t5_Sophisticated Algorithmic Strategies(MeanReversion+APO+StdDev_TrendFollowing+APO)_StatArb统计套利_PnL

已于 2024-06-12 07:30:29 修改
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分类专栏： pythonForFinance2 文章标签： 大数据
于 2021-12-26 19:51:50 首次发布
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本文链接：https://blog.youkuaiyun.com/Linli522362242/article/details/121896073
本篇内容探讨了算法交易中更复杂的策略，包括如何构建针对交易工具波动调整的策略。内容涉及波动性调整的技术指标、经济事件的交易策略以及统计套利交易策略的基础。通过动态适应价格波动，改善盈利能力和降低风险暴露。讨论了波动性在均值回复和趋势跟踪策略中的应用，并展示了如何将波动性指标纳入交易信号和策略中，以提高策略的适应性。

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     we will explore more sophisticated[səˈfɪstɪkeɪtɪd] 复杂的 trading strategies employed by leading market participants in the algorithmic trading business. We will build on top of the basic algorithmic strategies and learn about more advanced approaches (such as statistical arbitrage[ˈɑːrbɪtrɑːʒ]套利 and pair correlation) and their advantages and disadvantages. We will learn how to create a trading strategy that adjusts for trading instrument volatility. We will also learn how to create a trading strategy for economic events and understand and implement the basics of statistical arbitrage trading strategies.

This chapter will cover the following topics:

  • Creating a trading strategy that adjusts for trading instrument volatility
  • Creating a trading strategy for e
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