Green Stock Analysis
Steve just graduated from his finance degree and his parents are so proud of him. Infact they will be his first clients. Steves parents are passionate about green energy. They believe that as fossil fuels get used up, there will be more reliance on alternative sources of energy.
There are many forms of energy to invest in including hydroelectricity, wind energy, geothermal energy and bioenergy. However, Steve’s parents haven’t done much research and are willing to invest all their money into Daqo new Energy Corporation, a company that makes silicon Wafers for solar panels. Daqo’s Symbol is “DQ” Steve’s parents met at Dairy Queen so thats all the information they needed. Steve promised to look into Daqo stock for his parents but he is concerned about diversifying their funds He wants to analyze a handful of green energy stocks in addition to Daqo’s stocks. He has created an excel file concerning the stock data he wants to analyze and wants help. The analysis was done with an extension of microsoft Excel called Visual basic For Applications (VBA)
Extract Stock Sentiment From News Headlines
It used to take days for financial news to spread via radio, newspapers, and word of mouth. Now, in the age of the internet, it takes seconds. Did you know news articles are automatically being generated from figures and earnings call streams? Hedge funds and independent traders are using data science to process this wealth of information in the quest for profit.
In this notebook, we will generate investing insight by applying sentiment analysis on financial news headlines from FINVIZ.com. Using this natural language processing technique, we can understand the emotion behind the headlines and predict whether the market feels good or bad about a stock. It would then be possible to make educated guesses on how certain stocks will perform and trade accordingly. (And hopefully, make money!)
Exploring the Bitcoin Cryptocurrency Market
Since the launch of Bitcoin in 2008, hundreds of similar projects based on the blockchain technology have emerged. We call these cryptocurrencies (also coins or cryptos in the Internet slang). Some are extremely valuable nowadays, and others may have the potential to become extremely valuable in the future1. In fact, on the 6th of December of 2017, Bitcoin has a market capitalization above $200 billion. This project explores the various cryptocurrencies and brings out the recommended coins for possible investment based on the data.
Analyzing International Debt Data
It’s not that we humans only take debts to manage our necessities. A country may also take debt to manage its economy. For example, infrastructure spending is one costly ingredient required for a country’s citizens to lead comfortable lives. The World Bank is the organization that provides debt to countries.
In this notebook, we are going to analyze international debt data collected by The World Bank. The dataset contains information about the amount of debt (in USD) owed by developing countries across several categories. We are going to find the answers to questions like:
- What is the total amount of debt that is owed by the countries listed in the dataset?
- Which country owns the maximum amount of debt and what does that amount look like?
- What is the average amount of debt owed by countries across different debt indicators?
Risk and Returns: The Sharpe Ratio
An investment may make sense if we expect it to return more money than it costs. But returns are only part of the story because they are risky – there may be a range of possible outcomes. How does one compare different investments that may deliver similar results on average, but exhibit different levels of risks?
So let’s learn about the Sharpe ratio by calculating it for the stocks of the two tech giants Facebook and Amazon. As benchmark we’ll use the S&P 500 that measures the performance of the 500 largest stocks in the US. When we use a stock index instead of the risk-free rate, the result is called the Information Ratio and is used to benchmark the return on active portfolio management because it tells you how much more return for a given unit of risk your portfolio manager earned relative to just putting your money into a low-cost index fund.
