To analyzed profitability and risk of trading strategies on US Equity Markets using historical NYSE price data. Achieved Linear Regression Score of 0.9595 for predicting prices of SP500 on a one-day time scale. Implemented an algorithmic model for trading using moving average, achieved annual rate of return of 2.924% and Sharpe ratio of 0.803 Optimized portfolio using Monte Carlo Simulations and applied CAPM.

Analyze NYSE DataAnalyze NYSE Data Introduction In this project, I analyzed real-life data from the New York Stock Exchange. I drew a subset of a large dataset provided by Kaggle that contains historical financial data from S&P 500 companies. Why this Project? In this project, I went through the process of calculating summary statistics, drawing an inference from the statistics, calculating business metrics and using models to forecast future growth prospects for the companies. The goal is to perform an analysis and also create visual tools to communicate the results in informative ways. I have provided a clean data set for this project. Although in real-life scenarios, data sets often need to be cleaned and processed before analysis can proceed. This project allows me to see what a clean data set should look like. What skills did I use? The main goal of this project is to demonstrate my ability to: • Interpret the measures of central tendency and spread (mean, median, standard deviation, range). • Use a combination of Excel functions (e.g., IF statements, INDEX and MATCH, calculating descriptive statistics with the IF statement, dropdowns, data validation, VLOOKUP). • Analyze and forecast financial business metrics using Excel. • Create visualizations of a business metric and use Excel to create a financial forecast model. Submission What I included in my submission: 1- A presentation file that includes a slide with: • A statement of the question I posed. • Summary statistics and plots to communicate my final results. 2- Excel Workbook with tabs for each of the following: • Dataset • Summary statistics • Profit and Loss statement dashboard • Forecast model for three scenarios • My workbook could include additional tabs I might need for my project (e.g., pivot tables).

Interactive dashboard using Google Sheets and Slides to create an analysis of the NYSE with focus on Amazon and IBM.

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Udacity Nanodegree - Business Analytics - Project 2 - Analyze NYSE Data

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Business Analytics Udacity Nanodegree

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To analyzed profitability and risk of trading strategies on US Equity Markets using historical NYSE price data. Achieved Linear Regression Score of 0.9595 for predicting prices of SP500 on a one-day time scale. Implemented an algorithmic model for trading using moving average, achieved annual rate of return of 2.924% and Sharpe ratio of 0.803