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所在平台: Udemy |
课程主页: https://www.udemy.com/course/statistics-for-finance/
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课程名称：金融统计 概述：通过本课程提升您在金融职业中的统计技能，学习核心统计学和金融及商业应用。统计学是提供金融各领域分析基础的核心学科。本课程由经验丰富的金融从业者及前数学教授设计与制作，将带您领略全球金融行业中尖端的定量技术。本课程不要求有统计或金融的背景知识。它以高中数学的基础为起点，帮助您掌握金融市场建模、金融产品分析和风险管理所需的定量和计算工具。 您将学习到的内容：本课程将您扎实地打下统计学的概率基础，核心主题包括估计、假设检验和置信区间等，均有深入探讨。现代统计方法将应用于金融中的实际问题。 课程涵盖的主题包括： - 离散和组合概率 - 二项分布、正态分布、指数分布和卡方分布 - 混合正态分布 - 均值、方差、偏度和峰度 - 位置、尺度和形状参数 - 大数法则 - 中央极限定理 - 最大似然估计 - 矩方法 - 假设检验 - 检验的显著性水平、大小和检验力 - 置信界限和区间 - 金融时间序列中的平稳性和结构性突变 - 金融收益分布建模 Python工具：课程中包含用于处理概率分布、分析数据和实施现代统计算法的Python工具。所有软件都采用宽松的MIT许可协议，学生可以自由使用这些工具，并在未来的职业生涯或个人项目中应用。 立即注册！通过参加本课程，加速您的职业发展，提升您在金融和商业领域的统计技能。该课程包含超过20小时的讲座、广泛的习题集和实现现代统计方法的Python代码，并提供30天的退款保证，绝对不错过！
Level up your statistics skills for your career in finance with this course in core statistics and finance and business applications. Statistics is the core subject providing the foundation for analysis in all areas of finance. This course, designed and produced by a seasoned financial practitioner, and former math professor, delivers you to the forefront of cutting edge quantitative techniques used in the finance industry worldwide.This course assumes no knowledge of statistics or finance. From a basic foundation of only high school math this course will elevate you to the forefront of quantitative and computational tools for modelling financial markets, analyzing financial products, and managing risk. What You Will LearnThis course provides a thorough grounding in the probability foundations of statistics. The core topics of statistics, estimation, hypothesis testing, and confidence intervals, are treated in full depth. Modern statistics methods are applied to real problems from finance.Some of the topics covered in this course includeDiscrete and combinatorial probabilityThe binomial, normal, exponential, and chi-square distributionsMixed normal distributionsMean, variance, skewness, and kurtosisLocation, scale, and shape parametersLaw of large numbersCentral limit theoremMaximum likelihood estimationMethod of momentsHypothesis testingSignificance level, size, and power of testsConfidence bounds and intervalsStationarity and structural breaks in financial time seriesModelling the distributions of financial returnsIncludes Python ToolsPython based tools are included for working with probability distributions, for analyzing data, and providing implementations of modern statistical algorithms. All software that is part of this course is released under a permissive MIT license, so students are free to take these tools with them and use them in their future careers, include them in their own projects, whether open source or proprietary, anything you want!So Sign Up Now!Accelerate your career by taking this course and advancing your skills in statistics for finance and business. With more than 20 hours of lectures, extensive problem sets, and Python codes implementing modern statistics methods, not to mention a 30 day money back guarantee, you can't go wrong!
