Tag: AAPL

  • A Market-Neutral Strategy

    A Market-Neutral Strategy

    The work aims to solve the problem of Markowitz portfolio optimization for a one-year investment horizon through the pairs trading cointegrated strategy. Market-neutral trading strategies seek to generate returns independent of market swings to achieve a zero beta against its relevant market index. Statistical arbitrage (SA), pairs trading, and APO signals are analyzed. The study…

  • Dividend-NG-BTC Diversify Big Tech

    Dividend-NG-BTC Diversify Big Tech

    SEO Title: Can Dividends, Natural Gas and Crypto Diversify Big Techs? Ultimately, we need to answer the following fundamental question: Can Dividend Kings, NGUSD and BTC-USD Diversify Growth Tech assets? Dividends are very popular among investors, especially those who want a steady stream of income from their investments. Some companies choose to share their profits…

  • Returns-Volatility Domain K-Means Clustering and LSTM Anomaly Detection of S&P 500 Stocks

    Returns-Volatility Domain K-Means Clustering and LSTM Anomaly Detection of S&P 500 Stocks

    This study aims to implement and evaluate the K-means algorithm for ranking/clustering S&P 500 stocks based on average annualized return and volatility. The second goal is to detect anomalies in the best performing S&P 500 stocks using the Isolation Forest algorithm. Additionally, anomalies in the S&P 500 historical stock price time series data will be…

  • IQR-Based Log Price Volatility Ranking of Top 19 Blue Chips

    IQR-Based Log Price Volatility Ranking of Top 19 Blue Chips

    The focus is on risk assessment of top blue chips. We determine market regimes using standard deviation (STD) of log-domain stock prices.

  • Multiple-Criteria Technical Analysis of Blue Chips in Python

    Multiple-Criteria Technical Analysis of Blue Chips in Python

    Blue chip stocks are the stocks of well-known, high-quality companies. We demonstrate that the proposed approach can help optimize the blue-chip portfolios comprehensively.

  • Blue-Chip Stock Portfolios for Quant Traders

    Blue-Chip Stock Portfolios for Quant Traders

    This post delves into optimizing blue-chip stock portfolios using Python fintech libraries for private DIY self-traders. It includes steps for examining trading signals, comparing stock returns, performing analyses, and implementing forecast models. The content covers AAPL trading signals, risk vs. ROI analysis, a 4-stock portfolio, Monte-Carlo predictions, SPY return/volatility, and SPY Prophet forecast. The examples…

  • Data Visualization in Python – 1. Stock Technical Indicators

    Data Visualization in Python – 1. Stock Technical Indicators

    Featured Photo by Monstera on Pexels. In this project, we will implement the following Technical Indicators in Python: Conventionally, we will look at the following three main groups of technical indicators: Input Stock Data Let’s set the working directory VIZ import osos.chdir(‘VIZ’)os. getcwd() and import the key libraries import datetime as dtimport pandas as pdimport…

  • LSTM Price Predictions of 4 Tech Stocks

    LSTM Price Predictions of 4 Tech Stocks

    The given content explains the process of using Exploratory Data Analysis (EDA) and Long Short-Term Memory (LSTM) Sequential model for comparing the risk/return of four major tech stocks: Apple, Google, Microsoft, and Amazon, considering the tech scenario in 2023. The analysis involves examining stock price patterns, their correlations, risk-return assessment, and predicting stock prices using…

  • Bear vs. Bull Portfolio Risk/Return Optimization QC Analysis

    Bear vs. Bull Portfolio Risk/Return Optimization QC Analysis

    Based on the Portfolio Allocation and Optimization Algorithm discussed earlier and the related portfolio management, let’s run the Bear vs. Bull QC test of the portfolio P=[MSFT, AAPL, NDAQ] in terms of the Risk/Return Ratio (RRR). We have got a Sharpe ratio of less than one that is considered unacceptable or bad. The risk the…

  • 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.

  • 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