高效的面边缘检测和定量的绩效考核 首先介绍递归过程为有效地计算三次面参数的边缘检测,这个过程可以通过计算在曲面参数方程,用固定数量的相互独立算子。 然后,我们引入一个独立的图像定量标准解析评测不同的边缘检测器(包括梯度和过零基础的方法)。
2023-01-06 08:55:37 225KB 高效边缘检测
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matlab分时代码定量宏观模型 这是我作为个人学习练习编写的定量宏观经济模型代码的集合。 除DSGE块外,所有代码均具有异构代理,并使用numba用python编写。 您可以在每个主题下找到不同的版本,在其中我可能会使用不同的计算方法,增加模型的规模和/或调整一些关键的假设。 我一直在努力使它们易于阅读和快速阅读,以便它们可以帮助对学习这些主题感兴趣的其他人。 可以在每个文件中找到使用的参考。 快速指南 异类家庭 相谷里 节省消费 异构企业/行业动态 霍本海恩 Restuccia和罗杰森 代表家庭 新古典主义的成长 RANK模型 相谷 具有不完整市场且没有总体不确定性的生产经济中的平稳均衡解。 异构代理无限期地生活,并面临着特殊收入的风险。 这些版本在解决家庭问题以及如何指定收入冲击过程方面有所不同。 所有版本的共享功能是 绘制财富分配,资本供求和政策功能图。 用户可以选择的外部借入约束。 除非另有说明,否则将使用蒙特卡洛模拟来近似平稳分布 代码和解决方法 值函数迭代 版本1-2-收入状态。 版本2-代码将复制Aiyagari(1994)。 稍有不同的是,使用Rouwenhorst方
2022-11-18 16:05:28 1.41MB 系统开源
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深度对冲演示 使用机器学习对衍生产品定价 1) Jupyter version: Run ./colab/deep_hedging_colab.ipynb on Colab. 2) Gui version: Run python ./pyqt5/main.py Check ./requirements.txt for main dependencies. Black-Scholes(BS)模型-于1973年开发,并基于获得诺贝尔奖的作品-在近半个世纪以来一直是定价选择和其他金融衍生品的事实上的标准。 在理想的金融市场的假设下,可以使用该模型来计算期权价格和相关的风险敏感性。 然后,交易者可以从理论上使用这些风险敏感性来创建完善的对冲策略,以消除期权组合中的所有风险。 但是,在现实世界中很难满足完美金融市场的必要条件,例如零交易成本和连续交易的可能性。 因此,在实践中,银行必须依靠其交
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Quantitative Trading with R : Understanding Mathematical and Computational Tools from a Quant's Perspective
2022-06-22 20:55:15 15.14MB Quantitative Trading R Understand
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(含google最新机器学习处理器介绍)True to its original mission of demystifying computer architecture, the sixth edition of Computer Architecture: A Quantitative Approach continues its longstanding tradition of focusing on the areas where the most exciting computing innovation is happening, while always keeping an emphasis on good engineering design.
2022-05-29 10:57:11 23.73MB 处理器
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Computer-Architecture-A-Quantitative-Approach 第五版(中文扫描+英文文字版),Hennessy & Patterson大神的著作。
2022-04-29 14:48:34 30.09MB CA:AQA 体系结构 量化研究方法 Hennessy
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高级计算机体系结构 用书(第五版)
2022-04-27 14:03:50 7.9MB 源码软件
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After the fundamental volume and the advanced technique volume, this volume focuses on R applications in the quantitative investment area. Quantitative investment has been hot for some years, and there are more and more startups working on it, combined with many other internet communities and business models. R is widely used in this area, and can be a very powerful tool. The author introduces R applications with cases from his own startup, covering topics like portfolio optimization and risk management. There are six chapters in this book, categorized into three parts: Financial Market and Financial Theory, Data Processing and High Performance Computing of R, and Financial Strategy Practice. Every chapter is a holistic knowledge system. Section One is Financial Market and Financial Theory (including Chapters 1 and 2), which starts with an understanding of finance to establish a basic idea of financial quantification. Chapter 1, Financial Market Overview, is the opening chapter of this book, which mainly introduces the ideas and methods of how to use R language to make quantitative investments. Chapter 2, Financial Theory, mainly introduces the classic theoretical models of finance and the R implementation methods. In Section Two, Data Processing and High Performance Computing of R (including Chapters 3 and 4), essential tools of R language for data processing and their usage are introduced in detail. Chapter 3, Data Processing of R, cored with the data processing technology of R, introduces the methods of processing different types of data with R language. In Chapter 4, High Performance Computing of R, three external technologies are introduced to help the performance of R language meet the production environment requirements. Section Three, Financial Strategy Practice (including Chapters 5 and 6), combines the R language technology and the financial market rules to solve the practical problems in financial quantification field. In Chapter 5, Bonds and Repurchase, readers can learn the market and the methods of low-risk investment. In Chapter 6, Quantitative Investment Strategy Cases, the investment research methods from theory to practice are introduced in whole. Since knowledge of different areas is comprehensively applied in this book, it is suggested that you read all the chapters in order. Some of the technical implementations mentioned in this book use the information from the other two books of the series, R for Programmers: Mastering the Tools and R2 for Programmers: Advanced Techniques, so it is recommended that you read those two as well.
2022-02-25 23:29:44 17.57MB r语言 量化投资 金融
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Computer Architecture, A Quantitative Approach, 5th
2022-01-07 15:06:24 11.92MB Computer Architecture
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Quant面试必读--Heard on the Street, 面试Quant的经典书籍之一
2022-01-03 19:46:42 2.99MB Quant
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