptocurrencies at the mid-market price plus a fee. Due to the in-house liquidity source, Coinbase is independent of external liquidity, which reduces the volatility of the underlying cryptocurrencies. Thirdly, Coinbase launched Toshi, a browser for decentralised apps11 (DApp), in 2017 (Coelho-Prabhu; 2018; CB Information Services, 2018). Toshi then was further developed to become the first wallet that launched crypto-collectables, i.e., nonfungible tokens. In August 2018, Toshi was rebranded and became Coinbase Wallet. Thus, Coinbase is offering wallet, exchange, and merchant tools on one platform. Additionally, through its Application Programming Interface, applications can be built on the Coinbase platform. In October 2020, Coinbase launched an additional product in the US - the Coinbase Card (Coinbase, 2020b). This Visa debit card enables users to spend their cryptocurrencies stored on Coinbase for ATM cash withdrawals as well as both purchases and payments in-store and online. With Coinbase Prime, Coinbase introduced its latest service on May 25th, 2021(Coinbase, 2021d). Coinbase Prime is only accessible for institutional clients and is a prime brokerage solution that enables advanced trading, data analytics, sophisticated services, and best-in-class custody. In July 2021, Coinbase is available in more than 100 countries, has more than 56 million verified users and more than 1,700 employees worldwide, and supports 108 cryptocurrencies (Coinbase, n.d.a). Coinbase's quarterly trading volume totalled $335 billion, while crypto-assets worth approximately $223 billion are stored on the Coinbase platform. A steep ascent, considering that Coinbase's Seed, raising about $600 thousand, in 2012 lies less than ten years in the past (Craft, n.d.; Levy, 2021; CB Information Services, 2018). Until its direct listing on Nasdaq in April 2021, Coinbase conducted several series funding rounds, raised more than $540 million, and attracted a mix of corporate investment and venture capital. With $108.1 million equity raised in Series D, Coinbase reached the unicorn status in 2017, only five years after its founding. An overview of the funding rounds, the raised equity, and the share price is provided
[...]
1 To enhance the reading flow, the generic masculine is used.
2 In the financial market, the primary and the secondary market can be distinguished. In the former, new issues of securities, i.e., for instance, of stocks or bonds, are offered to initial buyers by government agencies or corporations. In the latter, in turn, securities, which already have been issued by government agencies and corporations, can be bought and sold by government agencies, corporations, and individual investors (Mishkin & Eakins, 2018).
3 Although crypto-coins and -tokens can have similar functions, they are distinguished by their relation to the blockchain. While coins are native to their blockchain and mainly used for transactions, tokens are created for decentralized applications on already existing blockchains and, thus, can have multiple purposes (see also EC- Council, n.d.). Due to the scope of this thesis, no distinction of coin and token is made and they are both addressed as cryptocurrency.
4 The Financial Industry Regulatory Authority introduced the rule 2090 in July 2012. This regulation obliges all brokers or dealers to use reasonable effort to open and maintain client accounts. In particular, they are required to be familiar with and record the material facts of each customer and to identify each person authorised to act on the client's behalf (Financial Industry Regulatory Authority, n.d.).
5 Smart contracts are programmes using the Ethereum blockchain. They are collections of code and data, have defined rules, are not controlled by users, and can be automatically enforced by code (Ethereum Foundation, 2021).
6 Most important economies of scale created by replacing labour with capital, i.e., through automatization.
7 Purchasing or commercial economies arise from bulk purchasing.
8 Financial economies result from the size of a firm and are manifested in lower interest rates only due to the size.
9 Managerial economies are administrational benefits arising from organisational improvements.
10 Marketing economies are the ability of a company to divide high advertising costs on a larger output level.
11 A DApp is similar to a traditional app, but its backend code runs on a decentralised peer-to-peer network in contrast to a centralised server. It combines a front-end user interface and a smart contract (Ethereum Foundation, 2021).
- Quote paper
- Andreas Renner (Author), 2021, Coinbase’s Nasdaq listing as a caesura. Qualitative and quantitative analysis of a major US cryptocurrency exchange, Munich, GRIN Verlag, https://www.grin.com/document/1144631
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