|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/quantitative-finance-with-python/
课程评论：没有评论
课程名称：Python量化金融 课程概述：如果你有意在量化金融领域获得一份高薪并有前途的职业，或者你是一名金融从业者，想要在金融与数据科学之间架起桥梁，成为一名全面的量化分析师，那么这门课程正是为你量身定制的。量化分析师在投资银行、对冲基金或金融公司的角色，吸引着许多具有定量技能的专业人士，尤其是那些来自金融、数据科学、技术或工程等领域的人士。 本课程旨在为你提供进入量化金融世界的知识入口，帮助你在技术基础上进一步提升。如果你能够成功完成本课程，将掌握量化金融和金融工程的精髓。 课程内容包括以下主题： - 股票市场 - 商品市场 - 外汇交易 - 加密货币 - 技术分析 - 金融衍生品 - 期货与期权 - 时间价值 - 现代投资组合理论 - 效率市场假说 - 使用机器学习进行股票价格预测 - 使用LSTM神经网络（深度学习）进行股票价格预测 - 使用机器学习进行黄金价格预测 - 用Python开发与回测交易策略 - 技术指标（如移动平均线和相对强弱指标） - 算法交易 - 高级交易方法（如套利与配对交易） - 随机游走理论 - 资本资产定价模型 - 夏普比率 - 金融Python编程 - 不同股票和资产类别之间的相关性 - K线图 - 处理股票的财务数据和OHLC数据 - 使用凯利准则进行最佳头寸规模 - 多样化与风险管理 通过这门课程，你将获得量化金融领域所需的技能和知识，为你的职业发展铺平道路。
Interested in a lucrative and rewarding position in quantitative finance? Are you a professional working in finance or an individual working in Data Science and want to bridge the gap between Finance and Data Science and become a full on quant?The role of a quantitative analyst in an investment bank, hedge fund, or financial company is an attractive career option for many quantitatively skilled professionals working in finance or other fields like data science, technology or engineering. If this describes you, what you need to move to the next level is a gateway to the quantitative finance knowledge required for this role that builds on the technical foundations you have already mastered.This course is designed to be exactly such a gateway into the quant world. If you succeed in this course you will become a master of quantitative finance and the financial engineering.This Course covers a variety of topics like:Stock MarketsCommodity MarketForex TradingCryptocurrencyTechnical AnalysisFinancial DerivativesFuturesOptionsTime Value of MoneyModern Portfolio TheoryEfficient Market HypothesisStock Price Prediction using Machine LearningStock Price Prediction using LSTM Neural Networks (Deep Learning)Gold Price Prediction using Machine LearningDevelop and Backtest Trading Strategies in PythonTechnical Indicators like Moving Averages and RSI.Algorithmic Trading.Advanced Trading Methodologies like Arbitrage and Pair Trading.Random Walk Theory.Capital Asset Pricing Model.Sharpe Ratio.Python for Finance.Correlation between different stocks and asset classes.Candle Stick Charts.Working with Financial and OHLC Data for stocks.Optimal Position Sizing using Kelly Criterion.Diversification and Risk Management.
