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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-for-finance-and-trading-algorithms/
课程评论：没有评论
课程名称：Python金融分析与算法交易 课程概述：欢迎参加《Python金融分析与算法交易》课程！如果你对如何使用Python进行严谨的金融分析和追求算法交易感兴趣，那么这门课程将非常适合你！本课程将引导你了解使用Python进行金融和算法交易所需的一切知识。我们将从学习Python的基础知识开始，然后深入了解Py-Finance生态系统中使用的各种核心库，包括Jupyter、NumPy、Pandas、Matplotlib、Statsmodels、Zipline、Quantopian等。 课程内容包括： - Python基础知识 - NumPy进行高速数值处理 - Pandas进行高效数据分析 - Matplotlib进行数据可视化 - 使用pandas-datareader和Quandl进行数据获取 - Pandas时间序列分析技术 - 股票收益分析 - 累计日收益 - 波动性与证券风险 - EWMA（指数加权移动平均） - Statsmodels与ETS（误差-趋势-季节性） - ARIMA（自回归积分滑动平均） - 自相关图与偏自相关图 - Sharpe比率 - 投资组合配置优化 - 有效前沿及蒙特卡洛优化 - 基金类型 - 委托单簿 - 卖空 - 资本资产定价模型 - 股票拆分与红利 - 有效市场假说 - 使用Quantopian进行算法交易 - 期货交易 通过本课程，学员将掌握金融分析和算法交易所需的Python技能，并能够应用这些技能进行实际的金融分析与交易策略设计。
Welcome to Python for Financial Analysis and Algorithmic Trading! Are you interested in how people use Python to conduct rigorous financial analysis and pursue algorithmic trading, then this is the right course for you! This course will guide you through everything you need to know to use Python for Finance and Algorithmic Trading! We'll start off by learning the fundamentals of Python, and then proceed to learn about the various core libraries used in the Py-Finance Ecosystem, including jupyter, numpy, pandas, matplotlib, statsmodels, zipline, Quantopian, and much more! We'll cover the following topics used by financial professionals: Python FundamentalsNumPy for High Speed Numerical ProcessingPandas for Efficient Data AnalysisMatplotlib for Data VisualizationUsing pandas-datareader and Quandl for data ingestionPandas Time Series Analysis TechniquesStock Returns AnalysisCumulative Daily ReturnsVolatility and Securities RiskEWMA (Exponentially Weighted Moving Average)StatsmodelsETS (Error-Trend-Seasonality)ARIMA (Auto-regressive Integrated Moving Averages)Auto Correlation Plots and Partial Auto Correlation PlotsSharpe RatioPortfolio Allocation Optimization Efficient Frontier and Markowitz OptimizationTypes of FundsOrder BooksShort SellingCapital Asset Pricing ModelStock Splits and DividendsEfficient Market HypothesisAlgorithmic Trading with QuantopianFutures Trading
