《分形统计分析与反馈交易策略》以分形统计分析与反馈交易策略为研究主题，旨在利用分形统计分析方法，构建反馈交易策略，探究相关应用问题；既发展了研究主题，也丰富了研究视角，还改进了研究方法；既有助于完善量化投资和金融决策理论，也有助于促进物理金融和行为金融的交叉协同，还有助于为理论研究者和实务工作者提供参考；具有重要的理论价值和深远的现实意义。
Let's get this straight， the core question studied in this book is how to use fractal statistical analysis to optimize feedback trading strategies.
At all times and in all over the world， money never sleeps. Many people were attracted by securities investment， until the security market came out. Hence， securities investment strategy is valued highly for investment profit. It not exaggeration to say， optimizing securities investment strategy has become an enduring research project.
Any securities investment strategies cannot be separated from the support of market phenomenon. If an investment strategy were divorced from the market phenomenon， it might be like an ivory tower. Eventually， this strategy will fail to acclimatize itself to the actual market and be difficult to be used in investment practice. As we all know， the fundamental purpose of studying securities investment strategies is to serve the practice of securities investment. Consequently， when we study the theory of securities investment strategies， we must consider the application value of investment strategies. In order to ensure investment strategies' broad application scenarios， not only should it be based on the real phenomenon of the securities market， but also the market phenomenon based on it should be universal.
吴栩，管理学博士，现为成都理工大学副教授、硕士生导师，第十三批四川省学术和技术带头人后备人选，国家自然科学基金管理科学部通讯评审专家，四川省科技计划项目（课题）评审专家，重庆市科技计划项目（课题）评审专家。自在华南理工大学攻读博士学位至今，长期从事分形统计分析、量化投资策略和企业融资困境方面的研究。在Nonlinear Dynamics、Journal of Computational and Applied Mathematics、Fractals-Complex Geometry Patterns and Scaling in Nature and Society、《管理评论》和《运筹与管理》等国家自然科学基金委管理科学部认定的重要期刊、CSSCI来源期刊、SCI检索期刊、SSCI检索期刊等学术刊物上发表论文30余篇：主持国家自然科学基金青年项目、教育部人文社会科学青年项目等国家、省部级5项；在科学出版社出版学术专著1部；出版《金融经济学》（西南财经大学出版社，2020年版）教材1部：部分学术论文已获得四川省教育厅第十二届哲学社会科学科研成果三等奖、广东金融学会第十届优秀金融科研成果三等奖、四川省第十八次社会科学优秀成果三等奖等。
1 Introduction
1．1 Core research question
1．2 Explicate key concepts
1．3 Research significance
1．4 Main research contents
1．5 Structure arrangement
2 Fractal Statistics and Fractal Markets
2．1 Mathematical basis of fractal statistics
2．1．1 Mathematical basis of fractal theory
2．1．2 From fractal theory to fractal statistics
2．2 Fractal series and fractal distribution
2．2．1 Fractal time series and fractal correlations
2．2．2 Fractal distribution and statistical measures
2．3 Evolution of fractal market theory
2．3．1 Background and content of fractal market theory
2．3．2 From monofractal market to multifractal market
2．4 Empirical test of multifractal market
2．4．1 Test methods of multifractal market
2．4．2 Test results of multifractal market
2．5 Brief summary and necessary explanations
……
3 Feedback Trading in Fractal Markets
4 Distributed Fractal Feedback Trading Strategies
5 Correlated Fractal Feedback Trading Strategies
6 Fractal Adaptive Feedback Trading Strategies
7 Research Conclusions and Research Expectations
Main References
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