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Wyckoff Method in Crypto Trading
April 10, 2025
The article explains how traders apply the Wyckoff Method to crypto markets, identifying accumulation, distribution, and trend shifts based on price and volume structure. It outlines key principles, market phases, and examples using Bitcoin and altcoins to detect institutional activity and improve trade timing in digital asset markets.
Turtle Strategy in Crypto Markets
April 8, 2025
The article explores how the classic Turtle Trading Strategy can be adapted for the cryptocurrency market. It explains the original system’s principles—breakouts, volatility-based sizing, and risk control—and shows how traders are applying it to Bitcoin and altcoins today. The piece includes practical examples, backtesting results, and implementation insights for systematic crypto trading.
Ethereum in 2025: Network, Usage, and Upgrades
April 3, 2025
The article provides a detailed update on Ethereum as of March 2025, covering its validator architecture, staking trends, rollup usage, protocol upgrades, and institutional adoption across finance, custody, and tokenization.
A Practical Overview of Crypto Trading Order Types
April 1, 2025
The article offers an advanced analysis of all order types in cryptocurrency trading across both spot and derivatives markets, including market, limit, stop-loss, stop-limit, trailing stop, OCO, iceberg, TWAP, VWAP, and others. It explains their mechanics, use cases, associated risks, and implementation differences across centralized (CEX) and decentralized (DEX) platforms. A comparative table highlights execution speed, slippage, and strategy suitability, providing valuable insights for institutional traders, quant developers, and experienced retail participants.
Multi-Agent Deep Q-Learning for Trading Strategy Optimization
March 27, 2025
This article presents a multi-agent Deep Q-Learning framework for developing adaptive trading strategies across multiple cryptocurrencies. By training separate agents with varied decision models on shared historical data, the approach enables improved prediction accuracy, strategy diversification, and dynamic decision-making. Empirical results on assets like BTC, ETH, and XRP show superior performance over traditional buy-and-hold strategies under diverse market conditions, including uptrends, downtrends, and sideways movements.
How Reservation Strategies Shape Optimal Trading
March 25, 2025
This article explains how brokers can optimize order execution under uncertainty while following client-imposed reservation strategies like TWAP or IS. Using a utility-maximizing framework and extensions of the Almgren-Chriss model, it shows how to balance market impact, execution risk, and benchmark tracking. Simulations demonstrate improved performance compared to TWAP strategies, offering insights into adaptive, risk-aware execution under real-world conditions.
Risk-Aware Linear Bandits in Algorithmic Trading
March 20, 2025
This article explores the application of risk-aware linear bandits in smart order routing (SOR), focusing on how the RISE and RISE++ algorithms optimize order execution across multiple trading venues. By balancing reward maximization with risk control, these models improve execution quality, reduce transaction costs, and enhance adaptability to changing market conditions. The article also examines empirical validation using NASDAQ ITCH data, demonstrating the effectiveness of risk-aware bandits in real-world trading environments.
Optimizing Cross-Chain Arbitrage in Decentralized Exchanges
March 18, 2025
This article explores the concept of cross-chain arbitrage in decentralized exchanges, focusing on the mechanics of arbitrage opportunities between PancakeSwap on the BNB Chain and QuickSwap on Polygon. It examines the impact of transaction costs, liquidity dynamics, and blockchain interoperability, providing insights into the challenges and potential profitability of executing cross-chain arbitrage strategies in decentralized finance.
State-Dependent Stochastic Models for Fill Probability Estimation
March 12, 2025
The article explores the concept of fill probability in limit order books and how state-dependent stochastic models provide more accurate predictions for traders. By considering dynamic factors like liquidity and volatility, these models offer a better understanding of order flow and execution risks, ultimately helping to optimize trading strategies and reduce transaction costs.
Axon Trade Partners With Elven
March 11, 2025
Elven and Axon Trade are joining forces to improve institutional trading infrastructure. This partnership delivers deep liquidity, low-latency execution, and seamless integration for professional traders. With a focus on stability and performance, the collaboration provides robust connectivity, advanced order routing, and reliable market access across multiple asset classes.
100 Books for Algorithmic Trading Professionals - Part 7: Trading Psychology
March 10, 2025
This article covers books that explore the psychological aspects of trading, from managing risk and handling stress to recognizing biases that impact financial choices. Topics include discipline, mental resilience, and strategies for maintaining focus in volatile markets. Traders will find insights from psychology, neuroscience, and behavioral finance to improve performance and build confidence.
100 Books for Algorithmic Trading Professionals - Part 6: Case Studies and Real-World Stories
March 5, 2025
History shapes modern trading. This article presents a selection of books that explore real-world case studies of algorithmic trading, financial crises, and market manipulation. From high-frequency trading to the rise of crypto, these books reveal the decisions and events that redefined global finance. Traders, analysts, and investors will gain insights into how markets evolve, the impact of hedge funds, and the role of technology in reshaping financial systems.
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