Blockwall Capital I Thesis

1. Introduction

This paper describes Blockwall’s investment thesis, and how we see the evolving asset class of crypto assets. At first, the evolution of the Internet from Web 1.0 through Web 2.0 to Web 3.0 will be described as well as its implications elaborated upon. This will be followed by an illustration of how Blockwall’s views the assets evolving within Web 3.0 in light of our Asset Classification Framework (ACF). This is of importance to understand where in Web 3.0 value will be generated and captured. After elaborating on our ACF, the key hypothesis of Blockwall’s investment rationale will be explained. In the following, our investment approach will be explained with respect to investment time horizons, portfolio strategy, rebalancing, as well as pre-sale opportunities.  

2. The Evolution of the Internet: From Web 1.0 to Web 3.0

The history of the Internet started with Web 1.0 in 1991, when Tim Berners-Lee announced the World Wide Web which enabled the sharing of information via the Internet. At this time, the Internet was a read-only web with the possibility to access information, but interactions with the websites such as content creation were not feasible. In fact, Web 1.0 websites were static web pages. Human interaction was basically limited to options such as e-mail. Early examples of Web 1.0 were university homepages, personal web pages, and dictionaries. Although limited in scope, Web 1.0 was a true technological innovation as the sharing of information was possible on a global scale for every individual at low costs. 

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Web 1.0, was built on top of protocols that lay the foundation for future development of the Internet, such as:

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• TCP/IP (1978): Information transmitting and identity in network
• IMAP/SMTP (1980s): E-Mail
• DNS (1984): Human-readable domain pages
• FTP (1985): File-sharing on central servers
• HTTP (1989): Linking documents across the Internet
• HTML (1993): Web programming language

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From the early 2000s onwards, Web 2.0 emerged. The major evolvement was the upgrade of the read-only to a read-write web. With its read-write possibility, Web 2.0 enabled users to (1) more easily interact with other users, and (2) create content on those websites and networks. Examples for networks in Web 2.0 are, for instance Facebook, ICQ, and Twitter. However, the transition from Web 1.0 to Web 2.0 was rather a continuous process than an instant switch. Chat rooms, such as the IRC network, already existed in Web 1.0. Unfortunately, those networks were complicated and difficult to use and therefore could not offer a user experience that appealed to a wider audience. Thus, Web 2.0 protocols were created in order to improve upon user experience and thereby increase the ease of interaction and contribution. Examples of Web 2.0 websites are, for instance, Amazon and Wikipedia. Those provide dynamic web pages instead of the static Web 1.0 ones, meaning its users are able to contribute and create content on them. In essence, Web 2.0 made social media and e-commerce possible, as it enabled peer-to-peer transactions and interactions on a global scale. 

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However, a trusted third party, namely the host of a network, is still required to store and manage the data centrally as Web 2.0 protocols cannot save state (i.e., store data about user relations and network usage, as well as changes therein). Hence, the network’s host officiates as an intermediary between its users. This is due to the fact that those networks had to be hosted on a server of a central party, providing the platform for the network and establishing a trusted environment for its users. Those servers store all the data related to the network’s usage by its users. Since those networks are managed by a central party (e.g., Facebook), this party is able to dictate the rules of engagement. 

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Due to their data monopolies, these centralized parties functioning as intermediaries capture a large part of the inherent value of the stored data, and due to their network effects they can consistently defend their position against competition. Essentially, they control all their users’ data and are able to monetize and use it, which in fact constitutes a commoditization of personal information.

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Examples for Web 2.0 specific protocols that enabled this upgrade of the Internet are:

• XML (1996): Human and machine-readable data description
• OSCAR (1997): AOL Instant Messenger, ICQ
• RSS (1999): Simple web syndication
• REST (early 2000): Restful APIs
• XFN (2003): Representation of human relationships 
• BitTorrent (2004): Efficient peer-to-peer file sharing

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With the fundamental setup of the Internet by Web 1.0 and Web 2.0 protocols, we are now facing the next upgrade of the internet (i.e., Web 3.0). To recap, the innovation of Web 1.0 was information sharing, and Web 2.0’s innovation was enabling user interaction throughout a network. Now, the innovation of Web 3.0 is based on its ability to enable transferability of value. The key component that leads to this upgrade is found in the protocols abilities to save state without the need of a central authority.

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Since Web 3.0 protocols hold the ability to account for changes in state on the protocol level, they enable peer-to-peer (P2P) transmission of value via the Internet for the first time in history. Web 3.0 is dominated by protocols, creating a trusted environment where users can interact without a trusted third party that functions as an intermediary between peers. As a result, the value captured in the data provided by users that was possessed and dominated by centralized third parties in the past will in the future be captured by users themselves. 

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In order to capture state, enable changes in the state, and to allow for the transfer of state between network participants, crypto assets use tokens, as they are the representation of state and therefore value. Additionally, tokens function as the incentivization force to coordinate economic activity in these networks, given that they set financial incentives. Therefore, tokens are the medium of interaction in these networks that capture the value created. As these protocols are significantly reducing the cost of coordinating economic activity among users, they are hypothesized to outperform the centralized networks of Web 2.0.

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Referring to the fat protocol thesis in the article by Joel Monegro: he strongly supports the value shift hypothesis from the evolution of Web 2.0 to 3.0. Monegro argues that in Web 1.0 and Web 2.0, value was captured on the application and product layer dominated by entities that are hosting the networks as a centralized service provider, thereby effectively owning all data. The major reason is because infrastructure protocols such as TCP/IP have not been monetized in the past. With crypto assets and their native tokens this changes drastically, since there is no central rent-seeking party involved anymore. Consequently, value (entailed in the data put on Web 3.0 protocols) will be at least partially captured on the protocol level itself and embodied in the respective tokens via a token model. These token models are structured in a way that all network participants are incentivized to actively engage in the network. Additionally, users apply tokens among others to pay for services, to acquire rights in the project’s governance, and for rewarding transaction verifying nodes with transactions fees.

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Blockchain enables a shift from centralization to decentralization, effectively reducing the power over user data and content of centrally owned networks like Facebook or YouTube. Those networks create substantial revenue streams for themselves based on their users’ content or data. With blockchains, however, users own these networks, rendering them decentralized, since there is no single party controlling the network. Therefore, value created in the network is distributed between its users, among others in the form of higher efficiency, reduced cost, or revenue for content creation. This constitutes the disintermediation of trusted third parties, as middlemen are effectively being cut out.

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Examples for the protocols that currently form the nascent stage of the Web 3.0 are:

• Bitcoin (2008): P2P value transfer network
• Ethereum (2013): Smart contract platform (security, decentralization)
• Stellar (2014): Global money and asset exchange platform
• Fetch.ai (2016): Machine learning-driven virtual marketplace
• Zcash (2016): Privacy-enabling P2P value transfer network
• EOS (2017): Smart contract platform (security, throughput)

3. Mapping an Infrastructure Protocol: A Simplified Perspective on its Layers

The Asset Classification Framework (ACF), developed by Blockwall, offers a framework to simplify the complex structure of a distributed ledger technology (DLT) system, identify the individual components of the system, and aid in the educated analysis and comparison of crypto-assets. The purpose of ACF is to analyze a single DLT system and the ecosystem built around it. 

3.1. Illustration of the ACF 

3.2. Explanation of the ACF

3.2.1. Protocol Layer

The protocol layer encompasses the protocols of a DLT and the mechanism for protocol implementation. Protocols are the foundation of the entire DLT system, as they define the set of formal rules that govern the system and codify its architectural design. Protocols act as a set of constitutional agreements (e.g., consensus mechanisms, hashing algorithms, data distribution protocols, etc.) that all the system participants agree upon. The protocol has a genesis component, referring to the processes required to undertake and complete before launching the system, and an alteration component (only in the case of on-chain governance), which is the process in place to enable modifications of the protocol rules. The network of a DLT system exists as a direct result of the implementation of the protocol rules. The network consists of an interconnected group of actors and processes that adhere to a technology standard (protocol) and actively participate in the exchange of data and information over integrated communication channels. The implementation has three core components: communication, transaction processing, and validation. The communication component is the exchange and sharing of data across participants; the transaction processing component is the set of actions required to add an unconfirmed transaction to the shared set of authoritative records; and the validation component is the set of processes required to ensure that actors independently arrive at the same conclusion with regard to the authoritative set of record. The implementation of the protocols facilitate the various steps in the settlement process that lead to the creation of an immutable ledger that saves all the transaction details of the DLT system.

3.2.2. Data Layer

The data layer is assembled over time as transactions are written to the ledger by the activities of the participants, who comply with the protocols of the DLT system. The data layer refers to information processed and stored by the DLT system in form of records. The core feature that a DLT system delivers is this shared data structure – the ledger – that has a set of crucial features, such as immutability, persistence, transparency, standardization, and censorship resistance. The ledger provides the authoritative version of records at a moment in time that is both shared amongst users of the system and updated over time as users engage with one another via the system. The data layer consists of two components: the operation and the journal component. The operation component is the processes, which govern how (and which) data is used in the creation of new records, modification of existing records, and the execution of code (may also include smart contracts); the journal component concerns the contents of stored records such as what data within the records is being referenced, or what is written in the blocks.

3.2.3. Developer Interface

One of the crucial layers, the developer interface are the tools and platforms that facilitate the interaction of developers with the DLT system to use its features to create other products or applications (e.g., decentralized applications (dApps), tokens, DEXs, etc.). They consist of an integrated development environment (IDE) that encompasses an execution environment (e.g., Ethereum Virtual Machine, WASM), the programming language (Domain Specific Languages or General Purpose Languages that are understood by the DLT system) to write codes, an Application Programming Interface (API), a Software Development Kit (SDK), compilers, and other tools that facilitate dApp development. The existence of this layer in a DLT system depends on the statefulness of the system. Stateful DLT systems (e.g., Ethereum, EOS) have their own execution environments that can range from a simple fixed-purpose to a more complex general-purpose virtual machine (e.g., Ethereum Virtual Machine, WASM). The Turing complete environment, especially that of a general-purpose virtual machine, theoretically allows the modeling of any program using the smart contract feature. In contrast, stateless DLT systems are based on simple scripting languages that lack Turing-completeness and offer limited or no smart contract functionality. Nevertheless, such systems can incorporate an external run-time environment through layer 2 protocols (e.g., side chains) developed on top of a DLT system.

3.2.4. Infrastructure Token

While the layers discussed above are the technological layers of a DLT system, the infrastructure token is the accounting mechanism that facilitates the economic rationale in the system. The Infrastructure token, sometimes the main/only product of the system (e.g., cryptocurrencies), is the game-theoretic incentive to the participants of the system. This is the medium through which Blockwall or any other individual/institutional investor invests in this technology. Often, infrastructure tokens are considered as the ‘shares/securities’ of a DLT system, especially with regulators seeking to classify some of them as securities. Nevertheless, the value of infrastructure tokens are expansive and not limited to the ownership of technology. Some infrastructure tokens act as the “gas” for transactions or used as a staking mechanism to participate in the validating process, governance, etc. Furthermore, the infrastructures tokens are standalone assets that can be used as a store of value, a medium of exchange and a vehicle for speculation in the crypto market. According to Blockwall’s investment thesis, the infrastructure token of a DLT system is able to capture value of its underlying technology. Therefore, token economics of a DLT system are the most important criteria of our thesis.  

3.2.5. Features

The features are not an inherent layer of a DLT system and serve the sole purpose of mapping the functionalities and characteristics of a DLT system. Mapping this layer helps to identify the value delivered by crypto-assets in the Web 3.0 ecosystem, thus enabling an educated analysis and comparison with similar DLT systems. Features of a system could be smart contract functionality, unique qualities of the system such as high scalability, robustness, etc., or any significant technology (e.g., zk-SNARKS) that the system introduced. 

3.2.6. Layer 2 protocols

Layer 2 protocols are built on top of a base layer protocol in order to amend or extend the capabilities of the underlying protocol. These meta-protocols provide enhanced features such as scaling, computation, privacy, smart contract functionality, decentralized exchange functionality, etc. Furthermore, some layer 2 protocols (e.g., side chains) are able to provide smart contract functionality to a stateless DLT system by offering an external runtime environment. In addition to smart contracts, side chains reduce the ‘attack surface’ of the base layer DLT, increase the scalability and offer additional privacy and confidentiality. Thus, the existence of such layer 2 protocols makes an underlying DLT system a fit to the investment thesis of Blockwall.

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A layer 2 protocol can have its own infrastructure token and provide its own developer interface to integrate the functionalities towards a dApp. In spite of this, a layer 2 protocol is always dependent on the base layer infrastructure provided by layer 1 protocol. Thus a dApp built on top of a layer 2 protocol uses the features of the layer 2 protocol and the features of the underlying layer 1 protocol (dApps can be developed without using any layer 2 protocols, solely based on the layer 1 infrastructure). 

3.2.7. Products

Products serve the end users and are often developed by third parties on the top of the overall DLT infrastructure. These products become successful by creating a unique value to the end-user through monetizing the value captured by the end-user, much like internet platforms of today (e.g., Uber, AirBnB, PayPal, etc.). But the similarity ends here as products developed on a DLT system are much more dependent on its infrastructure rather than the conventional internet platforms. Most of the dApps, the main products on a DLT infrastructure, require the end-user to use the infrastructure tokens to perform an action (e.g., initiate transaction, access a feature, etc.) or require the developer to use the tokens to access the resources of the infrastructure. Thus, a product developed on a DLT system is tied to the token mechanism of the DLT for its eternity and the monetization of the value delivered will always include a marginal fee to its DLT infrastructure. Thus the demand for the product will indirectly create a demand for the infrastructure tokens and enhance the value of the underlying infrastructure protocol.

3.2.8. User Interface

The last and final layer in the ACF is the user interface, which connects the end-user with the infrastructure token of the DLT system or other products developed on top of the infrastructure protocol. With respect to infrastructure tokens, the user-interface is mostly wallets that allow end-users to hold, send and receive tokens. Wallets can be offered by the DLT system itself or third parties. With respect to products (e.g., dApps, DEXs, etc.), the user interface is the front-end developed by the respective third parties. This is one of the most important layers for the adoption of products and services facilitated by the DLT system, but there is a general lack of user interfaces – especially a general user interface (e.g., dApp browsers), in the ecosystem today. 

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4. Key Hypothesis of Blockwall’s Crypto Asset Investment Rationale

4.1. The current state of the infrastructure layer

Currently, technological development of crypto assets is still at a nascent stage. This means that the foundation for dApps to be built upon – namely infrastructure protocols – is not yet set or only limited in scope. There are still several issues to be solved, such as the issue of scalability, which is a prerequisite for mass adoption. This issue is derived from a framework called “scalability trilemma”, which describes that a crypto asset can only have two of the following three qualities: (1) decentralization, (2) security, and (3) scalability. 

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In October 2018, USV released an article describing the evolvement process of the crypto asset industry as an iterative process between apps and infrastructure, beginning with a certain breakout app. This app leads to the development of infrastructure, which in turn enables new apps. Therefore, there is no infrastructure phase but a repetitive cycle of app and infrastructure development. However, building a sustainable dApp requires a reliable infrastructure to build upon. In fact, building a dApp on a specific blockchain essentially contains a bet by the dApp developers on the developers of that respective DLT system with respect to the sustainability and success of the respective underlying DLT system. 

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Additionally, the current adoption of crypto assets as well as the usage of dApps is still very low. Existing dApps have only very few daily active users (DAU) and monthly active users (MAU). For instance, the prediction market Augur has only 15 DAU and 344 MAU at the time of writing. One of the most hyped dApps, ‘CryptoKitties’, where you can collect digital representations of cats, currently has only 395 DAU and 3,677 MAU.

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Hypothesis 1

In the current stage of the Web 3.0 evolution, the majority of innovation and advancement is still occurring on the infrastructure layer, with a clear need to consider the necessities of the developers community and their use cases (i.e., dApps).

4.2. The importance of open source protocols

Web 3.0 crypto asset protocols are open source, meaning that their codebase can be publicly accessed, revised, and adjusted on platforms like GitHub. This enables many developers to start developing dApps for the network or simply to audit and contribute to the code. Effectively, network effects are also existing on the developer site. When Apple launched its iPhone they released significant parts of their code as open source. This incentivized and enabled thousands of developers to start building apps on top of the iPhone smartphone operating system, thereby creating value for the iPhone itself.

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Hypothesis 2

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If infrastructure layers are built with the key characteristic of public code (open source), the adoption of use cases in the form of dApps and its effect on the native tokens will outperform the non-public code (non-open source) infrastructure layer tokens.

4.3. Market cycles and S-curve of tech adoption

Adoption of technological innovation typically evolves in cycles and takes time. According to Amara’s law, we tend to overestimate the effects of technological innovation in the short-term but underestimate the long-term effects. This has been a publicly acknowledged effect from technology entrepreneurs like Bill Gates. As a result, cyclicality of technology adoption with its boom and bust phases evolves. Cyclicality of technology adoption is best described with the Gartner Hype Cycle.

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The Gartner Hype Cycle begins with a technological trigger that gets people excited about its promises for the future. This leads to a hype around the technology and inflated expectations of what the technology is capable of. At the peak, people realize the exuberance of their expectations and further become aware of the nascent stage of development the technology is still in, combined with the many problems that need to be solved prior to enabling potential mass adoption. The disappointment resulting from these realizations of the current state of the technology leads to the trough of disillusionment, which is a stage of exaggerated pessimism with respect to the new technology. At some point the market realizes its negative sentiment is exaggerated as well, and the sentiment goes through the slope of enlightenment and reaches the plateau of productivity. At this stage the most development of the technology takes place, which in turn triggers the next bull run that leads again to an irrational exuberance of expectations.

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This cycle of exaggerated hype followed by exaggerated disappointment happens several times during the adoption phase of a new technology. It is enforced by basic human emotions of greed and fear. At the peak people will feel “Fear Of Missing Out” (“FOMO”) on massive returns, while at the low people become overly anxious to fully lose their invested money.

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However, each of these cycles brings new people into the market and therefore plays a crucial role in the adoption of technology. The full adoption phase is best described using the concepts of the S-curve and the bell curve of technological adoption.

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The bell curve describes adoption as a slow start, where only few people realize the potential of the new technology. Those first two phases are referred to as “innovators” and “early adopters” phases. In these phases, the investment case for the new technology is far from obvious, and most investors and individuals cannot yet fathom the potential. Naturally, this is reflected in the price of such early stage investments, enabling substantial value appreciation potential if a wider audience eventually recognizes the potential. Consequently, if the “early majority” and the “late majority” – which are much larger groups than the “innovators” and “early adopters”– start realizing the technologies potential and entering with investments, the early adopters will already have accumulated substantial value appreciation in their investments. In fact, the earlier in the adoption cycle one enters an investment, the higher the potential profit. As the potential of the respective investment becomes more obvious and subsequently more investors start to enter the market, the more the potential profits decline. However, risk is proportional to the potential profits, meaning that with decreasing potential profits the risk also declines. This implies that early-stage investments due to their exceptionally high profit potential also incur exceptionally high levels of risk, which leads to the requirement of a deep analysis for early stage-investments prior to investing.

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The S-curve describes the typical market share evolvement of a technology during its adoption cycle. From the “innovators” until the “early majority” phase the market share typically grows exponentially. With the beginning of the “late majority” phase the growth rate tends to decline leading to a logarithmic growth until universal adoption is reached within the “laggards” phase.

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An important point to notice is when the chasm is being crossed. The chasm is a gap between the early adopters and the early majority due to missing pragmatic uses for the respective technology. With crypto assets this gap is due to issues such as the missing real life use cases, the lacking scalability, the current inconvenient user experience, and the regulatory unclarity. Those issues have to be solved in order to acquire users and subsequently achieve widespread adoption.

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Hypothesis 3

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Crypto assets are on the edge of reaching/crossing the chasm from early adopters to early majority. At the same time, adoption is key for any of the technologies to cross that chasm, whereas simpler use cases (e.g., payments) will reach their plateau of productivity first, while other use cases (e.g., smart contracts) will shortly follow.

5. Our Investment Thesis

Current levels of volatility and the drivers of market movements by speculative traders lead to a situation, where it is impossible to predict the market in the short-term. Moreover, crypto assets have brought with them a couple of new paradigms that change some rules on how they function as an investable asset. 

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At this stage, investments in such an environment require a long-term oriented fundamental and value-driven approach in order to allow for the technology to evolve and achieve adoption over time. Therefore, Blockwall is confident about crypto asset investments by taking a long-term investment approach into this asset class. Consequently, Blockwall has structured closed-ended funds with a duration of at least six years.

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Since crypto assets face substantial volatility, an open-ended fund structure would pose the risk of capital redemptions in unfavorable market conditions and further limit the fund to participate in promising pre-sale investments that are illiquid for quite some time. This is especially the case for the highly volatile crypto asset markets, where emotions quickly overtake an investor’s rational decision-making. Hence, a closed-ended fund structure prevents forced liquidations of portfolio positions due to capital redemptions. It further enables us to focus on the fundamental quality of our portfolio assets instead. By acting according to Blockwall’s individual assessment of performance, valuation as well as achievements of specific crypto assets, we are subsequently increasing or decreasing a position in the respective assets. Hence, in our view a closed-ended fund structure combined with a liquid venture capital approach is currently the most appropriate structure to invest in crypto assets.

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In traditional venture capital (VC), closed-ended funds cannot rebalance their portfolio as VC investments are typically illiquid and include lockup periods from seven to 10 years. Therefore, traditional VC funds face a one-time selection risk. On the other hand, liquid crypto assets are tradable upon finishing their initial token generating event. By investing into liquid assets, we have the opportunity to rebalance the portfolio according to our judgement concerning recent development and adoption progress of our portfolio tokens. In traditional VC investments this is not possible, which entails the opportunity to take advantage of the broad and competitive landscape of liquid crypto assets with the option of actively curating and rebalancing a portfolio.

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However, there are not only liquid crypto assets but also non-liquid crypto assets, usually referred to as pre-sale deals or private sale deals, in which projects sell their tokens directly and exclusively to professional investors on the contractual basis of mostly SAFT agreements (Simple Agreement on Future Tokens) or in various minor alternatives. Those pre-sale projects typically require a lock-up period of an average of 12 months and are more difficult to get access to, requiring the investor to be well connected within the industry. They offer potentially higher returns compared to liquid assets, while usually being in earlier stages of development, looking for strategic investors, which is in turn reflected in lower valuations. Additionally, due to their very early nature, pre-sale assets enable an investor to take a more active role in the development of the project, since investors can assist with protocol design and token economics, or with connecting the project to other projects for potential partnerships. On the contrary, those illiquid crypto assets bare the risks of not succeeding on launching their product or to achieve liquidity on exchanges after the tokenization event occurred.

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Due to the reasons outlined in section 4 concerning the nascent development stage of the industry, investments into infrastructure tokens enable multiple use cases and provide less risk as they do not depend on the success of a single project or use case. Hence, it is Blockwall’s conviction that investments into projects on the infrastructure layer, which provide multiple use cases currently offer promising risk return ratios. 

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However, we continuously follow the industry’s evolution to a point where the infrastructure layer is established as a sustainable, scalable and reliable basis for the development of dApps on top. This will enable end-user applications to become viable. At this point our thesis will eventually adapt and broaden in order to capture the full value proposition of crypto assets.

6. Conclusion

Blockwall is a long-term crypto asset investor, focused on building a crypto asset portfolio that sustains in a highly volatile market.

Blockwall is convinced that the appropriate strategy is a long-term fundamental and value-driven approach that takes the technology’s adoption rate as well as hype cycles into account. In the current state where technological development is in a nascent stage and adoption is relatively low, the fund focuses on infrastructure protocols that fulfill multiple use cases rather than end-user use cases. As the technology matures and gains wider market adoption, Blockwall’s selection criteria will eventually adapt to capture the advancement of the technology and evolve to investments in single use case dApps.

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Blockwall is a dedicated crypto asset manager that seeks to maximize investor’s returns by identifying promising crypto assets as well as by monitoring and evaluating their rightful place in our fund’s portfolio.

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Blockwall’s approach is also to take an active role in the development of its portfolio assets. Most projects look specifically for strategic investors, who maintain long-term exposure to their investments, as this prevents external shocks due to short-term sell-offs by investors. Additionally, long-term investors take a more active role and act as a sparring partner, meaning that they help their portfolio projects with topics such as token economics, or in the process of building partnerships.

A closed-ended fund structure combined with a liquid venture approach is most appropriate to bridge the opportunities of technologies and risks of public markets, as it prevents forced liquidations of portfolio positions due to capital redemptions by investors. It therefore enables the fund to take long-term positions, which we are convinced provide for the biggest value creation within the coming years.

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We are grateful for the prior works done in the crypto space to classify and analyze DLTs. The research done by the Cambridge Center for Alternative Finance on DLT systems in particular helped us to gain an in-depth understanding and formulate our thoughts. Furthermore, the articles by Jill Carlson and Joel Monegro, and the investment thesis by Joel Monegro & Chris Burniske certainly inspired our investment thesis and asset classification framework.

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