摘要翻译：
在目前的工作中，我们解决了评估一个交易策略或某一资产组合的历史绩效的问题。夏普比率和风险调整后收益等常用指标都有明显的缺陷。特别是，它们是全球性指数，也就是说，它们不保留任何关于业绩动态的“本地”信息，无论是在时间上还是在特定的投资范围内。这些信息可能是从业者的基础，因为过去的表现可能受到金融市场非平稳性的影响。为了突出这一特点，我们引入了“局部风险分解”(LRD)形式，其中保留了关于策略性能的动态信息。该框架以复杂系统理论中的多尺度技术为基础，特别适用于高频交易系统，可以应用于策略优化问题。
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英文标题：
《Local Risk Decomposition for High-frequency Trading Systems》
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作者：
M. Bartolozzi and C. Mellen
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最新提交年份：
2011
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Risk Management        风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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英文摘要：
  In the present work we address the problem of evaluating the historical performance of a trading strategy or a certain portfolio of assets. Common indicators such as the Sharpe ratio and the risk adjusted return have significant drawbacks. In particular, they are global indices, that is they do not preserve any 'local' information about the performance dynamics either in time or for a particular investment horizon. This information could be fundamental for practitioners as the past performance can be affected by the non-stationarity of financial market. In order to highlight this feature, we introduce the 'local risk decomposition' (LRD) formalism, where dynamical information about a strategy's performance is retained. This framework, motivated by the multi-scaling techniques used in complex system theory, is particularly suitable for high-frequency trading systems and can be applied into problems of strategy optimization.
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PDF链接：
https://arxiv.org/pdf/0904.4099