Tag: volatility
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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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NVIDIA Returns-Drawdowns MVA & RNN Mean Reversal Trading

The study presents a machine learning-focused analytical approach to optimize NVIDIA’s stock performance using moving average crossovers and aims at comparing the outcomes with simple RNN mean reversal trading strategies. The steps taken involve preparing the stock data, calculating moving averages and drawdowns, plotting heatmaps of returns and drawdowns, and predicting returns and cumulative returns…
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Oracle Monte Carlo Stock Simulations

Oracle Corporation’s significant developments in Generative AI have led to lucrative partnerships with Nvidia and Elon Musk’s xAI. Having secured contracts exceeding $4 billion for its Generation 2 Cloud designed for AI model training, Oracle’s earnings doubled in Q4 2023. Monte Carlo simulations align with Zacks Rank 3-Hold for ORCL, implying bullish potential with projected…
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NVIDIA Rolling Volatility: GARCH & XGBoost

This post examines the prediction of NVIDIA stock volatility using two models: the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and the Extreme Gradient Boosting (XGBoost). Both models are compared in terms of MSE and MAPE. The post discovers that the machine learning-based XGBoost model outperforms the GARCH model in NVDA volatility forecasting, showing the effectiveness of…
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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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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…
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EUR/USD Forecast: Prophet vs JPM

JP Morgan (JPM) analysis predicts the EUR/USD exchange rate to hold at 1.08 in December 2023, while ING forecasts suggest rates of $1.00 throughout 2023 and $1.02 in Q1 2024, rising to $1.10 by Q4 2024. Using the FB Prophet model, predictions show a hold at 1.08 +/- 0.07 in December 2023, aligning with JPM’s…
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Risk-Aware Strategies for DCA Investors

Dollar-Cost Averaging (DCA) is an investment approach that involves investing a fixed amount regularly, regardless of market price. It offers benefits such as risk reduction and market downturn resilience. It’s useful for beginners and can be combined with other strategies for a disciplined investment approach. References include Investopedia and Yahoo Finance.
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Joint Analysis of Bitcoin, Gold and Crude Oil Prices

The content discusses a comprehensive analysis on a joint time-series analysis of Bitcoin, Gold and Crude Oil prices from 2021 to 2023. It explores data processing, exploratory data analysis before running a range of statistical tests, ARIMA models fitting, and finally, using the Markowitz portfolio optimization method. It then presents a detailed analysis, including data…
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Top 6 Reliability/Risk Engineering Learnings

The content provides a review of Eric Marsden’s e-learning Python courseware on risk engineering, loss prevention and safety management. It includes discussions of various topics such as the failure of light bulbs, electronic components, large computing facility maintenance, and oil field pumps. The content also delves into stock market risk analysis like Value at Risk…
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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…
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Portfolio Optimization of 20 Dividend Growth Stocks

The post discusses implementing a stochastic optimization algorithm to create a balanced portfolio of 20 dividend growth stocks for maximum return within defined risk tolerance. By analyzing daily stock and benchmark data, the algorithm optimizes the portfolio to outperform the benchmark index and achieve desired risk-reward outcomes. The results facilitate spreading investment capital across diverse…
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Donchian Channel Trading Systems

This article explores the application of algo trading using Python for Altria Group, Inc., a Dividend King diversifying beyond smoking. The historical data for Altria is used to test and contrast trading strategies based on the Donchian Channel indicator. The key is to compare the highest total return when using the Donchian Channel Breakout versus…
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Stock Market ’22 Round Up & ’23 Outlook: Zacks Strategy vs Seeking Alpha Tactics

Featured Photo by Pixabay Contents: Zacks Market Research 2022 has been a strong year for jobs: Commodity markets: Energy: Global Investments: In the Zacks October 2022 Chief Investment Officer (CIO) survey, the CIOs made it fairly clear how they felt about investing outside the US. Answer: not great. Corporate High Yield and Investment Grade Bonds:In…
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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…
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Gulf’s Oil Price Web Scraping in R

Gulf’s Oil Price Web Scraping in R. Gulf states to gain $1.3 trillion in additional oil revenue by 2026: IMF. We discuss the basics of sourcing oil market price data for free online. discuss the basics of sourcing oil market price data for free online. Webscraping in R is a technique to retrieve large amounts…
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Basic Stock Price Analysis in Python

Our basic stock price analysis in Python includes stock prices, stock volume, market capitalization, 50/200-day moving average, scattered X-plot matrix, and stock volatility or standard deviation.


