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所在平台: Udemy |
课程主页: https://www.udemy.com/course/investment-analysis-with-natural-language-processing-nlp/
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课程名称：投资分析与自然语言处理（NLP） 课程概述： 欢迎进入以情感为基础的投资分析课程。利用自然语言处理（NLP）技术，深入剖析情感在金融分析和投资分析中的应用（使用Python），并严谨验证你的假设。探索文本数据在金融分析/投资分析中的潜力，采用严格以假设为驱动的研究方法，扎根于学术和实践文献，通过Python工具进行全面学习。 课程内容分为两个部分，共九个章节： 第一部分：投资分析基础 - 学习投资分析/金融分析过程的核心基本原理，包括投资安全关系和收益估算。 - 通过分析价格、风险和回报之间的关系，掌握金融分析的基本法律——单一价格法则。 - 掌握存短股票的概念和操作，学习如何从头开始计算股票和投资组合的收益。 - 深入探讨预期收益及其估算方法，包括资本资产定价模型（CAPM）及多因子资产定价模型。 - 量化股票风险和投资组合风险，掌握如何利用真实世界数据估算多股票的投资组合风险。 第二部分：基于自然语言处理（NLP）的投资/情感分析 - 介绍自然语言处理(NLP)在金融中的应用，学习情感分析的基本概念与五步流程。 - 学习如何设计假设并进行探索性数据分析，避免数据陷阱。 - 使用Python量化公司的情感，评估情感与股票回报之间的关系，开展情感投资分析。 - 通过统计方法严格验证投资假设，学习如何应对预期之外的结果。 本课程旨在为学员提供坚实的金融分析及情感分析基础，通过逐步指导和丰厚的练习题来巩固学习成果，帮助您成为自然语言处理(NLP)和投资分析领域的专家。
Say hello to Sentiment Based Investment Analysis done right. Leverage the power of Natural Language Processing (NLP) techniques to exploit Sentiment for Financial Analysis / Investment Analysis (with Python), while rigorously validating your hypothesis.Explore the power of text data for conducting financial analysis / investment analysis rigorously, using hypothesis driven approaches that are rigorously grounded in the academic and practitioner literature. All while leveraging the power of Python.Discover what Natural Language Processing (NLP) is, and how it's applied in Finance, using Python for Finance.Master the systematic 5 Step Process for Sentiment Analysis while working with a large sample of messy real world data obtained from credible sources, for free.# =============================# 2 PARTS, 9 SECTIONS TO MASTERY # =============================(plus, all future updates included!)PART I: INVESTMENT ANALYSIS FUNDAMENTALSStart by gaining a solid command of the core fundamentals that drive the entire investment analysis / financial analysis process.Explore Investment Security Relationships & Estimate ReturnsDiscover powerful relationships between Price, Risk, and ReturnsIntuitively explore the baseline fundamental law of Financial Analysis - The Law of One Price.Learn what "Shorting" a stock actually means and how it worksLearn how to calculate stock returns and portfolio returns from scratchWork with real-world data on Python and know exactly what your code does and why it worksEstimate Expected Returns of Financial SecuritiesExplore what "expected returns" are and how to estimate them starting with the simple meanDive deeper with "state-contingent" expected returns that synthesize your opinions with the dataLearn how to calculate expected returns using Asset Pricing Models like the CAPM (Capital Asset Pricing Model)Discover Multi-Factor Asset Pricing Models including the "Fama French 3 Factor Model", Carhart 4 ("Momentum"), and moreMaster the theoretical foundation and apply what you learn using real-world data on Python your own!Quantify Stock Risk and Estimate Portfolio RiskExamine the risk of a stock and learn how to quantify total risk from scratchApply your knowledge to any stock you want to explore and work withDiscover the 3 factors that influence portfolio risk (1 of which is more important than the other two combined)Explore how to estimate portfolio risk for 'simple' 2-asset portfoliosLearn how to measure portfolio risk of multiple stocks (including working with real-world data on Python!)Check your MasterySo. Much. Knowledge, Skills, and Experience. Are you up for the challenge? - Take the "Test Towards Mastery"Identify areas you need to improve on and get better at in the context of Financial Analysis / Investment AnalysisSet yourself up for success in Investment Analysis with Natural Language Processing (NLP) by ensuring you have a rigorous foundation in placePART II: INVESTMENT / SENTIMENT ANALYSIS WITH NATURAL LANGUAGE PROCESSING (NLP)Introduction to Natural Language Processing & Sentiment Analysis in FinanceGain an overview of what Natural Language Processing (NLP) is in the context of Finance.Discover the wealth of applications of Natural Language Processing (NLP) techniques in Finance, both in the academic and practitioner literature - for Context, Compliance, and Quantitative Analysis (aka, at least in principle, financial analysis / investment analysis).Explore what Sentiment Analysis is, and learn about the Fervent 5 Step Sentiment Analysis Process to help you conduct sentiment investing in a rigorous and statistically robust manner.Hypothesis Design & Exploratory Data AnalysisLearn how you can formally express your Finance investment ideas / investing thesis by transforming them into testable hypotheses that are short, ultra-specific, and measurable.Explore the wealth of data sources available, and how you can let your financial hypothesis drive the choice of data.Avoid the "GIGO Trap". See what it takes to really know your financial data with exploratory data analysis techniques designed to hold you in good stead when you get around to conducting sentiment-based financial analysis / investment analysis using Python.Estimating Firm-Level SentimentBecome a pro at quantifying sentiment/emotions of companies from scratch using Python, so you can use them for financial analysis / investment analysis.Apply lexicon / dictionary based approaches to estimating sentiment on Python while critically evaluating alternative approaches (e.g. using "machine learning" based approaches and why they can't be applied in some cases).Explore computations of sentiment "manually", leveraging the power of built-in methods inside Python's NLTK framework.Estimating Sentiment Portfolio ReturnsLink / merge your firm-level sentiment estimates with stock price and returns data on Python to evaluate relationships between sentiment and stock returns (reap the rewards of your hard work by finally conducting sentiment analysis!).Discover how to merge daily data with annual data, while using the "ffill" method built into Python (Pandas) to maintain a daily dataset with ease.Estimate quintile sorted sentiment portfolio returns and prep the data on Python for the final push.Sentiment / Natural Language Processing (NLP) based Investment AnalysisAvoid guesswork by leveraging the power of statistics to rigorously test and validate your hypothesis in a robust manner on Python.Gain a solid insight into why the statistics makes sense, including why we use a specific statistical test (the t-test)Explore what to do when things don't quite go the way you expected them to. And finally, learn whether the sentiment of a stock actually matters for financial / investment performance.DESIGNED FOR DISTINCTION™We've used the same tried and tested, proven to work teaching techniques that've helped our clients ace their exams and become chartered certified accountants, get hired by the most renowned investment banks in the world, and indeed, manage their own portfolios.Here's how we'll help you master financial analysis and sentiment analysis, and turn you into a PRO at Financial Analysis / Investment Analysis with Natural Language Processing (NLP) on Python:A Solid FoundationYou'll gain a solid foundation of the core fundamentals that drive the entire financial analysis / investment analysis process. These fundamentals are the essence of financial analysis and sentiment analysis done right.Code-along WalkthroughsForget about watching videos where all the code's written out. We'll start from a blank Jupyter Notebook. And code everything from scratch, one line at a time. That way you'll literally see how we conduct rigorous financial analysis / investment analysis using Natural Language Processing (NLP) / sentiment as the core basis, one step at a time.Loads of Practice QuestionsApply what you learn immediately with 100+ practice questions, all with impeccably detailed solutions. Plus, assignments that take you outside your comfort zone.Proofs & ResourcesMathematical proofs for the mathematically curious, workable.ipynb and.py Python code - all included.
