Crypto Basics

How to Make Money in Crypto? - Unveiling the Secrets to 100x Returns

Learn how to make money in crypto and discover the secrets to get 100x returns in the crypto market with expert insights and strategies.
Token Metrics Team
7 Minutes
MIN

The cryptocurrency world has become a dynamic hub of opportunities for savvy investors looking to make substantial profits. With the right strategies and a keen eye for emerging trends, anyone can achieve mind-boggling investment returns. 

In this comprehensive guide, we will explore the secrets to making money in crypto and uncover the path to 100x returns.

Who is Ian Balina?

Before we delve into the strategy, it's essential to understand the expertise and know the individual behind it. Ian Balina, the founder and CEO of Token Metrics, is a renowned figure in the crypto world. 

With a background in computer engineering and experience as a sales engineer at IBM and a consultant at Deloitte Consulting, Ian brings a unique blend of technical knowledge and business acumen. 

He turned $20,000 into over $5 million in less than 12 months using a data-driven approach. With his vast experience and proven track record, Ian's insights into the crypto market are highly sought after.

The 3-Point 100x Strategy

When making 100x returns in the crypto market, Ian Balina has developed a three-point strategy that forms the foundation of his approach. These three points are quality, tokenomics, and valuation.

Quality - The Key to Successful Crypto Investments - Investing in quality crypto assets is crucial for long-term success. By assessing the fundamentals and technology behind a project, you can determine its growth potential. Factors such as on-chain traction, active wallets, community size, and the team's background play a significant role in evaluating the quality of a crypto asset. Additionally, analyzing the code quality, developer activity, and security audits provides insights into the technological aspect of the project.

Tokenomics: Evaluating the Long-Term Value - Understanding the tokenomics of a crypto asset is essential to identify its long-term value. Factors such as supply and demand dynamics, economic incentives, and the token's utility within the ecosystem are crucial in determining whether it's worth holding for the long term. 

By assessing the balance between supply and demand and analyzing the market's perception of the asset, you can gauge its growth potential.

Valuation: Identifying Undervalued Gems - Finding undervalued crypto assets is the key to unlocking substantial returns. By comparing the fully diluted valuation (FDV) with the market capitalization, you can identify potential discrepancies. 

Additionally, analyzing the asset's valuation compared to its competitors within the sector provides valuable insights into its growth potential. Value investing principles, such as buying low and selling high, form the basis of this valuation strategy.

What is the 100x?

Before we dive deeper into the strategies, let's define what precisely a 100x return means in the crypto world. A 100x return refers to multiplying your investment by 100, resulting in a whopping 10,000% return. 

For example, turning $10,000 into $1 million or $1,000 into $100,000 would be considered a 100x return. Achieving such astronomical returns requires identifying crypto assets with tremendous growth potential and investing in them at the right time.

Solana: A 1000x Case Study

To illustrate the potential for 100x returns, let's examine the success story of Solana. Solana, a blockchain platform, delivered over 1000x returns to early venture capital (VC) investors. By analyzing the various funding rounds and the subsequent performance of Solana's token, we can gain insights into the strategies that led to such impressive returns.

Seed Round: Seeding the Path to Success

In March 2018, Solana raised over $3 million in its seed round for 4 cents per token. At this early stage, the project had only released version 0.1 of its whitepaper. 

Fast forward to the all-time high of Solana's token, which reached almost $260, and VC investors who participated in the seed round achieved an incredible 6500x return on their investment.

Additional Funding Rounds: Amplifying the Growth

Solana's journey continued with additional funding rounds, each contributing to the project's growth and increasing the potential for substantial returns. In June 2018, Solana raised $12 million at 20 cents per token shortly before launching its private test net. 

In July 2019, another funding round resulted in over $5 million raised at 22.5 cents per token, just before the public test net launch. Finally, in February 2020, right before the main net launch, an additional $2.4 million was raised at 25 cents per token.

Matic (Polygon): A Case Study in Launchpad Success

Another avenue to achieve 100x returns in crypto is through launchpads, which provide opportunities for retail investors to participate in early-stage projects. 

One such success story is Matic, now known as Polygon, which launched through the Binance Launchpad. By analyzing Matic's journey, we can understand how early investors achieved impressive returns.

Seed Investor Success: Reaping the Rewards

Seed investors who got in early on Matic received the tokens for 0.0079, which proved to be an incredible bargain. With the all-time high reaching almost 300x the seed price, seed investors who held their tokens experienced a staggering 3700x return. Turning $10,000 into $37 million showcases the potential for substantial gains through early-stage investments.

Retail Investors: Seizing the Opportunity

Retail investors who participated in the Binance Launchpad event for Matic also reaped significant rewards. With a launchpad sale price of 0.00263, retail investors achieved a remarkable 1100x return if they held their tokens until the all-time high. 

Even with a modest investment of $300, these retail investors saw their holdings grow to over $300,000, demonstrating the potential for 100x returns through launchpad participation.

How to Make 100x via Mining?

Mining cryptocurrencies can be another avenue to achieve 100x returns. By dedicating computing power to secure blockchain networks, miners are rewarded with newly minted tokens. One project that exemplifies the potential for significant returns through mining is Helium.

Helium: Mining the Path to Profits

Helium is a project that enables individuals to mine tokens by sharing their internet connection through specialized devices called hotspots. By participating in the Helium network, miners earn HNT tokens as a reward. 

With the all-time high price of HNT reaching almost $55, early miners experienced a remarkable 500x return on their investment. This showcases the potential for substantial gains through mining endeavors in the crypto market.

How to Make 100x in a Bear Market?

While the crypto market can be volatile, it's still possible to achieve 100x returns even in bearish conditions. One project that exemplifies the potential for significant gains during a bear market is Kaspa.

Kaspa: Profiting in a Downturn

Kaspa is a proof-of-work blockchain project that experienced a 100x return during a bear market. Despite the challenging market conditions, Kaspa's fair launch approach and favorable economics allowed early investors to achieve substantial returns. 

With the all-time low price of 0.00017 and the all-time high reaching $0.05, investors who held their positions saw their investments multiply by 100x.

Crypto Quality: Assessing Fundamentals and Technology

When investing in cryptocurrencies, it's crucial to assess the quality of the underlying projects. Evaluating the fundamentals and technology behind a crypto asset provides valuable insights into its potential for growth.

Fundamentals: The Foundation of Success

Examining the fundamentals of a crypto asset involves analyzing factors such as on-chain traction, active wallets, community size, and the team's background. By understanding the project's fundamentals, investors can gain confidence in its long-term viability and growth potential.

Technology: The Backbone of Innovation

The technological aspect of a crypto project is equally important. Assessing factors such as developer activity, security audits, and code quality provides insights into the project's technical robustness. A solid technological foundation indicates the potential for innovation and long-term success.

Crypto Tokenomics: Evaluating Long-Term Value

Understanding the tokenomics of a crypto asset is crucial for identifying its long-term value. By analyzing supply and demand dynamics, economic incentives, and the token's utility within the ecosystem, investors can assess whether the asset is worth holding for the long term.

Supply and Demand Dynamics: Striking a Balance

Analyzing the supply and demand dynamics of a crypto asset is essential to gauge its growth potential. 

A balanced supply and demand relationship ensures stability and sustainable value appreciation. Factors such as token issuance mechanisms and token utility within the ecosystem play a significant role in determining the asset's potential.

Economic Incentives: Driving Value Creation

Economic incentives within a crypto ecosystem are vital for driving value creation. By examining factors such as staking rewards, token burns, and revenue-sharing mechanisms, investors can gain insights into the potential for token appreciation. Projects with well-designed economic models attract long-term investors and create a strong foundation for growth.

Crypto Valuation: Finding Undervalued Gems

Identifying undervalued crypto assets is the key to achieving substantial returns. By comparing the fully diluted valuation (FDV) with the market capitalization, investors can identify potential discrepancies in the market's pricing. 

Additionally, analyzing the asset's valuation compared to its competitors within the sector provides valuable insights into its growth potential.

Finding the Margin of Safety

Value investing principles can be applied to crypto asset valuation. By identifying assets with a margin of safety, investors can capitalize on market mispricing and achieve significant returns. 

Buying assets below their intrinsic value provides a buffer against market fluctuations and sets the stage for substantial gains.

Injective Protocol vs. SEI Network: A Comparative Analysis

To illustrate the importance of valuation, let's compare two projects: Injective Protocol and SEI Network. By analyzing their respective valuations and market positions, we can gain insights into their growth potential.

Injective Protocol: Unleashing the Power of Decentralized Exchanges

Injective Protocol aims to revolutionize the decentralized exchange landscape. With a fully diluted valuation of $1.2 billion and a market capitalization of $400 million, there is room for growth. 

Analyzing the project's fundamentals, technology, and competitive landscape provides valuable insights into its potential for value appreciation.

SEI Network: Tapping into the Power of NFTs

SEI Network focuses on the non-fungible token (NFT) space, aiming to bring unique digital assets to the forefront. 

With a fully diluted valuation of $200 million and a market capitalization of $100 million, SEI Network is undervalued compared to its competitors. Assessing the project's fundamentals, technology, and market positioning provides valuable insights into its growth potential.

Best 100x Crypto Picks

Based on the strategies outlined and the analysis conducted, I am excited to share my 100x crypto picks. These picks represent projects that exhibit strong fundamentals, promising tokenomics, and the potential for significant valuation growth.

  • Solana (SOL): With its impressive track record of delivering 1000x returns to early VC investors, Solana remains a top contender for substantial gains.
  • Polygon (MATIC): Formerly known as Matic, Polygon achieved remarkable returns through its launchpad event on Binance. Retail investors who participated in the event experienced 1000x returns.
  • Helium (HNT): By participating in the Helium network and mining HNT tokens, early miners achieved impressive returns of 500x.
  • Kaspa (KAS): Despite a bearish market, Kaspa demonstrated the potential for 100x returns through its fair launch approach.

Conclusion

Making money in the crypto market requires strategic thinking, thorough analysis, and a willingness to take calculated risks. By focusing on quality projects, evaluating tokenomics, and identifying undervalued assets, investors can position themselves for substantial gains. 

However, it's essential to conduct thorough due diligence and stay informed about market trends and developments. With the knowledge and strategies outlined in this guide, you are well-equipped to navigate the crypto market and unlock the potential for 100x returns.

Disclaimer

The information provided on this website does not constitute investment advice, financial advice, trading advice, or any other advice, and you should not treat any of the website's content as such.

Token Metrics does not recommend that any cryptocurrency should be bought, sold, or held by you. Conduct your due diligence and consult your financial advisor before making investment decisions.

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Token Metrics Team
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Recent Posts

Research

A Complete Guide to Writing Smart Contracts

Token Metrics Team
4
MIN

Introduction

Smart contracts are self-executing contracts with the terms of the agreement directly written into lines of code. They run on blockchain platforms, such as Ethereum, enabling decentralized, automated agreements that do not require intermediaries. Understanding how to write a smart contract involves familiarity with blockchain principles, programming languages, and best practices for secure and efficient development.

Understanding Smart Contracts

Before diving into development, it is essential to grasp what smart contracts are and how they function within blockchain ecosystems. Essentially, smart contracts enable conditional transactions that automatically execute when predefined conditions are met, providing transparency and reducing dependency on third parties.

These programs are stored and executed on blockchain platforms, making them immutable and distributed, which adds security and reliability to the contract's terms.

Choosing the Right Platform

Writing a smart contract starts with selecting an appropriate blockchain platform. Ethereum is among the most widely used platforms with robust support for smart contracts, primarily written in Solidity—a statically-typed, contract-oriented programming language.

Other platforms like Binance Smart Chain, Polkadot, and Solana also support smart contracts with differing languages and frameworks. Selecting a platform depends on the project requirements, intended network compatibility, and resource accessibility.

Learning the Programming Language

The most commonly used language for writing Ethereum smart contracts is Solidity. It is designed to implement smart contracts with syntax similar to JavaScript, making it approachable for developers familiar with web programming languages.

Other languages include Vyper, a pythonic language focusing on security and simplicity, and Rust or C++ for platforms like Solana. Learning the syntax, data types, functions, and event handling of the chosen language is foundational.

Setting Up Development Environment

Development of smart contracts typically requires a suite of tools for editing, compiling, testing, and deploying code:

  • IDEs: Integrated Development Environments such as Remix (web-based for Solidity) or Visual Studio Code with plugins.
  • Frameworks: Tools like Truffle or Hardhat enable local blockchain simulation, automated testing, and deployment scripts.
  • Node and Wallet: Connecting to blockchain networks often requires running a node or leveraging services like Infura, along with digital wallets (e.g., MetaMask) for transaction signing.

Writing the Smart Contract Code

Writing a smart contract involves structuring the code to define its variables, functions, and modifiers. Key steps include:

  1. Define the contract: Use the keyword contract to declare the contract and its name.
  2. Declare state variables: Define data stored on the blockchain, such as balances or ownership details.
  3. Write functions: Implement logic that changes state variables or triggers events.
  4. Use modifiers: Add conditional checks like access restrictions (e.g., only the owner can execute certain functions).
  5. Emit events: Use events to log significant contract operations for off-chain monitoring.

Example snippet in Solidity:

pragma solidity ^0.8.0;

contract SimpleStorage {
  uint storedData;

  function set(uint x) public {
    storedData = x;
  }

  function get() public view returns (uint) {
    return storedData;
  }
}

Testing and Debugging

Testing is crucial to ensure smart contracts operate as intended and to prevent bugs or vulnerabilities. Strategies include:

  • Writing unit tests using frameworks like Truffle or Hardhat.
  • Running tests on local blockchains (Ganache) before deploying.
  • Using linters and analysis tools to detect common security issues.

Adopting rigorous testing can reduce the risk of exploits or loss of funds caused by contract errors.

Deploying the Smart Contract

Deployment involves publishing the compiled smart contract bytecode to the blockchain. This includes:

  • Compiling the contract into bytecode.
  • Connecting to the desired blockchain network (testnet or mainnet) usually via wallet integration.
  • Submitting a deployment transaction, which requires gas fees for execution.

Using test networks like Ropsten, Rinkeby, or Goerli is recommended for initial deployment to validate functionality without incurring real costs.

Using AI Tools for Smart Contract Research

Emerging AI-driven platforms can assist developers and analysts with smart contract evaluation, security analysis, and market sentiment interpretation. For instance, tools like Token Metrics provide algorithmic research that can support understanding of blockchain projects and smart contract implications in the ecosystem.

Integrating these tools along with manual audits aids comprehensive assessments for better development decisions.

Best Practices and Security Considerations

Writing secure smart contracts requires awareness of common vulnerabilities such as reentrancy attacks, integer overflows, and improper access controls. Best practices include:

  • Following established design patterns and standards (e.g., OpenZeppelin contracts).
  • Performing thorough code reviews and external audits.
  • Keeping contracts as simple and modular as possible.

Robust security practices are critical due to the immutable nature of deployed smart contracts on blockchain.

Conclusion

Writing a smart contract involves a combination of blockchain knowledge, programming skills, and adherence to security best practices. From choosing a platform and language to coding, testing, and deploying, each step plays an important role in the development lifecycle.

Leveraging AI-powered tools like Token Metrics can add valuable insights for developers aiming to enhance their understanding and approach to smart contract projects.

Disclaimer

All information provided in this article is for educational purposes only and does not constitute financial or investment advice. Readers should conduct their own research and consult professional sources where appropriate.

Research

Understanding the Risks of AI Controlling Decentralized Autonomous Organizations

Token Metrics Team
4
MIN

Introduction

Decentralized Autonomous Organizations (DAOs) represent an innovative model for decentralized governance and decision-making in the blockchain space. With the increasing integration of artificial intelligence (AI) into DAOs for automating processes and enhancing efficiency, it is vital to understand the risks associated with allowing AI to control or heavily influence DAOs. This article provides a comprehensive analysis of these risks, exploring technical, ethical, and systemic factors. Additionally, it outlines how analytical platforms like Token Metrics can support informed research around such emerging intersections.

DAO and AI Basics

DAOs are blockchain-based entities designed to operate autonomously through smart contracts and collective governance, without centralized control. AI technologies can offer advanced capabilities by automating proposal evaluation, voting mechanisms, or resource allocation within these organizations. While this combination promises increased efficiency and responsiveness, it also introduces complexities and novel risks.

Technical Vulnerabilities

One significant category of risks involves technical vulnerabilities arising from AI integration into DAOs:

  • Smart Contract Exploits: AI-driven decision-making typically operates on smart contracts. Flaws or bugs in the smart contract code can be exploited, possibly amplified by AI’s autonomous execution.
  • Data Integrity and Quality: AI requires reliable data inputs to function correctly. Malicious actors might inject false or biased data, leading to misguided AI decisions that could harm DAO operations.
  • Algorithmic Errors: AI algorithms might contain bugs, incorrect assumptions, or be insufficiently tested, which could result in unintended behaviors or decisions with negative consequences.

Governance and Control Challenges

Integrating AI into DAO governance raises complex questions around control, transparency, and accountability:

  • Lack of Transparency: AI algorithms, especially those using complex machine learning models, can be opaque, making it difficult for stakeholders to audit decisions or understand governance processes fully.
  • Centralization Risks: AI models are often developed and maintained by specific teams or organizations, which could inadvertently introduce centralization points contrary to the decentralized ethos of DAOs.
  • Unintended Bias: AI systems trained on biased datasets may propagate or exacerbate existing biases within DAO decision-making, risking unfair or harmful outcomes.

Security and Manipulation Risks

The autonomous nature of AI presents unique security concerns:

  • Manipulation Attacks: Adversaries might target the AI’s learning process or input data channels to manipulate outcomes toward malicious goals.
  • Autonomy Exploits: An AI controlling critical DAO functions autonomously could make decisions that are difficult to reverse or disrupt, leading to lasting damage if exploited.
  • Emergent Behavior: Complex AI systems might develop unexpected behaviors in dynamic environments, creating risks hard to anticipate or control within DAO frameworks.

Ethical and Regulatory Concerns

Beyond technical risks, the interaction between AI and DAOs also introduces ethical and regulatory considerations:

  • Accountability Gaps: Determining liability for AI-driven decisions within DAOs is challenging, potentially leading to accountability voids in cases of harm or disputes.
  • Compliance Complexity: Evolving regulatory landscapes surrounding both AI and blockchain could create overlapping or conflicting requirements for AI-controlled DAOs.
  • User Consent and Autonomy: Members participating in DAOs may have concerns over how AI influences governance and whether adequate consent frameworks are in place.

Mitigating Risks with Analytical Tools

Understanding and managing these risks require robust research and analytical frameworks. Platforms such as Token Metrics provide data-driven insights supporting comprehensive evaluation of blockchain projects, governance models, and emerging technologies combining AI and DAOs.

  • Thorough Technical Reviews: Regular audits and reviews of AI algorithms and smart contracts can detect vulnerabilities early.
  • Transparency Initiatives: Employing explainable AI methods enhances trust and allows stakeholder scrutiny.
  • Scenario Analysis: Exploring potential failure modes and adversarial scenarios helps prepare for unexpected outcomes.
  • Community Engagement: Active and informed participation in DAO governance ensures more robust checks and balances.

Conclusion

The fusion of AI and DAOs promises innovative decentralized governance but comes with substantial risks. Technical vulnerabilities, governance challenges, security threats, and ethical concerns highlight the need for vigilant risk assessment and careful integration. Utilizing advanced research platforms like Token Metrics enables more informed and analytical approaches for stakeholders navigating this evolving landscape.

Disclaimer

This article is for educational purposes only and does not constitute financial, legal, or investment advice. Readers should perform their own due diligence and consult professionals where appropriate.

Research

How AI Enhances Vulnerability Detection in Smart Contracts

Token Metrics Team
4
MIN

Introduction: The Growing Concern of Smart Contract Vulnerabilities

Smart contracts are self-executing contracts with the terms directly written into code, widely used across blockchain platforms to automate decentralized applications (DApps) and financial protocols. However, despite their innovation and efficiency, vulnerabilities in smart contracts pose significant risks, potentially leading to loss of funds, exploits, or unauthorized actions.

With the increasing complexity and volume of smart contracts being deployed, traditional manual auditing methods struggle to keep pace. This has sparked interest in leveraging Artificial Intelligence (AI) to enhance the identification and mitigation of vulnerabilities in smart contracts.

Understanding Smart Contract Vulnerabilities

Smart contract vulnerabilities typically arise from coding errors, logic flaws, or insufficient access controls. Common categories include reentrancy attacks, integer overflows, timestamp dependencies, and unchecked external calls. Identifying such vulnerabilities requires deep code analysis, often across millions of lines of code in decentralized ecosystems.

Manual audits by security experts are thorough but time-consuming and expensive. Moreover, the human factor can result in missed weaknesses, especially in complex contracts. As the blockchain ecosystem evolves, utilizing AI to assist in this process has become a promising approach.

The Role of AI in Vulnerability Detection

AI techniques, particularly machine learning (ML) and natural language processing (NLP), can analyze smart contract code by learning from vast datasets of previously identified vulnerabilities and exploits. The primary roles of AI here include:

  • Automated Code Analysis: AI models can scan codebases rapidly to detect patterns indicative of security flaws.
  • Anomaly Detection: AI can recognize atypical or suspicious contract behaviors that deviate from standard practices.
  • Predictive Assessment: By using historical vulnerability data, AI can predict potential risk points in new contracts.
  • Continuous Learning: AI systems can improve over time by incorporating feedback from newly discovered vulnerabilities.

Techniques and Tools Used in AI-Driven Smart Contract Analysis

Several AI-based methodologies have been adopted to aid vulnerability detection:

  1. Static Code Analysis: AI algorithms break down smart contract code without execution, identifying syntactic and structural weaknesses.
  2. Dynamic Analysis and Fuzzing: Leveraging AI to simulate contract execution in varied scenarios to uncover hidden vulnerabilities.
  3. Graph Neural Networks (GNNs): Applied to model relational data within smart contract structures, improving detection of complex vulnerabilities.
  4. Transformer Models: Adapted from NLP, these analyze code semantics to spot nuanced issues beyond basic syntax errors.

Some emerging platforms integrate such AI techniques to provide developers and security teams with enhanced vulnerability scanning capabilities.

Advantages of AI Over Traditional Auditing Methods

Compared to manual or rule-based approaches, AI provides several notable benefits:

  • Scalability: AI can analyze thousands of contracts quickly, which manual teams cannot feasibly match.
  • Consistency: AI reduces human error and subjective assessment variability in vulnerability identification.
  • Real-Time Analysis: AI-powered systems can run continuous scans and provide rapid alerts for emerging threats.
  • Cost Efficiency: Automating portions of the audit process can reduce resource expenditure over time.

Despite these advantages, AI is complementary to expert review rather than a replacement, as audits require contextual understanding and judgment that AI currently cannot fully replicate.

Challenges and Limitations of AI in Smart Contract Security

While promising, AI application in this domain faces several hurdles:

  • Data Quality and Availability: Training AI models requires large, well-labeled datasets of smart contract vulnerabilities, which are limited due to the relative novelty of the field.
  • Complexity of Smart Contracts: Diverse programming languages and design patterns complicate uniform AI analysis.
  • False Positives/Negatives: AI may generate incorrect alerts or miss subtle vulnerabilities, requiring human validation.
  • Adversarial Adaptation: Malicious actors may develop exploits specifically designed to evade AI detection models.

How to Use AI Tools Effectively for Smart Contract Security

Developers and security practitioners can optimize the benefits of AI by:

  • Integrating AI Reviews Early: Employ AI analysis during development cycles to detect vulnerabilities before deployment.
  • Combining with Manual Audits: Use AI as a preliminary screening tool, followed by detailed human assessments.
  • Continuous Monitoring: Monitor deployed contracts with AI tools to detect emergent risks or unexpected behaviors.
  • Leveraging Platforms: Utilizing platforms such as Token Metrics that provide AI-driven analytics for comprehensive research on smart contracts and related assets.

Conclusion & Future Outlook

AI has a growing and important role in identifying vulnerabilities within smart contracts by providing scalable, consistent, and efficient analysis. While challenges remain, the combined application of AI tools with expert audits paves the way for stronger blockchain security.

As AI models and training data improve, and as platforms integrate these capabilities more seamlessly, users can expect increasingly proactive and precise identification of risks in smart contracts.

Disclaimer

This article is for educational and informational purposes only. It does not constitute financial, investment, or legal advice. Always conduct your own research and consider consulting professionals when dealing with blockchain security.

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