Tag: TSLA
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Leveraging Predictive Uncertainties of Time Series Forecasting Models
Featured Image via Canva. In this post, we will take a deep dive into issues around predictive uncertainties of Time Series Forecasting (TSF) models. Our final goal is to minimize decision-making risks. TSF is a prediction of what will occur in the future, and it is an uncertain process. Because of the uncertainty, the accuracy…
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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…
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A Comprehensive Analysis of Best Trading Technical Indicators w/ TA-Lib – Tesla ’23
This study presents a comprehensive stock technical analysis guide for Tesla (TSLA) using the TA-Lib Python library. It explores the use of over 200 technical indicators, analyses historical data, and offers insight for both swing traders and long-term holders. The content includes detailed explanations and plots for various momentum, volume, volatility, and trend indicators, providing…
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Real-Time Stock Sentiment Analysis w/ NLP Web Scraping
Stock sentiment analysis is gaining popularity as a technique to understand public opinions on specific assets. This study uses NLP web scraping in Python to extract stock sentiments from financial news headlines on FinViz. The sentiment analysis can help determine investor opinions and potential impacts on stock prices, though it is not a standalone predictor.
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Dividend-NG-BTC Diversify Big Tech
SEO Title: Can Dividends, Natural Gas and Crypto Diversify Big Techs? The objective of this project is to implement several basic Quant Trading (QT) optimization ideas by analyzing tech growth, dividend stocks and highly volatile assets (commodities and crypto) in terms of risk/return optimization scenarios and (potential) diversification options. We will use the financial APIs…
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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.
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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.
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The Qullamaggie’s OXY Swing Breakouts
Featured Photo by @Nate_Dumlao at @unsplash This post was inspired by the Qullamaggie’s trading journey and its application to the TSLA swing breakouts. Read more about breakouts here. Our current goal is to extend the above breakout analysis to the $OXY stock. Motivation Occidental Petroleum: The Next Merger Arbitrage Play? Protecting Life’s Work: Buffett’s Acquisition…
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The Qullamaggie’s TSLA Breakouts for Swing Traders
The content explains a Python-based stock scanner project that analyses TSLA’s historical data downloaded from Yahoo Finance. It applies a set of functions to identify stocks meeting growth criteria and checks for consolidation. The output is a series of plots showing original close price vs filtered data or breakouts. The scanner aims to help swing…
