Crypto Assets Study 2025: An Overview of the Swiss and Liechtenstein Crypto Assets Ecosystem

FH Zentralschweiz Crypto Assets Study 2025 An Overview of the Swiss and Liechtenstein Crypto Assets Ecosystem Institute of Financial Services Zug IFZ www.hslu.ch/ifz 1Crypto Assets Study 2025 Contents 1 Introduction 2 1.1 DefinitionofCryptoAssets............................................... 3 1.2 MethodologicalApproach ............................................... 3 2 Structure of the Investment Ecosystem for Crypto Assets 4 3 Overview of Providers of Crypto Asset-related Products and Services 7 4 Overview of Market Activities 9 4.1 IndirectInvestments .................................................. 9 4.2 DirectInvestments ................................................... 16 4.3 Tokenisation....................................................... 18 4.4 Summary......................................................... 20 5 Crypto Assets as an Investment 21 6 Institutional Investors in Crypto Asset Markets 26 6.1 Definition and Characteristics of Institutional Investors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 6.2 LiteratureReview .................................................... 27 6.3 On-chainAnalysis.................................................... 28 6.4 Off-chainAnalysis.................................................... 32 6.5 Summary......................................................... 34 7 Conclusion and Outlook 35 Authors 36 References 37 Introduction 2 1. Introduction The fifth edition of the “Crypto Assets Study” provides an overview of the current state and developments in the investment ecosystem for crypto assets in Switzerland and the Principality of Liechtenstein. As in previous years, the objective is to provide a data-driven overview for both industry stakeholders and external audiences, such as investors, service providers, and regulators. A general overview of global market developments can be drawn from the total market capitalisation of publicly traded crypto assets, illustrated in Figure 1.1. 0 1,000 2,000 3,000 4,000 Jan 2018 May 2018 Sep 2018 Jan 2019 May 2019 Sep 2019 Jan 2020 May 2020 Sep 2020 Jan 2021 May 2021 Sep 2021 Jan 2022 May 2022 Sep 2022 Jan 2023 May 2023 Sep 2023 Jan 2024 May 2024 Sep 2024 Jan 2025 May 2025 USD (in billions) Figure 1.1: Total market capitalisation of crypto assets, by end of period (source: CoinGecko (online-a)) After a steady recovery phase that began in late 2023, the market reached a new end-of-month all-time high of approximately USD 3.7 trillion in January 2025, surpassing the previous peak observed during the 2021 growth cycle. As of the end of June 2025, total market capitalisation stood at USD 3.5 trillion, slightly below the January high (CoinGecko, online-a). Since early 2023, Bitcoin’s share of the total market capitalisation has steadily increased, rising from around 38 percent in January 2023 to 62 percent in June 2025 (CoinGecko, online-a). This trend highlights Bitcoin’s enduring prominence within the broader crypto asset investment ecosystem. Part of the increase in total market value coincided with capital inflows into spot Bitcoin exchange-traded funds (ETFs). Introduced in the United States in early 2024, these products attracted significant investor interest, with assets under management reaching USD 136 billion for Bitcoin by end of June 2025 (CoinMarketCap, online-a), and USD 11 billion for Ether (CoinMarketCap, online-b). These figures correspond to approximately six percent and four percent of each asset’s total market capitalisation, respectively, highlighting the significant role that regulated investment vehicles are beginning to play in the crypto asset investment ecosystem. Developments in the area of crypto asset investments have also been observed in Switzerland and Liechtenstein in recent months. In addition to the overall expansion of crypto-related services and products offered by local financial institutions, this includes, for example, the licensing of BX Digital by the Swiss Financial Market Supervisory Authority (FINMA) as a first Distributed Ledger Technology (DLT) trading facility (FINMA, 2025). In terms of infrastructure, regulated trading venues and tokenisation platforms continued to expand their activities. For example, the SIX Digital Exchange (SDX) reached a cumulative volume of over CHF 1.6 billion in digital bond issuances by mid-2025 (SDX, 2025a). Additional tokenisation initiatives involving Swiss banks and financial infrastructure providers were launched or continued in 2025, particularly in the area of deposit tokens and asset-backed tokens. In Liechtenstein, the European Economic Area (EEA) MiCA Implementation Act entered into force on 1 February 2025, serving to pre-implement the EU Markets in Crypto-Assets Regulation (MiCAR) ahead of its formal incorporation into the EEA Agreement. This step underlines Liechtenstein’s proactive alignment with the EU regulatory framework for crypto assets (Financial Market Authority Liechtenstein, online). These developments appear to have increased the acceptance and adoption of crypto assets not only at the corporate level, but have also led to an increasing adoption of crypto assets among private individuals. According to a November 2024 study by the Lucerne University of Applied Sciences and Arts, approximately eleven percent of the Swiss population are invested in crypto assets through instruments such as cryptocurrencies, stablecoins, ETFs, exchange-traded notes (ETNs), non-fungible tokens (NFTs), and tokenised real-world assets. Notably, the study found that curiosity, return expectations, and diversification are the primary motivations for entering the crypto asset market, highlighting the growing potential for related financial services and product providers (Dietrich, Rey, & Amrein, 2024). 3Crypto Assets Study 2025 1.1. Definition of Crypto Assets The definition of the subject matter remains consistent with previous editions of the “Crypto Assets Study” and serves to delineate the scope of the analysis: bCrypto assets are digital representations, like claims, values, or rights, issued on a distributed ledger, such as a blockchain protocol, in the form of tokens. This definition includes all tokenised information recorded on a distributed ledger, irrespective of the degree of decentralisation or whether the system is public or private. This inclusive approach accommodates a wide range of designs and use cases. As detailed in the crypto asset taxonomy introduced by Ankenbrand, Bieri, Ferrazzini, et al. (2024), crypto assets can exhibit substantial diversity across multiple dimensions. For example, at the token level, they may serve different functions such as utility, governance, investment, or ownership, and can be native or non-native. At the protocol level, tokens are implemented on infrastructures with varying technical architectures, consensus mechanisms, and permissioning models. At the tokenomics level, design parameters such as decentralisation and supply mechanisms differ widely. These attributes are illustrative rather than exhaustive, and highlight the large diversity of crypto assets that all fall under the outlined definition. 1.2. Methodological Approach The methodological approach of this study remains consistent with the previous edition. Market activities are primarily analysed using structured desk research and publicly available data sources. This allows for a comprehensive and comparable assessment of crypto asset-related investment products and services offered in Switzerland and Liechtenstein. 1.2.1 Identification of Relevant Market Participants A multi-step screening process was conducted to identify companies offering crypto asset-related investment products and/or services. First, Swiss and Liechtenstein entities were selected based on public registers and databases, including those provided by FINMA and the Liechtenstein Financial Market Authority (FMA-LI). The sample included banks, securities firms, FinTech companies, asset managers, IT service providers, and other relevant actors. In a second step, each company was examined using general web search results and large language model support to determine its relevance to the crypto asset investment ecosystem. For positively identified entities, corporate websites were reviewed to extract general information about their activities, offerings, and target clients. 1.2.2 Classification Framework The structure of the investment ecosystem introduced in Chapter 2 served as the classification basis. Each company was mapped to one or more segments of the value chain, distinguishing between off-chain, on-chain centralised, and on-chain decentralised investment products and services. The resulting dataset was subjected to plausibility checks to improve accuracy and consistency. 1.2.3 Data Sources The analysis is based exclusively on publicly available or commercially licensed data. Key quantitative indicators and product-level data were obtained from the following sources: 1. Bloomberg 2. BX Swiss 3. CoinGecko 4. Google BigQuery 5. Morningstar Direct 6. Semrush 7. SIX 1.2.4 Scope and Limitations The findings are based solely on desk research and do not reflect confidential or unpublished business activity. It is important to note that the majority of the data providers referenced focus on publicly traded crypto assets. Consequently, investment activities involving private or permissioned DLT systems are not captured in this study. Furthermore, due to the partially scarce public information available and the use of large language models, the evaluation and classification of the in-scope companies follows the most probable categorisation in some cases. The results should therefore be interpreted as an informed approximation of observable developments in the crypto asset investment ecosystem of Switzerland and the Principality of Liechtenstein. Structure of the Investment Ecosystem for Crypto Assets 4 2. Structure of the Investment Ecosystem for Crypto Assets The structure of the crypto asset investment ecosystem broadly mirrors that of traditional financial markets, but with important distinctions. As shown by the vertical columns in Figure 2.1, the investment value chain includes the issuance of crypto assets and of financial instruments based on them, the participation of investors (both in the primary and secondary markets), the provision of investment services, the operation of trading venues, and posttrading activities. A key differentiating factor to the investment value chain of traditional assets is the degree to which blockchain-based systems are integrated into these processes. This technological dimension is illustrated by the horizontal layers in Figure 2.1, which distinguish between: •Off-chain: Traditional financial infrastructure without direct integration of DLT, covering indirect investments in crypto assets (e.g., exchange-traded products or structured products). Investors do not directly interact with blockchain-based systems. •Centralised on-chain: Services and products built on DLT that offer direct exposure to crypto assets, but are operated by identifiable intermediaries or regulated institutions that retain control over key processes. •Decentralised on-chain: Fully decentralised infrastructures that provide direct exposure to crypto assets, where activities are executed through smart contracts and user-controlled wallets, without reliance on centralised entities. The following sections provide an overview of the actors and functions along the investment value chain as presented in Figure 2.1. Note that the figure focuses on the core processes of investment. In addition to these, supporting infrastructure such as compliance services (e.g., Know Your Customer and Anti-Money Laundering) and market data providers are essential enablers of investor access and market integrity. Issuance Issuers initiate the creation of new crypto assets or indirect financial products based on them. For indirect products, the issuer is typically a regulated financial institution. Primary Market Secondary Market Technological Innovation Post-Trading Infrastructure Trading Infrastructure Investment Services Investors Issuers Off-Chain Centralised On-Chain Decentralised On-Chain Tokenisers Investment Product Providers Private Individuals/ Companies/ Institutionals Banks/ Asset Managers/ Brokers Centralised Crypto Exchanges Traditional Exchanges Custodians Decentralised Finance (DeFi) Decentralised Crypto Exchanges Crypto Wallets/ Smart Contracts Investment Protocols Centralised Crypto-Native Investment Protocols Miners/ Validators/ Decentralised Issuers Figure 2.1: Structure of the investment ecosystem for crypto assets 5Crypto Assets Study 2025 These instruments allow clients to gain exposure to crypto assets without requiring on-chain interaction, such as operating wallets or managing private keys, as these investment products can be booked directly into traditional securities accounts. Direct issuance of crypto assets occurs through the tokenisation of digital or real-world assets on a DLT network. Centralised issuers (e.g., regulated tokenisation platforms or stablecoin providers) generate these tokens while retaining operational control. In decentralised settings, issuance is embedded in protocol mechanisms. Here, two general categories of issuers exist: •Miners and validators: These actors receive newly created tokens as protocol rewards for producing and verifying blocks, thereby contributing to network consensus and security. This process can be understood as a form of issuance embedded in the protocol itself, where the generation of new tokens is tied to the operation and maintenance of the underlying blockchain infrastructure (Shrimali & Patel, 2022). •Decentralised issuers: These include individuals, decentralised autonomous organisations (DAOs), or other entities deploying smart contracts to create and distribute tokens via open, decentralised infrastructures. They operate without the need for platform-level permission or central coordination and represent a share of token issuance in decentralised finance and community-driven projects (U.S. Department of the Treasury, 2023). Investors Investors form the demand side of the ecosystem and are the final recipients of investment services and products. This study considers a range of investor types, including retail clients and institutional investors. As in earlier editions, business volume metrics are presented based on observable activity at the service provider level. However, due to the pseudonymous nature of most DLT-based systems and the limitations of available off-chain market data, it is difficult to attribute activity to specific investor categories. As a result, the analyses in Chapter 4 do not distinguish between investor types. A more detailed assessment of institutional investor exposure to crypto asset markets is provided in Chapter 6. Investment Services Investment services include the structuring, offering, and management of crypto asset exposures. These services may relate to off-chain investment products or direct crypto asset holdings. Providers such as banks, asset managers, and brokers typically operate across the off-chain and/or centralised on-chain domains, depending on their product offering. They support clients in accessing crypto asset markets either directly or indirectly. Within the centralised on-chain segment, crypto-native investment platforms have emerged that combine onchain infrastructure with centralised service models (S&P Global Ratings, 2023). These include, for example, CeFi lenders, staking-as-a-service providers, and portfolio platforms, which offer users simplified access to on-chain yield or crypto asset exposure, while retaining centralised control over execution and custody (Ethereum Foundation, 2025). In decentralised finance (DeFi), smart contract protocols replicate investment functions such as asset management, lending, and staking. These decentralised services allow users to manage their crypto asset positions without the involvement of intermediaries (Gogel, 2021). Trading Infrastructure Trading platforms facilitate the buying and selling of crypto assets and related financial instruments. Indirect investment products are typically traded on conventional exchanges and require no DLT interaction at the user level. Direct crypto asset trading takes place on either centralised or decentralised platforms. Centralised crypto exchanges (CEXs) operate order books and provide custodial services, resembling traditional trading venues. Decentralised exchanges (DEXs), in contrast, are built on smart contracts and execute trades via automated market maker protocols. They operate without intermediaries and rely on DLT-native mechanisms. Note that cross-chain bridges and interoperability protocols also play an important role in enabling trading and asset transfers between blockchain ecosystems. However, these services are not directly and exclusively related to investments and are therefore not discussed in more detail in this study. Structure of the Investment Ecosystem for Crypto Assets 6 Post-trading Infrastructure Custody and settlement conclude the investment value chain for crypto asset exposure. For off-chain investment products, post-trade functions are typically handled by custodians, such as banks or specialised financial institutions, which integrate these assets into traditional securities account structures. In the centralised on-chain segment, custodians also play a key role. These may include regulated crypto asset custodians or centralised exchanges that safeguard client assets by managing private keys and maintaining omnibus or segregated wallets under their control. In the decentralised on-chain setting, post-trade activities are carried out through crypto wallets and smart contracts. Users retain full control over their assets by managing private keys themselves or by interacting with protocol-based smart contracts that autonomously settle and hold assets.1 1For a comprehensive discussion of digital wallets, see Ankenbrand, Bieri, Gattlen, et al. (2024). 7Crypto Assets Study 2025 3. Overview of Providers of Crypto Asset-related Products and Services This chapter presents the results of an updated evaluation of the Swiss and Liechtenstein crypto asset investment ecosystem1, based on public web data and an AI-supported screening process using OpenAI’s GPT4o model (OpenAI, 2025). The goal is to provide an overview of companies with tangible business activities in the crypto asset investment space as of the end of June 2025. The identification and evaluation of relevant companies for this study followed a three-step process: 1. Compilation of the initial sample: Newly available company lists were consulted, including entities licensed by the FINMA and the FMA-LI, as well as DLT-related companies listed in FinTech directories. This resulted in a total sample of 1,053 companies. 2. Verification of activity status: All companies were reviewed using entries in the commercial registers of Switzerland and the Principality of Liechtenstein to assess whether they are active. As a result, 879 companies (83% of the total) were confirmed to be active and relevant for further analysis2. For these, a website check was conducted to ensure that they are operational and that relevant information could be retrieved through public sources. 3. Assessment of crypto asset investment relevance: All companies were evaluated using a combination of public web data and OpenAI’s GPT-4o model to determine their involvement in the crypto asset investment ecosystem. Based on this analysis and subsequent manual plausibility checks and adjustments, a core sample of 407 companies (39% of the total) with tangible business activities and projects in the crypto asset investment domain was identified. 1Note that in certain statements and analyses that follow, the Principality of Liechtenstein is referenced alongside Swiss cantons, or the two countries are considered collectively. This is done to increase the significance, although it is clear that Switzerland and the Principality of Liechtenstein are distinct markets. 2In contrast to last year, companies with legal entities in both Switzerland and the Principality of Liechtenstein were assigned only to the country in which their headquarters are located. For this core sample, the following paragraphs provide an analysis of regional distribution, targeted customer segments, and product and service offerings. The classification of companies follows the ecosystem structure introduced in Chapter 2. 0% 10% 20% 30% 40% 50% ZG ZH LI GE TI VD SZ BE NE AG SG LU BS TG GR AR SO SH OW JU VS UR Proportion of companies Figure 3.1: Headquarters of examined companies (n=407) Figure 3.1 illustrates the regional distribution of the companies in the Swiss and Liechtenstein crypto asset investment ecosystem. It reveals that the cantons of Zug (ZG) and Zurich (ZH) are the most strongly represented, with 40 and 22 percent of all companies, respectively. The Principality of Liechtenstein (LI) and Geneva (GE) follow with ten and nine percent, respectively. Smaller clusters of companies involved in crypto asset-related investment products and services are located in Ticino (TI), Vaud (VD), and Schwyz (SZ) with three percent each, and Bern (BE) with two percent. This distribution highlights a strong concentration of crypto asset investment companies in the cantons of Zurich and Zug. Figure 3.2 presents the customer segments targeted by companies in the Swiss and Liechtenstein crypto asset investment ecosystem. Among the 407 companies analysed, 37 percent operate exclusively in the business-tobusiness (B2B) segment, serving banks, corporates, family offices, and other institutional clients. Another 53 percent address both B2B and business-to-consumer (B2C) segments, while ten percent focus solely on B2C, targeting retail or private clients. Overview of Providers of Crypto Asset-related Products and Services 8 B2B B2B & B2C B2C Total Liechtenstein 15 (4%) 20 (5%) 5 (1%) 40 (10%) Switzerland 135 (33%) 195 (48%) 37 (9%) 367 (90%) Total 150 (37%) 215 (53%) 42 (10%) 407 (100%) Figure 3.2: Customer segments of examined companies (n=407) Within the B2B segment, companies serve a diverse range of client types. 78 percent serve corporates, and 81 percent address other institutional clients. The latter group excludes family offices and banks but includes pension funds, insurance companies, foundations, and other organisations with substantial capital and professional investment capabilities. Additionally, 39 percent of companies serve banks, while 27 percent focus on family offices. Proportion of companies 4% 47% 6% 14% 17% 16% 18% 19% 16% 9% 9% 12% 0% 20% 40% 60% 80% Issuance Investment Services Trading Infrastructure Post-Trading Infrastructure On-Chain Decentralised Investments On-Chain Centralised Investments Off-Chain Indirect Investments Figure 3.3: Service offerings of examined companies (n=407, multiple classifications possible) Figure 3.3 provides an overview of the product and service offerings of companies in the Swiss and Liechtenstein crypto asset investment ecosystem, categorised into the service types Issuance,Investment services,Trading infrastructure, and Post-trading infrastructure. The percentages represent the proportion of companies offering products or services within each category, further broken down by whether the services are delivered off-chain, via onchain centralised systems, or via on-chain decentralised systems. Issuance services are most commonly found in the context of on-chain centralised investments, where they are offered by 17 percent of companies. In the decentralised space, 16 percent of companies provide issuance-related services, such as token launches on decentralised platforms. Issuance plays a smaller role in the off-chain indirect segment, where only four percent of companies are active in this area, issuing, for example, structured products on crypto assets. Investment services are most prominently offered for offchain indirect products, with 47 percent of companies offering such services. In comparison, 16 percent of companies provide investment services for direct investments via centralised channels, while nine percent are active in offering decentralised investment solutions. Trading infrastructure services, such as conversions between fiat and crypto assets or between different crypto assets, are provided across all categories with varying degrees of prevalence. They are most common in the onchain centralised segment, where 18 percent of companies enable clients to trade crypto assets. In the off-chain indirect category, exchange services are offered by six percent of companies. Nine percent of companies are active in the decentralised exchange space. Post-trading infrastructure services, i.e., custody, are most commonly offered in the context of on-chain centralised investments, provided by 19 percent of companies. In the off-chain indirect category, 14 percent of companies offer such services, typically focusing on the safekeeping of indirect products on crypto assets. Self-custody solutions, which allow clients to manage their own keys and assets independently, are available from twelve percent of companies operating in the on-chain decentralised space. In summary, it becomes clear that the companies associated with the crypto asset investment ecosystem are concentrated in the cantons of Zurich and Zug. Combined B2B and B2C business models and pure B2B business models dominate, whereas pure B2C business models are less common. The range of services is broad, with investment offerings being the most prevalent, particularly in the field of off-chain indirect investments. 15 Crypto Assets Study 2025 0 5 10 15 20 25 30 35 40 45 50 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 2019 2019 2020 2020 2021 2021 2022 2022 2023 2023 2024 2024 2025 CHF (in thousands) Average trade size ETP Structured Products 0 10 20 30 40 50 60 Nov 18 Feb 19 May 19 Aug 19 Nov 19 Feb 20 May 20 Aug 20 Nov 20 Feb 21 May 21 Aug 21 Nov 21 Feb 22 May 22 Aug 22 Nov 22 Feb 23 May 23 Aug 23 Nov 23 Feb 24 May 24 Aug 24 Nov 24 Feb 25 May 25 In thousands Market trades ETP Structured Products Figure 4.8: Monthly number of market trades (left-hand graph) and half-yearly average trade size (right-hand graph) (sources: SIX) shows the proportional distribution of trading turnover by currency over time, highlighting the dominance of certain currencies in the Swiss exchange landscape for crypto asset investments. 0% 20% 40% 60% 80% 100% H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 2019 2019 2020 2020 2021 2021 2022 2022 2023 2023 2024 2024 2025 USD CHF EUR GBP JPY Figure 4.9: Half-yearly proportions of turnover by currency (sources: SIX) Figure 4.9 shows that USD-denominated products have consistently dominated trading turnover in the Swiss crypto asset-related product market. From 2019 to the first half of 2025, USD has accounted for the majority of trading volume each year, representing 77 to 89 percent of total turnover. In the first half of 2025, USDdenominated products made up approximately 77 percent of total volume, underscoring the continued central role of USD in the Swiss crypto asset investment ecosystem. CHF-denominated products have grown in significance in more recent years. While they accounted for only around 13 percent of turnover in 2019, their share increased to over 16 percent in the first half of 2025. This rise suggests a steady demand for francdenominated instruments. Products denominated in euro, British pound, and Japanese yen account for comparatively smaller shares of trading turnover. In the first half of 2025, they represented 5.9 percent, 0.35 percent, and 0.02 percent of turnover, respectively. 4.1.2 Derivatives Crypto Exchanges Another form of indirect exposure to crypto assets involves trading derivatives on specialised crypto exchanges. Unlike tokenised assets on DLTs, these derivatives are proprietary financial instruments offered by individual exchanges. As they cannot be withdrawn to personal wallets, they do not confer on-chain ownership of the underlying asset and are therefore considered indirect investments. Derivatives crypto exchanges offer a range of products beyond spot trading, including futures contracts, allowing investors to speculate or hedge on the future price of crypto assets. The monthly derivatives trading volume on derivatives crypto exchanges originating from Switzerland are analysed for the period from January 2020 to end of June 2025. To collect the data, the following steps are applied: Overview of Market Activities 16 1. Obtain monthly global trading volumes for all crypto exchanges from CoinGecko (online-b) API. 2. Identify the top 20 exchanges by total trading volume for each month, considering only those with a trust score greater than five out of ten to ensure reliability and liquidity. 3. Obtain the monthly proportions of total website traffic from Switzerland for the identified exchanges from Semrush (online). Note that VPN use and cross-border access may distort the measured share of Swiss traffic. 4. Estimate the monthly trading volume from Switzerland by multiplying the exchange’s global trading volume by the Swiss traffic share. 5. Aggregate the monthly Swiss trading volumes for each in-scope exchange over the sample period to determine the total monthly trading volume of Swiss users. 0 10 20 30 40 50 Jan 20 Mar 20 May 20 Jul 20 Sep 20 Nov 20 Jan 21 Mar 21 May 21 Jul 21 Sep 21 Nov 21 Jan 22 Mar 22 May 22 Jul 22 Sep 22 Nov 22 Jan 23 Mar 23 May 23 Jul 23 Sep 23 Nov 23 Jan 24 Mar 24 May 24 Jul 24 Sep 24 Nov 24 Jan 25 Mar 25 May 25 In CHF billion Figure 4.10: Monthly derivatives trading volume on derivatives crypto exchanges from Switzerland (source: CoinGecko (online-b), Semrush (online)) Figure 4.10 shows the trading volumes on derivatives crypto exchanges originating from Switzerland, showing relatively low activity throughout 2020. Trading activity peaked notably in May 2021 at CHF 28.6 billion, after which volumes began a downward trajectory that persisted into early 2022. Between 2022 and the end of the third quarter of 2023, market volumes remained relatively stable, exhibiting limited fluctuation. A shift occurred in the fourth quarter of 2023, marking the onset of a recovery that continued with a clear upward trend from January through March 2024. In the past twelve months, trading volumes on derivatives crypto exchanges from Switzerland saw a significant surge, followed by a correction. In June 2025, Swiss investors traded approximately CHF 20 billion on derivatives crypto exchanges. Between July 2024 and June 2025, BitMart, XT.COM, and Binance were the most popular crypto derivatives exchanges among Swiss investors, based on the total derivative trading volumes originating from Switzerland. 4.2. Direct Investments Building on the previous analysis of market metrics for indirect crypto investments via traditional exchanges and derivatives crypto exchanges, this section turns to direct investments in crypto assets. Direct investment refers to purchasing and holding crypto assets in a manner that enables direct ownership on a blockchain, typically through an exchange that allows withdrawals to a personal wallet. For direct investments, this study distinguishes between two types of exchanges, i.e., centralised (Section 4.2.1) and decentralised (Section 4.2.2) exchanges. In particular, trading activity related to direct investment is estimated, with a focus on Switzerland, and Section 4.2.3 presents a comparison of trading volumes for centralised, decentralised, and derivatives crypto exchanges. The data analysed covers the period from January 2020 to end of June 2025, and data collection follows the same approach as outlined in Section 4.1.2. 4.2.1 Centralised Crypto Exchanges Centralised crypto exchanges (CEXs) are digital platforms that enable the trading and, optionally, the custody of crypto assets. Functioning as intermediaries, these exchanges connect buyers and sellers, thereby facilitating the execution of spot market transactions. Modelled largely on traditional financial exchanges, CEXs typically employ order book systems and algorithmic matching engines. Many such platforms also offer custodial services, which relieve users of the responsibility of managing private wallets and interacting directly with blockchain infrastructure. While this convenience reduces the technical barriers for users, it introduces counterparty risk, as control over private keys is transferred to the exchange. Furthermore, several CEXs support fiat onand off-ramp functionalities, allowing for the seamless conversion between fiat currencies and crypto assets. 17 Crypto Assets Study 2025 Figure 4.11 shows monthly trading volumes on CEXs originating from Switzerland. Volumes rose sharply in early 2021, peaking in May at over CHF 17.8 billion, an all-time high. However, after mid-2021, there was a steady decline in volume until September 2023. A notable resurgence in volume was observed in late-2023 to mid-2024. 0 4 8 12 16 20 Jan 20 Mar 20 May 20 Jul 20 Sep 20 Nov 20 Jan 21 Mar 21 May 21 Jul 21 Sep 21 Nov 21 Jan 22 Mar 22 May 22 Jul 22 Sep 22 Nov 22 Jan 23 Mar 23 May 23 Jul 23 Sep 23 Nov 23 Jan 24 Mar 24 May 24 Jul 24 Sep 24 Nov 24 Jan 25 Mar 25 May 25 In CHF billion Figure 4.11: Monthly spot trading volume on centralised crypto exchanges from Switzerland (source: CoinGecko (online-b), Semrush (online)) Between May 2024 and June 2025, trading volumes exhibited substantial monthly fluctuations. The period began with relatively stable volumes between CHF 3.4 billion and CHF 4.7 billion, followed by a significant surge (around 150%) starting in November 2024. The volume peaked in December 2024 at over CHF 10 billion, indicating intensified trading activity. However, this peak was followed by a steady decline, with volumes falling to approximately CHF 3 billion by May 2025, suggesting a return to more moderate trading behaviour or reduced investor engagement. Based on aggregated trading volume data between July 2024 and June 2025, the top three CEXs by Swiss trading volumes were Binance, Crypto.com, and Pionex. In comparison to the Swiss CEX volumes reported in last year’s edition of the “Crypto Assets Study”, some slight differences in the aggregated monthly volumes are apparent. This is mainly due to the removal of some exchanges from the Coingecko API that were available for the previous study. 4.2.2 Decentralised Crypto Exchanges Decentralised crypto exchanges (DEXs) are digital platforms that enable peer-to-peer trading of crypto assets without the involvement of centralised intermediaries. In contrast to CEXs, DEXs are built directly on blockchain protocols and rely on smart contracts to facilitate direct transactions between users. As a result, users of DEXs retain full control over their assets and are individually responsible for the management of their private keys through selfcustodial wallets. Figure 4.12 shows the monthly trading volume on DEXs originating from Switzerland. Two peaks in trading volumes during 2021 can be observed, reaching around CHF 1.2 billion and coinciding with periods of heightened DeFi activity globally. Volumes then gradually decreased, reaching the minimum value in September 2023 with just CHF 0.04 billion. 0 0.4 0.8 1.2 1.6 Jan 20 Mar 20 May 20 Jul 20 Sep 20 Nov 20 Jan 21 Mar 21 May 21 Jul 21 Sep 21 Nov 21 Jan 22 Mar 22 May 22 Jul 22 Sep 22 Nov 22 Jan 23 Mar 23 May 23 Jul 23 Sep 23 Nov 23 Jan 24 Mar 24 May 24 Jul 24 Sep 24 Nov 24 Jan 25 Mar 25 May 25 In CHF billion Figure 4.12: Monthly spot trading volume on decentralised crypto exchanges from Switzerland (source: CoinGecko (online-b), Semrush (online)) Since last year’s edition of the “Crypto Assets Study”, DEX trading volumes originating from Switzerland experienced a substantial surge followed by a partial correction. The period began with moderate volumes in June 2024 (CHF 0.54 billion), followed by a gradual increase through October 2024. A significant surge occurred in November and December 2024, where monthly trading volumes reached approximately CHF 1.5 billion, respectively, the highest recorded during the observed period. This represents an increase of approximately 83 percent from October to November. However, following the December peak, volumes began to gradually decline. By June 2025, the trad- Overview of Market Activities 18 ing volume had fallen to approximately CHF 0.26 billion, suggesting a cooling-off phase after the intense trading activity of the previous months. Between July 2024 and June 2025, the top three DEXs by Swiss trading volumes were Aerodrome Slipstream, Pancakeswap, and Raydium. 4.2.3 Exchange Type Comparison Since the methodology for estimating Swiss trading volumes is identical across CEXs, DEXs, and derivatives crypto exchanges, their results are directly comparable. While this section focuses on direct investments, the analysis also includes derivatives crypto exchanges to provide a comprehensive view of trading activity across all major crypto exchange types. In the first half of 2025, the trading volumes from Switzerland across the three exchange types showed varied trends, with shifts in the overall market dynamics compared to the previous year. While CEXs experienced a slight decline in Swiss trading volume when comparing the first half of 2024 to the first half of 2025, DEXs saw considerable growth. In contrast, derivatives exchanges continued to attract substantial volume, maintaining their prominence in the Swiss market. Table 4.1 presents a comparison of the global trading volumes, Swiss traffic shares, estimated Swiss trading volumes, and Swiss trading volume per capita for the first half of 2025. Derivatives crypto exchanges reported the largest global trading volume in the first half of 2025, with CHF 99,200 billion. CEXs followed with CHF 14,503 billion, and DEXs recorded CHF 1,144 billion. The typically higher trading volumes on derivatives crypto exchanges, compared to CEXs and DEXs, can be attributed to factors such as the ability to leverage and short-sell, as well as the diverse 8Swiss population data was obtained from the Federal Statistical Office (2025) and refers to the end of the first quarter of 2025. payoff structures that derivatives offer. Additionally, the lower volumes on DEXs compared to CEXs are often due to lower liquidity, higher technological complexity, potential smart contract risks, and the involvement of blockchain in every transaction, which can result in higher transaction fees and longer settlement times. When examining website traffic from Switzerland in the first half of 2025, DEXs held the largest share (0.44%), followed by CEXs (0.20%) and derivatives exchanges (0.14%). Swiss trading volumes are estimated by multiplying the global trading volume of each exchange with its web traffic share from Switzerland. In the first half of 2025, derivatives crypto exchanges accounted for CHF 141.0 billion, CEXs for CHF 28.7 billion, and DEXs for CHF 5.0 billion in Swiss trading volumes. These differences are also evident on a per capita basis, with the average Swiss investor trading CHF 15,548 on derivatives crypto exchanges, CHF 3,170 on CEXs, and CHF 554 on DEXs. It is important to note that, while these figures are based on the Swiss population, institutional investors from Switzerland likely play a role in the trading volumes as well. 4.3. Tokenisation Switzerland has developed a comprehensive legal and regulatory framework for asset tokenisation, a process that enables the issuance of crypto assets on-chain and thereby facilitates direct investment. Since 2018, the Swiss Financial Market Supervisory Authority (FINMA) has classified “asset tokens” as securities, providing a legal basis for Security Token Offerings (STOs) (Stefanoski & Sahin, 2021). Rather than introducing standalone legislation, Swiss regulators integrated DLT into existing financial market laws (Maerki Baumann, online). The Federal DLT Act, which came into full effect in August 2021, introduced ledger-based securities, i.e., uncerTable 4.1: Trading volume comparison across different crypto exchange types in the first half-year of 2025 Centralised exchanges Decentralised exchanges Derivatives exchanges Global volume CHF 14,503 bn CHF 1,144 bn CHF 99,200 bn Swiss traffic share 0.20% 0.44% 0.14% Swiss volume CHF 28.7 bn CHF 5.0 bn CHF 141.0 bn Swiss volume per capita8CHF 3,170 CHF 554 CHF 15,548 19 Crypto Assets Study 2025 tificated securities recorded directly on a blockchain, and a new regulatory licence for DLT-based trading facilities (PwC, online). Several Swiss start-ups and regulated entities have issued tokenised equity. As of the beginning of July 2025, TokenMarketCap (online) listed a total of 102 asset tokens issued in Switzerland. Of these, 31 are actively traded, representing an aggregate valuation of approximately CHF 590 million, while the remaining tokens are either not traded or available only on request. This indicates that although tokenisation activity is ongoing, secondary market liquidity remains limited, with fewer than one-third of asset tokens being traded. While most early tokenisation efforts in Switzerland have focused on equity instruments, developments in the debt market have also gained momentum. The launch of the SIX Digital Exchange (SDX) in 2021 (SIX, 2021) marked a significant milestone in this area, enabling the issuance of native digital bonds within a fully regulated infrastructure. As of July 2025, SDX has listed eleven digital bonds with a total volume of over CHF 1.6 billion (SDX, 2025a). In 2025, Citi announced a strategic collaboration with SDX to serve as custodian and tokenisation agent for latestage pre-IPO equities via SDX’s regulated digital central securities depositary platform. The initiative, expected to launch in the third quarter of 2025, aims to enhance institutional access to private market assets and provide issuers with a compliant model for managing liquidity and cap tables, further signalling institutional interest in regulated tokenised financial instruments (SDX, 2025b). In parallel to developments at SDX, Switzerland’s digital asset infrastructure is expanding with the emergence of additional regulated venues. A notable example is the launch of BX Digital, which became the first financial market infrastructure in Switzerland to receive authorisation from FINMA to operate as a dedicated DLT trading facility (FINMA, 2025). Once operational, BX Digital will provide regulated trading and decentralised settlement of crypto assets on a public blockchain (i.e., Ethereum), without intermediaries such as central securities depositories. It is designed to support the trading of tokenised shares, bonds, and funds among institutional participants, enabling fast and secure delivery-versus-payment settlement via a direct link to the Swiss National Bank’s payment system (BX Digital, online). The expansion of tokenised securities and DLT-based trading facilities has highlighted the potential need for reliable, blockchain-native settlement assets denominated in Swiss francs. In this context, CHF-based stablecoins could form a critical component in enabling delivery-versuspayment on both public and permissioned blockchains, serving as the cash leg in tokenised transactions and supporting private as well as institutional use cases in Switzerland’s evolving crypto asset ecosystem. 0 50 100 150 200 250 Jan 19 May 19 Sep 19 Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 May 23 Sep 23 Jan 24 May 24 Sep 24 Jan 25 May 25 USD (in billions) Figure 4.13: Monthly total USD value of stablecoins in circulation (source: Visa & Allium Labs (online-b)) Hence, while tokenisation infrastructure for equities and bonds continues to mature in Switzerland, the role of blockchain-native payment instruments is receiving increased attention. The global market capitalisation across all fiat-referenced stablecoins, as illustrated in Figure 4.13, has grown substantially in recent years, rising from under USD 1 billion in early 2019 to approximately USD 231 billion by mid-2025, with U.S. dollar-denominated tokens such as Tether (USDT) and USD Coin (USDC) accounting for the majority of volume and circulation (Visa & Allium Labs, online-a). In contrast, stablecoins linked to other currencies represent a relatively small share of the market and are used in more limited contexts. CHF-based stablecoins have historically seen limited traction as on-chain settlement mechanisms. This is exemplified by the termination of Bitcoin Suisse’s CryptoFranc (XCHF), whose issuance and redemption were officially discontinued in August 2024 (Bitcoin Suisse, online). A more recent initiative is Frankencoin, a decentralised CHF-denominated stablecoin launched on Ethereum. Governed by a DAO and backed by overcollateralised assets, it allows users to mint tokens independently of traditional intermediaries. As of the beginning of July 2025, the total supply exceeded Overview of Market Activities 20 10.5 million ZCHF, backed by collateral worth over 23.4 million ZCHF (Frankencoin, online). Furthermore, the concept of tokenised deposits, blockchain representations of bank-held liabilities, is gaining interest as a potentially more regulated and bank-integrated alternative (Swiss Bankers Association, 2024). As highlighted in the report by the Swiss Bankers Association (2025), such instruments could offer the technological advantages of stablecoins while preserving the two-tier banking system and reducing risks of disintermediation. Unlike decentralised models, tokenised deposits would be issued by supervised institutions and fully backed by central bank reserves or sight deposits, providing a higher degree of legal certainty and integration into existing financial infrastructure. The Swiss Bankers Association stresses that a stablecoin ecosystem anchored in the Swiss franc and embedded within the domestic regulatory framework is essential to ensure monetary sovereignty and systemic stability (Swiss Bankers Association, 2025). 4.4. Summary In conclusion, the market for crypto asset investments in Switzerland and Liechtenstein has experienced growth in recent years, both in the realm of indirect and direct investments. Indirect investments through products such as ETPs and open-end funds demonstrate continuous expansion, reflected in the increasing number of available products and a steady rise in AuM, even when adjusted for the price effects of underlying crypto assets. The area of direct investments is also experiencing growth, with notable trading volumes on CEXs and derivatives crypto exchanges. However, CEXs have seen a decline in volume compared to the previous year. Furthermore, the tokenisation of assets, supported by Switzerland’s established regulatory infrastructure, is gaining importance and opening new opportunities for the issuance and trading of DLT-based securities. This infrastructure development is shaped not only by growing investor demand but also by the steady increase in regulatory clarity and the broader institutional acceptance. 21 Crypto Assets Study 2025 5. Crypto Assets as an Investment With the continued rise in market capitalisation of Bitcoin and other crypto assets, the question of their role within a traditional investment portfolio has gained increasing relevance. In this year’s edition of the study, we introduce two additional methodological enhancements to deepen the analysis of Bitcoin’s potential as an investment. First, we include gold as an additional asset in our analysis. This extension reflects the frequent comparison between Bitcoin and gold, particularly with regard to their perceived role as “safe haven” assets. By explicitly incorporating gold, we aim to assess whether Bitcoin demonstrates similar characteristics in a portfolio context. Second, we apply a simple linear regression model to estimate Bitcoin’s beta in relation to traditional asset classes. Specifically, we distinguish between upside beta and downside beta, depending on whether the respective market proxy exhibits positive or negative returns. This approach enables us to assess whether Bitcoin’s sensitivity to market movements differs under positive versus negative return conditions. The resulting beta coefficients, calculated with respect to equities, bonds, real estate, and gold, offer a more granular understanding of Bitcoin’s asymmetric risk behaviour. The following analysis is based on a simplified modelling framework and relies on general assumptions regarding the crypto asset market, the typical investment universe of traditional Swiss investors, their strategic asset allocation, and the selected observation period. The core assumptions are as follows: 1. The crypto asset market is proxied by Bitcoin (denominated in CHF), given its dominant share of total market capitalisation in recent years (CoinGecko, online-a), as shown in Figure 5.1. After declining to below 40 percent in early 2022, Bitcoin’s dominance increased steadily, reaching 62 percent by the end of June 2025. This upward trend underscores Bitcoin’s central role in the crypto asset ecosystem. Accordingly, using Bitcoin as a proxy for the broader crypto asset market offers a meaningful and robust representation of overall market dynamics throughout the analysis period. Price data for Bitcoin was obtained from finanzen.net (online). 2. The reference portfolio of a traditional investor is based on the strategic allocation of Swiss pension funds, as reported by the “Occupational Pension Supervisory Commission (OPSC)”, and serves as the benchmark.1 3. The four asset classes included in the analysis, i.e., stocks, bonds, real estate, and gold, are proxied by the Swiss Performance Index®(SPI), the Swiss Bond Index®TR (SBI), the CH Real Estate®Shares TR (SXI), and the spot price of gold in CHF, respectively. Data for the traditional indices were sourced from SIX (online-a) and gold price data was retrieved from Bloomberg L.P. (2025). 4. The observation period spans from the beginning of 2018 to the end of June 2025. This starting point coincides with the broader availability of indirect crypto asset investment products, thereby facilitating access for traditional investors (see Chapter 4). Business days are used as the frequency, to match the trading calendars of conventional asset classes. 0% 25% 50% 75% 100% Jan 2018 May 2018 Sep 2018 Jan 2019 May 2019 Sep 2019 Jan 2020 May 2020 Sep 2020 Jan 2021 May 2021 Sep 2021 Jan 2022 May 2022 Sep 2022 Jan 2023 May 2023 Sep 2023 Jan 2024 May 2024 Sep 2024 Jan 2025 May 2025 Figure 5.1: Bitcoin dominance (source: CoinGecko (online-a)) Building on these methodological foundations, the subsequent section investigates Bitcoin’s return sensitivity with respect to traditional asset classes by estimating its beta coefficients. In particular, the analysis distinguishes between upside and downside betas to capture potential asymmetries in Bitcoin’s behaviour under differing market conditions. This approach allows for a more differenti1In this analysis, traditional alternative investments are excluded from the investment universe. Crypto Assets as an Investment 22 ated understanding of Bitcoin’s return dynamics and risk exposure across varying market states. The beta analysis thus serves as a critical precursor to the portfolio-level assessment that follows, providing empirical insights into the extent and direction of Bitcoin’s co-movement with conventional assets. Formally, the analysis is based on a series of simple linear regressions of the form rBTC,t −rf,t =α+β·(rm,t −rf,t) + εt, where rBTC,t denotes the return of Bitcoin at time t,rm,t the return of the respective market proxy (i.e., SPI, SBI, SXI, or gold), and rf,t the daily risk-free rate2. To examine potential asymmetries in market sensitivity, separate regressions are conducted for periods in which (rm,t − rf,t)>0(upside beta) and (rm,t −rf,t)<0(downside beta). This decomposition allows us to assess whether Bitcoin exhibits different sensitivities during periods of positive versus negative market excess returns. All regressions are estimated using heteroskedasticity-consistent standard errors (Long & Ervin, 2000) to ensure robust inference. 2Throughout this chapter, the daily risk-free rate is proxied by the yield of the 10-year Swiss government bond. The corresponding data is obtained from the Swiss National Bank (online). The results of the regression analysis are summarised in Figure 5.2, which displays the estimated beta coefficients3 of Bitcoin with respect to each traditional asset class under up-market, down-market, and overall conditions. The analysis reveals a statistically significant relationship between Bitcoin and the stock market (SPI) across all three regimes. Specifically, Bitcoin exhibits an overall beta of 0.82 (p= 0.0003) with respect to the SPI, indicating a positive and economically meaningful sensitivity to equity market movements. Notably, the beta is higher during down markets (1.29,p= 0.025) than in up markets (0.78, p= 0.0046), suggesting asymmetric risk exposure and greater co-movement during periods of negative equity returns. These magnitudes imply that a one percent decline in the SPI is associated with an average 1.29 percent decline in Bitcoin’s excess return, underscoring Bitcoin’s vulnerability to broader equity market stress. Conversely, during up markets, a one percent increase in the SPI corresponds to an average increase of 0.78 percent in Bitcoin’s excess return, indicating that Bitcoin tends to benefit from rising equity prices, albeit to a lesser extent than it reacts during downturns. In contrast, the estimated betas with respect to bonds (SBI) are not statistically significant in any regime, indi3Asterisks indicate statistical significance: *** p < 0.01, ** p < 0.05, *p < 0.10. Figure 5.2: Estimated beta coefficients of Bitcoin with respect to traditional asset classes under up-market, down-market, and overall conditions 23 Crypto Assets Study 2025 cating that Bitcoin does not exhibit a meaningful linear relationship with bond market excess returns over the sample period. This is the case even though some coefficients are relatively large, because the underlying relationship is noisy, leading to large standard errors that make it difficult to distinguish these estimates from zero in a statistical sense. For real estate (SXI), only the overall beta is statistically significant (0.49,p= 0.030), while both upside and downside betas remain insignificant, implying moderate co-movement on average, but no strong directional dependence. The analysis further reveals a strong and statistically significant relationship between Bitcoin and gold in up markets (0.81,p= 0.0013) and over the full sample (0.55, p= 0.0004), whereas the beta during down markets is smaller and statistically insignificant (0.40,p= 0.325). This asymmetry suggests that Bitcoin and gold tend to comove primarily during periods of rising gold prices, potentially reflecting similar investor behaviour during risk-on phases. The magnitude of these betas further indicates that Bitcoin responds to gold price movements with a sensitivity comparable to its response to equities in up-market environments. Overall, these findings highlight that Bitcoin’s return dynamics are most closely tied to stocks and gold, with varying sensitivities depending on market conditions. These findings indicate that Bitcoin’s return dynamics are systematically linked to broader financial markets, albeit in an asymmetric fashion. As such, a subsequent portfoliolevel investigation is warranted to evaluate whether Bitcoin can enhance risk-adjusted performance when integrated into a traditional asset allocation framework. To explore this potential, four distinct portfolio allocations that reflect different approaches to diversification within a traditional investment framework are constructed and compared. As shown in Table 5.1, the first portfolio serves as a baseline and includes only the conventional asset classes bonds, stocks, and real estate, weighted based on the strategic allocation of Swiss pension funds. The second and third portfolios introduce a small allocation (3%) to either Bitcoin or gold, respectively, allowing for a direct comparison of their diversification potential, as alternative assets often regarded as stores of value. The fourth portfolio combines both Bitcoin and gold, each at a three percent allocation, resulting in a dual-alternative structure. In all adjusted portfolios, the weights of the traditional asset classes are proportionally reduced to accommodate the new components. This setup enables a comprehensive evaluation of how Bitcoin, gold, and their combination influence overall portfolio performance, volatility, and risk-adjusted return metrics. To evaluate the in-sample performance of the four portfolios, their cumulative returns and maximum drawdowns are analysed. Daily portfolio returns are calculated with annual rebalancing, and the analysis covers the period from January 2018 to June 2025. The visualisation in Figure 5.3 summarises the performance of each portfolio, showing how the inclusion of Bitcoin and/or gold affects both return dynamics and downside risk over time. The results show that the inclusion of Bitcoin leads to a higher cumulative return compared to both the gold-inclusive and baseline portfolios. Specifically, the Bitcoin-inclusive portfolio achieves a cumulative return of 48.8 percent, outperforming the gold-inclusive portfolio (32.2%) and the portfolio without either alternative asset (30.3%). The portfolio that includes both Bitcoin and gold generates the highest cumulative return at 51.0 percent, suggesting a potential complementary effect of the two assets when combined. In terms of downside risk, the Bitcoin-inclusive portfolio experiences the deepest maximum drawdown at -19.8 percent, followed closely by the portfolio with both Bitcoin and gold at -19.3 percent. These are slightly more severe than the drawdowns of the baseline portfolio (-18.2%) Table 5.1: Asset allocations considered Portfolios Bonds Stocks Real Estate Gold Bitcoin Portfolio excluding BTC & Gold 40% 35% 25% 0% 0% Portfolio including BTC 39% 34% 24% 0% 3% Portfolio including Gold 39% 34% 24% 3% 0% Portfolio including BTC & Gold 38% 33% 23% 3% 3% Crypto Assets as an Investment 24 Figure 5.3: Portfolio performances of the four asset allocations and the gold-inclusive portfolio (-17.6%), highlighting the increased short-term volatility introduced by Bitcoin. By the end of June 2025, however, all four portfolios exhibit relatively modest drawdowns of approximately -1.9 percent, indicating that they had largely recovered from earlier market stress episodes. Notably, the drawdown of the combined Bitcoin and gold portfolio at that point is comparable to that of the other portfolios, suggesting that the inclusion of gold helped mitigate some of the interim volatility introduced by Bitcoin. As a result, this portfolio ended the period in a similarly resilient state, despite its higher return profile. A more detailed view of portfolio performance over time is provided in Table 5.2, which reports annualised returns, volatility, and Sharpe ratios across the full sample period, each calendar year, and the first half of 2025. Over the full period, the portfolio including both Bitcoin and gold achieves the highest annualised return (5.7%) and the highest Sharpe ratio (0.77), while keeping volatility slightly below that of the Bitcoin-only portfolio (7.3% vs. 7.4%). The Bitcoin-inclusive portfolio delivers a similar return (5.5%) but comes with the highest volatility and a slightly lower Sharpe ratio (0.72). In contrast, the goldinclusive and baseline portfolios offer more modest returns of 3.8 percent and 3.6 percent, respectively, along with slightly lower volatility (6.6% and 6.7%, respectively) and lower risk-adjusted performance in general. While the higher volatility introduced by Bitcoin affects year-to-year Sharpe ratios, the inclusion of gold appears to mitigate some of this risk, leading to improved stability in the dual-asset portfolio. In the most recent period, i.e., first half of 2025, all four portfolios display broadly similar returns and Sharpe ratios, indicating a degree of convergence in performance. However, notable differences persist across earlier years, especially in return levels and risk-adjusted outcomes. This highlights that Bitcoin’s impact on portfolio performance has been time-dependent, but not necessarily detrimental to short-term stability in the most recent phase. It remains to be seen whether the convergence in portfolio performance observed in the first 31 Crypto Assets Study 2025 rotate addresses for privacy reasons, which complicates the identification and tracking of large holders over time. Third, comprehensive and scalable data access for Bitcoin is more limited in public platforms like Google BigQuery, whereas Ethereum offers more structured and readily accessible datasets. The process for collecting Ethereum balance data involves the following steps: 1. Construct a double-entry ledger of Ethereum addresses by aggregating inflows and outflows from transactions and gas fees. Outgoing transactions incur gas costs, which are deducted from the sender’s balance in addition to the transferred amount. 2. Include only successful transactions, as indicated by a transaction status. 3. Compute daily net balance changes per address and calculate cumulative balances using window functions. 4. Retain addresses holding at least 20 Ether on a given day, as this threshold approximates accounts with a minimum of USD 100,000 in holdings based on Ethereum’s historical all-time-high price, thereby focusing the analysis on large holders potentially indicative of institutional activity. 5. Convert daily Ether balances to USD using historical prices from CoinGecko (online-b). 6. Retain addresses with balances of at least USD 100,000 on any given day. 7. Restrict the analysis to the period from June 1, 2020, to June 1, 2025. Figure 6.4 illustrates the cumulative Ether balances (blue) and USD-denominated balances (green) of large Ethereum holders over time (magenta). The blue line indicates a gradual and consistent accumulation of Ether over the years, suggesting that large holders, potentially institutional entities, were accumulating Ether irrespective of market volatility. The green line exhibits more volatility, reflecting Ethereum’s price fluctuations. The number of large holders seems to undergo an increase prior to or during significant price rallies, particularly in early 2021 and early 2024. This observation could indicate the entry of new large players like institutional entities during growth phases. However, the most noteworthy observation is that even during substantial USD value declines, such as during 2022 and 2023, Ether balances of large Ether holders do not experience a sharp decline. This resilience implies a limited presence of short-term liquidation behaviour typically associated with retail investors, suggesting instead a holding strategy consistent with institutional market participants. 0 40 80 120 160 Number of accounts (in tsd.) 0 1 2 3 4 0 0.5 1 1.5 USD balance (in trillions) ETH balance (in billions) ETH Balance USD Balance Figure 6.4: Weekly aggregated Ethereum large balances in Ether (blue) and USD (green), and count of large accounts (magenta) In addition, Figure 6.5 shows the relative yearly Ethereum balance changes for addresses holding at least USD 100,000, segmented by weekday and weekend activity over the observed period. Across all observed years, approximately 75 percent of balance movements occur on weekdays, indicating a persistent structural pattern. This suggests that Ethereum balance shifts of large holders are predominantly driven by weekday activity, aligning with the operating hours and behavioural norms of traditional financial markets. Such a pattern may again reflect a significant institutional presence. Institutional Investors in Crypto Asset Markets 32 0% 25% 50% 75% 100% 2020 2021 2022 2023 2024 2025 Proportion of yearly ETH balance change Weekend Weekday Figure 6.5: Yearly Ether balance change by weekday and weekend 6.3.3 Holding Period Analysis While account balance analysis reveals the size and persistence of holdings, it does not capture how long those assets have been retained by their owners. To gain a fuller picture of investor behaviour, the next step examines holding periods, distinguishing between long-term holders (LTH) and short-term holders (STH). This dimension provides insight into investor conviction and trading horizons, which are often correlated with the strategic objectives of institutional versus retail participants. The following patterns may indicate institutional activity: • An increase in LTH-held supply may suggest accumulation behaviour, often associated with institutional strategies. • A rise in STH supply may indicate tokens are being moved in anticipation of near-term trading. The percentage of LTH versus STH of Ether is shown in Figure 6.6 and is based on the data generated in Section 6.3.2, with the figure also displaying the corresponding Ether price development over time. The distinction between LTH and STH follows the common convention of classifying addresses holding assets for more than 155 days as long-term holders and those holding for less as short-term holders. The figure shows that as Ether’s price rose, long-term holdings gave way to short-term speculation in the middle of 0 1,000 2,000 3,000 4,000 5,000 6,000 0% 25% 50% 75% 100% ETH price (USD) Proportion of holders LTH STH ETH Price (USD) Figure 6.6: Long-term versus short-term Ether holder change over the years 2021. This high turnover, typical of bull markets and significant crypto asset rallies, is reflected in the decline in the LTH percentage. Higher confidence in Ether’s longterm value is indicated by an increase and subsequent stabilisation in the percentage of long-term holders, particularly after 2022, despite significant price changes. While the figure alone cannot conclusively attribute these trends to institutional activity, the observed persistence in longterm holding patterns is consistent with the growing presence of institutional investors in Ether’s holder base. 6.4. Off-chain Analysis In addition to on-chain metrics, market data from centralised exchanges can provide further insight into trading behaviour and the potential role of institutional participants. This section examines two off-chain indicators, i.e., temporal trading patterns and market liquidity, to assess institutional involvement over time. A first indicator, shown in Figure 6.7, reveals a clear and consistent pattern in global spot trading volumes of Bitcoin across the days of the week. From January 2018 to June 2025, average weekday volumes ranged from 1.41 to 1.45 million BTC. In contrast, weekend trading volumes were notably lower, averaging 1.14 million BTC on Saturday and 1.17 million BTC on Sunday. This disparity between weekday and weekend trading activity supports the hypothesis that institutional investors, who typically trade during business hours on 33 Crypto Assets Study 2025 0 0.25 0.5 0.75 1 1.25 1.5 BTC (in millions) Figure 6.7: Mean global spot trading volume of Bitcoin by day of the week (source: CoinMarketCap (online-c)) weekdays, contribute significantly to overall market volume. The approximately 20 percent lower average volume on weekends may indicate reduced institutional engagement and a shift toward retail-driven activity during those periods. The consistency of this pattern over a multiyear timeframe reinforces the relevance of day-of-week effects in crypto asset market microstructure and suggests that, despite the continuous nature of crypto asset trading, institutional influence remains concentrated within traditional market hours. Figure 6.8 further explores the temporal evolution of trading activity distribution between weekdays and weekends. The data reveals a declining trend in the relative share of weekend trading volume over the observed period from 2018 through June 2025. While weekends accounted for around 25 to 27 percent of total trading volume in the years 2018 to 2020, this share gradually decreased, falling to 21 percent in 2022 and 2023, and reaching a low of 18 percent in 2024. For the first half of 2025, the weekend share remained subdued at 19 percent. This shift suggests an increasing concentration of market activity during weekdays, strengthening the interpretation that institutional participation has grown over time. As institutional actors generally operate within traditional business hours, a growing weekday dominance likely reflects their rising influence in the crypto asset markets. Conversely, the declining weekend share could indicate that retaildriven trading, which is more evenly distributed throughout the week, has become relatively less dominant. In addition to changes in trading volume patterns, a second indicator of institutional involvement is market liq0% 25% 50% 75% 100% 2018 2019 2020 2021 2022 2023 2024 2025 Proportion of trading volume Weekend Weekday Figure 6.8: Yearly proportions of global spot trading volume of Bitcoin by weekday and weekend (source: CoinMarketCap (online-c)) uidity. This is assessed by tracking the evolution of the mean bid-ask spread for Bitcoin across four major centralised exchanges, i.e., Bitfinex, Bitstamp, Coinbase, and Gemini, over the period from 2018 to mid-2025.3The bidask spread is expressed as a percentage and calculated as askmin −bidmax askmin ×100, where askmin is the lowest ask price and bidmax the highest bid price at a given point in time. The calculation is based on hourly data, and the graph displays the corresponding yearly averages. The findings are illustrated in Figure 6.9. Across most platforms, a clear downward trend in spreads is evident, indicating a significant increase in market liquidity and trading efficiency. Bitstamp and Gemini, which initially exhibited relatively wide bid-ask spreads, experienced a notable and steady narrowing over the observed period. Coinbase consistently maintained tighter spreads than the other exchanges, reflecting its comparatively higher liquidity and market efficiency throughout. Bitfinex, starting from already low spread levels, remained stable in the earlier years and demonstrated a modest tightening more recently. These developments suggest a gradually maturing and increasingly efficient trading environment, potentially influenced by growing institutional participation, enhanced liquidity provision, and the broader integration of crypto asset markets with traditional financial systems. 3These are the exchanges for which consistent data is available from January 2018 to the end of June 2025, as provided by Bitcoinity (online). Institutional Investors in Crypto Asset Markets 34 0 0.02 0.04 0.06 0.08 2018 2019 2020 2021 2022 2023 2024 2025 Spread (in %) Bitfinex Bitstamp Coinbase Gemini Figure 6.9: Yearly mean bid-ask spreads for Bitcoin on Bitfinex, Bitstamp, Coinbase, and Gemini (source: Bitcoinity (online)) 6.5. Summary Assessing the influence of institutional investors in crypto asset markets is challenging due to the pseudonymity of blockchain protocols and because market data generally does not distinguish between investor types. Still, assuming that institutional actors manage larger volumes, operate mainly on weekdays, and hold assets for extended periods, certain indicative patterns emerge from on-chain and off-chain data. On-chain analyses for Bitcoin and Ether reveal a higher prevalence of large transactions during weekdays. For Ethereum specifically, large-balance accounts show stable asset holdings even during market downturns and maintain a substantial share of long-term holdings, patterns consistent with institutional-style investment behaviour. However, the anonymity of blockchain addresses prevents definitive attribution without verified identity data. Off-chain data from centralised exchanges further point to possible growth in institutional participation. Global Bitcoin spot volumes are increasingly concentrated on weekdays, and mean bid–ask spreads have narrowed over time across four major exchanges. These features align with professional market norms, and the observed spread compression likely reflects increased liquidity provision, potentially from institutional market makers, as well as the general maturation of crypto asset trading infrastructure. 35 Crypto Assets Study 2025 7. Conclusion and Outlook This chapter presents key statements and hypotheses based on the findings of the “Crypto Assets Study 2025”. It summarises trends in the Swiss and Liechtenstein crypto asset market and provides insights into underlying market dynamics and potential future developments. On the way from a niche to an established asset class. The global crypto asset market has experienced a recovery in the past months, reaching a total market capitalisation of USD 3.5 trillion in mid-2025. In Switzerland and the Principality of Liechtenstein, indirect investment products have followed a similar trajectory, with assets under management (AuM) reaching approximately CHF 15 billion by the end of June 2025, an increase of more than CHF 6 billion compared to June 2024. In addition to rising prices, adoption has also continued to increase. The Swiss and Liechtenstein crypto asset investment ecosystem is evolving. Over the past twelve months, the number of companies active in crypto asset investments in Switzerland and Liechtenstein has increased from 359 to 407. Most are located in the cantons of Zug and Zurich. Business models serving both institutional and private clients, as well as those focused exclusively on institutional clients, dominate the market, while companies targeting only private clients are less common. The range of services spans all main segments of the crypto asset investment value chain, with investment services being the most common, particularly in the area of off-chain indirect investments. More products, but trading volumes show no clear tendency. The number of indirect investment products on Swiss traditional exchanges, including exchange-traded products and structured products, has continued to rise. While nominal AuM in these products fluctuated over the observation period, price-adjusted AuM showed a comparatively steady increase, indicating a net inflow of new capital. In June 2025, around two thirds of the AuM was based on Bitcoin products, although trading volumes have tended to increase proportionally more for indirect products linked to other crypto assets. Overall, trading volumes showed fluctuations but no clear tendency, and did not record significant growth compared to June 2024, one year earlier. This pattern is visible not only in indirect investments, including trading on derivatives crypto exchanges, but also in direct investments on centralised and decentralised crypto exchanges, with derivatives markets accounting for the largest share of overall trading activity. Bitcoin is not the new gold. The analysis of return dynamics shows that Bitcoin is most closely linked to both stocks and gold. Based on a historical assessment of riskadjusted performance for various asset class combinations, a portfolio including Bitcoin and gold achieved the best performance in the past, indicating that the two assets complemented each other in improving portfolio efficiency. However, a general limitation is that many prevalent portfolio allocation approaches are dependent on the historical performance of the individual asset classes. This underlines the value of exploring alternative portfolio optimisation approaches, particularly when dealing with volatile crypto assets. Institutional investors are increasingly entering the crypto asset market. Measuring the influence and significance of institutional investors in the crypto asset market is challenging because neither trading data from exchanges nor blockchain records directly identify the type of market participant. Their presence must therefore be inferred from characteristic behaviour, such as larger trade sizes, longer holding periods, and trading patterns concentrated on traditional business days. Multiple indicators point to growing institutional interest. Centralised exchange data for Bitcoin and Ether show higher trading volumes on weekdays compared to weekends and a gradual narrowing of bid-ask spreads. On-chain data confirm this weekday-dominant pattern, with large Bitcoin and Ether transactions more common on weekdays. In Ethereum, large-balance accounts hold assets increasingly steadily, even across different market phases, and retain a substantial share of long-term positions. Blockchain meets Kassenobligation. Swiss franc stablecoins have not shared in the strong growth of their USDdenominated counterparts. However, tokenised deposits and other balance sheet-based instruments are emerging as a promising use case. Switzerland is addressing this topic proactively and benefits from a well developed, regulated secondary market for tokenised assets. Authors 36 Authors This study was prepared by the following authors from the Lucerne University of Applied Sciences and Arts (HSLU), listed in alphabetical order. Authors (HSLU) Thomas Ankenbrand Denis Bieri Head Competence Center Investments Lecturer Joël Ettlin Angelo Gattlen Research Associate Research Associate Patric A. Huber Jovana Milojevic Lecturer Lecturer We would also like to thank the research partners of this study, namely Finnova, Inventx, Canton of Zug, SFTI / Swiss Fintech Innovations, SIX, Swiss Bankers Prepaid Services, and Zürcher Kantonalbank, for their monetary and content-related support. Contact For more information about this study, please contact us at: Thomas Ankenbrand Lucerne University of Applied Sciences and Arts thomas.ankenbr[email protected] Disclaimer This document has been prepared to provide general information. Nothing in this document constitutes a recommendation for the purchase or sale of any financial instrument or a commitment by the Lucerne University of Applied Sciences and Arts. In addition, this document includes information obtained from sources believed to be reliable, but the Lucerne University of Applied Sciences and Arts does not warrant its completeness or accuracy. This also includes the outputs of AI tools, like ChatGPT or DeepL, which were situationally used in the preparation of this document. 37 Crypto Assets Study 2025 References Angeris, G., Evans, A., Chitra, T., & Boyd, S. (2022). Optimal routing for constant function market makers. In Proceedings of the 23rd ACM Conference on Economics and Computation (pp. 115–128). Ankenbrand, T., Bieri, D., Ferrazzini, S., Hofer, S., Makra, A., Plazibat, A., … Spitzli, R. (2024). Crypto Asset Taxonomy. In: Crypto Assets Study 2024. Retrieved 25/06/2025, from https://hub.hslu.ch/retailbanking/download/crypto -assets-study/ Ankenbrand, T., Bieri, D., Gattlen, A., Aerni, A. L., Bieri, C., & Hoehener, J. (2024). Digital Wallets. Retrieved 06/12/2024, from https://www.ti8m.com/de/insights/downloads/wallet-studie Bitcoin Suisse. (online). CryptoFranc (XCHF) - the Swiss Franc Stablecoin. Retrieved 02/07/2025, from https://www .bitcoinsuisse.com/cryptofranc Bitcoinity. (online). Bid-ask spread. Retrieved 16/07/2024, from https://data.bitcoinity.org/markets/spread/all/USD ?r=day&t=l Bloomberg L.P. (2025). Gold Spot Price (XAU/CHF). (Data retrieved from Bloomberg Terminal, accessed on 2025-0702) BX Digital. (online). First regulated financial market infrastructure for trading and settlement of digital assets in Switzerland. Retrieved 02/07/2025, from https://bxdigital.ch/en/first-regulated-financial-market-infrastructure -for-trading-and-settlement-of-digital-assets-in-switzerland/ Chen, W., Chuen, M., & Aste, T. (2022). Whale Movements and Price Dynamics in the Cryptocurrency Market.Financial Innovation,8(1), 1–18. doi: 10.1186/s40854-022-00347-9 Coinbase Institutional, & EY-Parthenon. (2025). 2025 Institutional Investor Digital Assets Survey (Research Report). Coinbase. Retrieved from https://www.coinbase.com/en-gb/institutional/research-insights/research/ market-intelligence/2025-institutional-investor-survey (Accessed: 2025-07-03) CoinGecko. (online-a). Global Cryptocurrency Market Cap Charts. Retrieved 01/07/2025, from https://www.coingecko .com/en/global-charts CoinGecko. (online-b). CoinGecko Mainpage. Retrieved 30/07/2025, from https://www.coingecko.com CoinMarketCap. (online-a). Bitcoin ETF Tracker. Retrieved 01/07/2025, from https://coinmarketcap.com/etf/bitcoin/ CoinMarketCap. (online-b). Ethereum ETF Tracker. Retrieved 01/07/2025, from https://coinmarketcap.com/etf/ ethereum/ CoinMarketCap. (online-c). Bitcoin Price History. Retrieved 16/07/2024, from https://coinmarketcap.com/currencies/ bitcoin/historical-data/ Daian, P., Goldfeder, S., Kell, T., Li, Y., Zhao, X., Bentov, I., … Juels, A. (2019). Flash Boys 2.0: Frontrunning, Transaction Reordering, and Consensus Instability in Decentralized Exchanges.arXiv preprint arXiv:1904.05234. Retrieved from https://arxiv.org/abs/1904.05234 Danos, V., Khalloufi, H. E., & Prat, J. (2021). Global order routing on exchange networks. In International Conference on Financial Cryptography and Data Security (pp. 207–226). Deloitte. (2021). Taking the Pulse of Digital Assets in Financial Services Across EMEA (Research Report). Deloitte. Retrieved from https://www2.deloitte.com/ch/en/pages/financial-services/articles/how-do-emea -financial-institutions-view-digital-assets.html (Accessed: 2025-07-03) References 38 Dietrich, A., Rey, R., & Amrein, S. (2024). Crypto investments in Switzerland: awareness, relevance and reasons to invest. Retrieved 25/06/2025, from https://zenodo.org/records/14217143 Ethereum Foundation. (2025). Staking as a service (SaaS). Webpage. Retrieved 06/08/2025, from https://ethereum .org/en/staking/saas/ EY–Parthenon. (2024, May). Gaining Ground: How Institutional Investors Plan to Approach Digital Assets in 2024 (Research Report). EY. Retrieved from https://www.ey.com/content/dam/ey-unified-site/ey-com/en-us/insights/ financial-services/documents/ey-gaining-ground-how-institutional-investors-plan-to-approach-digital-assets-in -2024.pdf (Accessed: 2025-07-03) Federal Statistical Office. (2025). Bevölkerungsstand am Ende des 1. Quartals 2025. Retrieved 06/08/2025, from https://www.bfs.admin.ch/bfs/de/home/statistiken/bevoelkerung.html Financial Market Authority Liechtenstein. (online). MiCAR. Retrieved 25/06/2025, from https://www.fma-li.li/en/ supervision-regulation/fintech/micar finanzen.net. (online). Bitcoin - Schweizer Franken. Retrieved 02/07/2025, from https://www.finanzen.ch/devisen/ bitcoin-franken-kurs FINMA. (2025). FINMA licenses first DLT trading facility. Retrieved 25/06/2025, from https://www.finma.ch/en/news/ 2025/03/20250318-mm-dlt-handelssystem/ Foucault, T., & Menkveld, A. J. (2008). Competition for order flow and smart order routing systems.The Journal of Finance,63(1), 119–158. Frankencoin. (online). Frankencoin. Retrieved 02/07/2025, from https://www.frankencoin.com/ Gogel, D. (2021). DeFi Beyond the Hype: The Emerging World of Decentralized Finance (Policy�maker toolkit companion report). University of Pennsylvania, Wharton Blockchain and Digital Asset Project. Retrieved 05/08/2025, from https://wifpr.wharton.upenn.edu/wp-content/uploads/2021/05/DeFi-Beyond-the-Hype.pdf Investopedia. (2025). Business Day. Retrieved 08/08/2025, from https://www.investopedia.com/terms/b/business -day.asp Long, J. S., & Ervin, L. H. (2000). Using heteroscedasticity consistent standard errors in the linear regression model.The American Statistician,54(3), 217–224. Maerki Baumann. (online). Swiss crypto regulatory landscape – what works and where the challenges lie? ARCHIP Blog. Retrieved 02/07/2025, from https://www.archip.ch/en/knowledge-center/article/swiss-regulatory-landscape Markowitz, H. (1952). Portfolio Selection.The Journal of Finance,7(1), 77–91. Retrieved 11/08/2025, from http:// www.jstor.org/stable/2975974 OpenAI. (2025). GPT-4o Model. Retrieved from https://openai.com (Used in an AI-assisted screening process; accessed 8 June 2025) PwC. (online). Swiss DLT law: New regulations bring new opportunities. Retrieved 02/07/2025, from https://www.pwc .ch/en/insights/regulation/swiss-dlt-new-regulations.html SDX. (2025a). Listing with SIX Digital Exchange. Retrieved 02/07/2025, from https://www.sdx.com/listing/ SDX. (2025b). Citi and SDX Join Forces to Unlock Access to Tokenized Private Market Assets for Global Issuers and Investors. Retrieved 02/07/2025, from https://www.sdx.com/news/citi-and-sdx-join-forces-to-unlock-access-to -tokenized-private-market-assets/ Semrush. (online). Dashboard. Retrieved 05/08/2025, from https://www.semrush.com/projects/ 39 Crypto Assets Study 2025 Shrimali, B., & Patel, H. B. (2022). Blockchain state-of-the-art: architecture, use cases, consensus, challenges and opportunities.Journal of King Saud University - Computer and Information Sciences,34(9), 6793–6807. Retrieved from https://www.sciencedirect.com/science/article/pii/S131915782100207X doi: 10.1016/j.jksuci.2021.08 .005 SIX. (2021). SIX Launches its SIX Digital Exchange by Successfully Issuing the World’s First Digital Bond in a Fully Regulated Environment. Retrieved 02/07/2025, from https://www.six-group.com/en/newsroom/media-releases/ 2021/20211118-six-sdx-digital-bond.html SIX. (online-a). Index Data Center - Index Overview. Retrieved 02/07/2025, from https://www.six-group.com/ exchanges/indices/data_centre/ SIX. (online-b). SIX Crypto Market Index 10. Retrieved 02/07/2024, from https://www.six-group.com/en/market-data/ indices/crypto/six-crypto-market-index-10.html S&P Global Ratings. (2023). Crypto CeFi And DeFi Must Strike A Balance To Thrive (Research report). S&P Global Ratings. Retrieved 04/08/2025, from https://www.spglobal.com/_assets/documents/ratings/research/101578824 .pdf (Published June 22, 2023) Stefanoski, D., & Sahin, O. (2021). Security token offering: a snapshot in Switzerland as of August 2021. Ernst & Young. Retrieved 02/07/2025, from https://www.ey.com/en_ch/insights/financial-services/security-token -offering-a-snapshot-in-switzerland Swiss Bankers Association. (2024). Swiss banks sign memorandum of understanding to explore the feasibility of a jointly issued Swiss franc deposit token. Retrieved 18/08/2025, from https://www.swissbanking.ch/ en/media-politics/news/schweizer-banken-unterzeichnen-absichtserklaerung-um-die-machbarkeit-eines -gemeinsam-emittierten-schweizer-franken-buchgeld-tokens-zu-pruefen Swiss Bankers Association. (2025). Stablecoins in Switzerland. Retrieved 02/07/2025, from https:// www.swissbanking.ch/_Resources/Persistent/0/5/0/1/0501708bb8d749954729879c52024ab0cb65d2d7/ SBA%20Expert%20report%20stablecoins.pdf Swiss National Bank. (online). Yields on bond issues – Day. Retrieved 02/07/2025, from https://data.snb.ch/en/topics/ ziredev/cube/rendoblid Sygnum Bank AG. (2024). Digital Asset Adoption and Outlook 2024 (Tech. Rep.). Sygnum. Retrieved from https:// www.sygnum.com/research (Accessed: 2025-07-03) TokenMarketCap. (online). List of Swiss Asset Tokens. Retrieved 02/07/2025, from https://www.tokenmarketcap.ch/ U.S. Department of the Treasury. (2023). Illicit Finance Risk Assessment of Decentralized Finance (Government report). U.S. Department of the Treasury. Retrieved 04/08/2025, from https://home.treasury.gov/system/files/136/DeFi -Risk-Full-Review.pdf (License: Public Domain; Assessment under Executive Order 14067) Visa & Allium Labs. (online-a). Stablecoin Supply. Retrieved 08/07/2025, from https://visaonchainanalytics.com/ supply Visa & Allium Labs. (online-b). Visa Onchain Analytics Dashboard. Retrieved 08/07/2025, from https:// visaonchainanalytics.com/ Zetzsche, D. A., Buckley, R. P., & Arner, D. W. (2021). The Markets in Crypto-Assets Regulation (MiCAR): A Critical Overview.Journal of Financial Regulation and Compliance,29(4), 547–567. doi: 10.1108/JFRC-09-2021-0094 ISBN-Number 978-3-907379-56-1 Lucerne School of Business Institute of Financial Services Zug IFZ Campus Zug-Rotkreuz Suurstoffi 1 6343 Rotkreuz T +41 41 757 67 67 [email protected] hslu.ch/ifz A study conducted by