Macro trading is not an exclusive language of traditional finance—it is equally effective in the crypto market. As the market evolves from a single-narrative framework toward institutionalization and globalization, price fluctuations are increasingly shaped by the combined influence of interest rate paths, dollar strength, and shifts in risk appetite. Understanding this transmission mechanism helps you identify trends earlier in high-volatility environments, reduce emotional trading, and upgrade your perspective from "watching the market" to "building a framework."
Price fluctuations in the crypto market are driven not only by fundamentals and liquidity but are also highly influenced by sentiment and narratives. A policy statement, a trending social media topic, or an on-chain whale transaction can all shift market expectations and redirect capital flows in a short period of time. This course systematically explains the transmission mechanism from "sentiment → narrative → price" and focuses on answering a key practical question: how to transform seemingly subjective, discrete, and noisy information into trackable, verifiable, and actionable trading signals.
The essence of financial markets goes beyond the mere buying and selling of assets—it is the reallocation of risk, expectations, and capital efficiency. As a critical infrastructure of modern finance, derivatives have deeply influenced global capital flows, asset pricing, and investment strategy design. As markets evolve from single-asset trading to multi-asset, globalized, and digitalized frameworks, understanding derivatives and the underlying market structure has become an essential competency for modern investors and traders.
This course explores how AI agents are transforming on-chain trading by connecting data analysis, strategic decision-making, and automated execution. Students will gain a clear understanding of this technology and its capabilities, as well as the evolving role of AI in the crypto market. From market monitoring to risk management, the course demonstrates how AI can function both as a tool and as an active participant. Upon completion, students will be able to understand AI's systemic impact on trading efficiency, security, and multi-chain ecosystems.
This course will start from market analysis and progressively extend to strategy construction, backtesting validation, automated execution, and risk control monitoring, helping learners understand how AI can truly improve the quality of trading decisions—beyond merely providing the superficial ability to "predict price movements." At the same time, the course will also explore, through platform-based infrastructure (such as Gate for AI), how AI capabilities can be more efficiently deployed into real-world trading scenarios.
As the crypto market gradually undergoes structural integration with the traditional financial system, "tokenized stocks" are transitioning from conceptual exploration to practical experimentation. Tokenized stocks do not merely represent a change in the form of trading U.S. stocks. They entail a systematic restructuring of asset issuance methods, trading hours, and market accessibility. They show the crypto world's genuine demand for compliant assets, and also highlight the inherent boundaries of on-chain finance in terms of law, custody, and rights mapping. Understanding tokenized stocks essentially means understanding how TradFi and Crypto compromise, reorganize, and coexist with each other.
This course will systematically introduce the core concepts, operating mechanisms, and common classifications of AI Agents, and explain why they are becoming an important infrastructure in blockchain applications. Starting from the definition, capability boundaries, and technical components of Agents, the course will gradually extend to key scenarios such as on-chain wallets, smart contracts, data oracles, automated execution, and multi-agent collaboration.
Financial derivatives are among the most important—and most easily misunderstood—tools in modern markets. From agricultural futures for hedging, to risk management of interest rates, exchange rates, and stock indices, to futures, options, and perpetual swaps in the crypto market, derivatives all revolve around a single core objective: redistributing and managing risk. This course will systematically introduce the fundamental logic, major types, market functions, and participant structures of derivatives, and further explain how these tools extend from traditional finance into the rapidly evolving crypto derivatives market.
Prediction markets are a unique market mechanism that discovers probabilities and information by trading the outcomes of future events. This course will guide you from foundational concepts to understanding how prices reflect event probabilities, and how information, sentiment, and arbitrage influence the market. We will also dive into the operational mechanisms of on-chain prediction markets, including smart contracts, oracles, and liquidity design. Finally, you will learn how prediction markets can expand into information markets and potentially become a critical infrastructure for future finance and governance.
The data structure of the cryptocurrency market is complex, multi-sourced, and highly dynamic, making traditional analytical methods difficult to apply. Artificial Intelligence (AI) is becoming the core engine that connects data, decision-making, and trade execution, spanning the entire trading process from signal extraction to strategy optimization. This course will help you understand the critical role of AI in crypto trading, and how to achieve precise decision-making and execution optimization in a high-noise market. Through systematic learning, you will master the complete intelligent workflow from data analysis to trade execution.
In the early stages of the crypto market, price fluctuations were primarily driven by spot trading and capital inflows, with a relatively simple market structure. However, with the rapid development of the derivatives market, leverage has gradually become the dominant force, profoundly reshaping how the market operates. Today, products such as perpetual swaps, margin trading, and leveraged ETFs account for the majority of trading volume, marking the market’s transition into a leverage-centric phase. Within this structure, price movements are no longer determined solely by supply and demand, but are increasingly influenced by position structures, funding rates, and liquidation mechanisms. Many sharp fluctuations are triggered not by news or fundamentals, but by changes in leverage structures and cascading liquidations.
With the rapid development of blockchain applications, performance bottlenecks have increasingly become a core issue limiting large-scale adoption. Against this backdrop, Layer 2 emerged as a critical scaling solution. Rather than simply boosting base-layer performance, Layer 2 achieves efficiency gains through architectural innovation without sacrificing security or decentralization. This course begins with the fundamental contradictions of blockchain scaling and systematically analyzes the design logic and technical paths of Layer 2. By understanding these mechanisms, you will gain a clearer insight into the evolutionary direction of current blockchain infrastructure.
Web3 is not merely a collection of blockchain or cryptocurrency technologies; rather, it represents a new system of assets, ownership, and market structures. From private keys controlling assets, to smart contracts defining rules, to the formation of on-chain finance and token economies, this system is reshaping how value is created and transferred. With the integration of AI, Web3 is evolving from being merely "usable" to becoming "understandable and actionable," entering a new phase known as Intelligent Web3. This course aims to provide a structured understanding of this system as a whole.
With Bitcoin and Ethereum ETFs officially entering the mainstream financial system, the crypto market is transitioning from being “trading-driven” to “allocation-driven.” ETFs are not just new investment instruments—they represent critical infrastructure that transforms the way capital enters the market, influences pricing mechanisms, and reshapes market segmentation.
In the digital world, "identity“ has long been treated merely as a login tool, while the power structures and trust mechanisms behind it were rarely examined. As Web3, decentralized finance, and on-chain governance continue to evolve, identity is no longer just a key for system access—it now carries credit, permissions, and value distribution. This course starts from that fundamental shift and guides you to rethink the evolving role of identity in digital society, exploring how decentralized identity becomes a critical foundation for rebuilding trust in Web3.
