Algorithmic Trading: Strategies for Optimizing Trade Execution
58:41
mathworks.com
Algorithmic Trading: Strategies for Optimizing Trade Execution
Practical examples and a case study using MATLAB’s recently released Transaction Cost Analysis (TCA) functions to help Portfolio Managers, Traders, and Analysts to develop strategies to reduce trading costs and better manage trading risk
2016年12月5日
Algorithmic Trading Strategies
📈 Unlock the Power of Algorithmic Trading! 🚀 Here are 5 Key Steps to Build Winning Strategies: 1️⃣ Determine your trading strategy: Nail down your approach, whether it's based on technical indicators, fundamental analysis, or a combo of both. 2️⃣ Statistically analyze the strategy: Use quantitative methods to assess historical performance, identifying patterns, trends, and risks for the asset. 3️⃣ Code Development: Translate your strategy into executable code with languages like Python or C .
0:54
📈 Unlock the Power of Algorithmic Trading! 🚀 Here are 5 Key Steps to Build Winning Strategies: 1️⃣ Determine your trading strategy: Nail down your approach, whether it's based on technical indicators, fundamental analysis, or a combo of both. 2️⃣ Statistically analyze the strategy: Use quantitative methods to assess historical performance, identifying patterns, trends, and risks for the asset. 3️⃣ Code Development: Translate your strategy into executable code with languages like Python or C .
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📈 Unlock the Power of Algorithmic Trading! 🚀 Here are 5 Key Steps to Build Winning Strategies: 1️⃣ Determine your trading strategy: Nail down your approach, whether it's based on technical indicators, fundamental analysis, or a combo of both. 2️⃣ Statistically analyze the strategy: Use quantitative methods to assess historical performance, identifying patterns, trends, and risks for the asset. 3️⃣ Code Development: Translate your strategy into executable code with languages like Python or C .
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