Tag: stocks

  • Quant Trading using Monte Carlo Predictions and 62 AI-Assisted Trading Technical Indicators (TTI)

    Algorithmic Trading using Monte Carlo Predictions and 62 AI-Assisted Trading Technical Indicators (TTI): The goal of the here presented pilot study is to develop and test an end-to-end Python-3 script in Jupyter that implements algorithmic trading. Thanks to high-level automation and integration of multiple tasks, the script can simultaneously analyze hundreds of technical indicators, run…

  • S&P 500 Algorithmic Trading with FBProphet

    We use Facebook’s Prophet to forecast S&P 500 stock adjusted close price. We plot the results simulating an initial investment of $1,000.

  • Stock Forecasting with FBProphet

    Stock Forecasting with FBProphet

    Prophet from Meta (Facebook) is a procedure for forecasting time series data such as stocks. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.

  • OXY Stock Update Wednesday, 25 May 2022

    OXY Stock Update Friday, 20 May 2022 Energy Stocks Rebound Friday With 4% Jump in Crude Oil Prices Occidental Petroleum Shares Rise After Berkshire Hathaway Adds Stake in Firm TechView Opinion – BUY

  • AAPL Stock Technical Analysis 2 June 2022

    AAPL Stock Technical Analysis 19 May, 2022. Both annual and monthly linear regression trends of the AAPl stock performance vs CPI change show a clear positive gradient. This means that this dividend stock is a good candidate for your inflation-resistant portfolio for reasons beyond its dividend.

  • Inflation-Resistant Stocks to Buy

    Inflation-Resistant Stocks to Buy AAPL Example Python workflow Download 3 historical datasets – stock price and monthly/annual CPI Compute the monthly/annual stock performance (%) and CPI rate (%) Apply linear regression to the stock vs CPI performance cross-plot Check the slope or gradient of the linear trend – positive, negative or zero.

  • OXY Stock Technical Analysis 17 May 2022

    OXY Stock Technical Analysis 17 May 2022 Occidental Petroleum Is About To Crush Its Debt And Own The House – debt load to fall by nearly $20B in the coming year.

  • A Weekday Market Research Update

    A Weekday Market Research Update

    Market technical analysis, research and ideas.

  • ML/AI Regression for Stock Prediction – AAPL Use Case

    1. Install Yahoo finance library 2. Call all dependencies that we will use for this exercise  3. Define the ticker you will use 4. Let’s look at the data table 5. Data Exploration Phase 6. Data Preparation, Pre-Processing & Manipulation 7. Apply Linear Regression 8. Perform ML QC Analysis 9. Final Output

  • Macroaxis Wealth Optimization

    Macroaxis is an investment management solution designed to aid small businesses with portfolio creation, asset allocation, and more, using a variety of financial models. It offers a range of features, such as portfolio rebalancing, risk management, and a diverse set of analysis tools, at a starting price of $19.99 per month. The company also provides…

  • Upswing Resilient Investor Guide

    About Investment Business Helicopter View Business Intelligence (BI) Sneak Peek Risk/Return Ratio Risk Severity Matrix Min(Risk) Control Max(Reward) Control Stock Liquidity Bid-Ask Spread (BAS) Roadmap to the Highest Return 1 Preparation Phase (Workspace Setup) 2 Stock Data Analytics (Crunch the Numbers) 3 Max(Return) “Double Your Money” 4 Min(Fees) – “Investment Fees Matter” 5 Risk/Return Trade-Off…

  • Stocks on Watch Tomorrow

    Stocks on Watch Tomorrow

    Stocks on Watch Tomorrow Zacks Research Pup’s Weekday Dig MarketWatch Bulletin TradingView Community SeekingAlpha Daily Updates Cryptocurrencies, ETFs, Dividend Ideas, Global Investing, Trading, Stocks to Watch

  • Keras LSTM Stock Prediction

    Despite the vast amount of historical stock data, the high noise to signal ratio and varied market conditions cause inadequate stock price predictions. A solution to these challenges is Long Short Term Memory (LSTM). LSTMs offer a range of adjustable parameters without the necessity for fine-tuning, and efficiently handle sequential data.