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2 posts tagged with "Trading Algorithms"

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Understanding Gradient Descent and Its Applications in Trading Algorithms

· 6 min read
Vadim Nicolai
Vadim Nicolai
Senior Software Engineer at Vitrifi

Introduction​

Gradient Descent is a fundamental optimization algorithm used in machine learning and quantitative finance. In the context of algorithmic trading, it helps in optimizing predictive models, from price forecasting to portfolio optimization. Understanding how Gradient Descent works and how it can be applied in the financial markets is crucial for developing effective trading strategies.

In this article, we will explore the concept of Gradient Descent, its variations, and its applications in trading.

Understanding Euclidean Distance and Its Applications in Trading Algorithms

· 5 min read
Vadim Nicolai
Vadim Nicolai
Senior Software Engineer at Vitrifi

Introduction​

Euclidean distance is not just a mathematical concept but a crucial tool for data analysis in various fields, including trading and quantitative finance. In algorithmic trading, Euclidean distance can be applied to evaluate the similarity between financial assets, identify trading signals, and optimize portfolio allocation. As a distance metric, it helps in quantifying the relationship between different financial data points, allowing for more effective trading strategies.

In this article, we will discuss what Euclidean distance is, how it's calculated, and where it fits in the world of financial markets and algorithmic trading.