|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/quantitative-finance-algorithmic-trading-in-python/
课程评论：没有评论
**Quantitative Finance & Algorithmic Trading in Python 课程总结** 本课程深入探讨量化金融和算法交易的基础知识，尤其侧重于金融工程的数学模型和 Python 实现。 **核心内容概览：** * **金融基础：** 学习股票、债券及其他衍生品的基础概念。 * **数学模型：** 重点理解金融领域的核心数学模型，包括： * **债券定价：** 学习债券的未来价值、现值、收益率、麦考利久期以及债券定价理论与实践。 * **现代投资组合理论 (Markowitz 模型)：** 探索多元化、均值、方差、有效前沿及夏普比率，以及资本配置线 (CAL)。 * **资本资产定价模型 (CAPM)：** 理解系统性与非系统性风险、beta 和 alpha 参数、线性回归以及为何市场风险是唯一相关风险。 * **随机行为：** 介绍金融中的随机性，包括维纳过程、伊藤引理和布朗运动。 * **Black-Scholes 模型：** 学习 Black-Scholes 模型理论与实践，以及如何通过对冲消除风险，并使用蒙特卡罗模拟进行期权定价和计算期权希腊字母。 * **衍生品：** 学习期权（看涨和看跌期权）、远期和期货合约、信用违约互换 (CDS) 和利率互换等衍生品基础。 * **风险管理：** 学习价值风险 (VaR) 的概念，以及如何使用蒙特卡罗模拟来计算风险。 * **利率模型：** 探索均值回归随机过程、Ornstein-Uhlenbeck 过程和 Vasicek 模型，并应用蒙特卡罗模拟为债券定价。 * **投资策略：** 探讨价值投资和有效市场假说。 * **Python 实践：** * **Python 入门：** 讲解 Python 的安装、使用 Python 进行量化金融的原因，以及金融模型处理历史数据的问题。 * **Python 基础：** 涵盖变量、字符串、循环、逻辑运算符、函数、数据结构（列表、数组、元组、字典）、面向对象编程 (OOP) 和 NumPy 库。 **课程目标：** 本课程适合对统计学和数学感兴趣的学习者，旨在帮助您深入理解金融工程的数学模型，并利用 Python 进行量化金融分析和算法交易。 **警告：** 本课程需要扎实的统计学和数学基础。
This course is about the fundamental basics of financial engineering. First of all you will learn about stocks, bonds and other derivatives. The main reason of this course is to get a better understanding of mathematical models concerning the finance in the main. First of all we have to consider bonds and bond pricing. Markowitz-model is the second step. Then Capital Asset Pricing Model (CAPM). One of the most elegant scientific discoveries in the 20th century is the Black-Scholes model and how to eliminate risk with hedging. IMPORTANT: only take this course, if you are interested in statistics and mathematics!!!Section 1 - Introductioninstalling Pythonwhy to use Python programming languagethe problem with financial models and historical dataSection 2 - Stock Market Basicspresent value and future value of moneystocks and sharescommodities and the FOREXwhat are short and long positions?Section 3 - Bond Theory and Implementationwhat are bondsyields and yield to maturityMacaulay durationbond pricing theory and implementationSection 4 - Modern Portfolio Theory (Markowitz Model)what is diverzification in finance?mean and varianceefficient frontier and the Sharpe ratiocapital allocation line (CAL)Section 5 - Capital Asset Pricing Model (CAPM)systematic and unsystematic risksbeta and alpha parameterslinear regression and market riskwhy market risk is the only relevant risk?Section 6 - Derivatives Basicsderivatives basicsoptions (put and call options)forward and future contractscredit default swaps (CDS)interest rate swapsSection 7 - Random Behavior in Financerandom behaviorWiener processesstochastic calculus and Ito's lemmabrownian motion theory and implementationSection 8 - Black-Scholes ModelBlack-Scholes model theory and implementationMonte-Carlo simulations for option pricingthe greeksSection 9 - Value-at-Risk (VaR)what is value at risk (VaR)Monte-Carlo simulation to calculate risksSection 10 - Collateralized Debt Obligation (CDO)what are CDOs?the financial crisis in 2008Section 11 - Interest Rate Modelsmean reverting stochastic processesthe Ornstein-Uhlenbeck processthe Vasicek modelusing Monte-Carlo simulation to price bondsSection 12 - Value Investinglong term investingefficient market hypothesisAPPENDIX - PYTHON CRASH COURSEbasics - variables, strings, loops and logical operatorsfunctionsdata structures in Python (lists, arrays, tuples and dictionaries)object oriented programming (OOP)NumPyThanks for joining my course, let's get started!
