Tag: algorithmictrading

  • Risk-Aware Strategies for DCA Investors

    Risk-Aware Strategies for DCA Investors

    Let’s look at the the Dollar-Cost Averaging (DCA) investment approach that involves investing the same amount of money in a target security at regular intervals over a certain period of time, regardless of price. It can make it easier to deal with uncertain markets by making purchases automatic. It also supports an investor’s effort to invest…

  • Joint Analysis of Bitcoin, Gold and Crude Oil Prices with Optimized Risk/Return in 2023

    Joint Analysis of Bitcoin, Gold and Crude Oil Prices with Optimized Risk/Return in 2023

    Referring to the recent fintech R&D study in Python, let’s discuss joint time-series analysis of Bitcoin (BTC), Gold (GC=F) and Crude Oil (CL=F) prices 2021-23 with the subsequent Markowitz portfolio optimization of these 3 assets in 2023. Goals: Scope: Input Data Let’s set the working directory import os os.chdir(‘PORTFOLIORISK’) os. getcwd() and import the following…

  • Advanced Integrated Data Visualization (AIDV) in Python – 1. Stock Technical Indicators

    Advanced Integrated Data Visualization (AIDV) 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…

  • Gold ETF Price Prediction using the Bayesian Ridge Linear Regression

    Gold ETF Price Prediction using the  Bayesian Ridge Linear Regression

    Featured Photo by Pixabay. Let’s set the working directory GOLD import osos.chdir(‘GOLD’) os. getcwd() and import the following libraries from sklearn.linear_model import LinearRegression import pandas as pdimport numpy as np import matplotlib.pyplot as plt%matplotlib inlineplt.style.use(‘seaborn-darkgrid’) import yfinance as yf Let’s read the dataDf = yf.download(‘GLD’, ‘2022-01-01’, ‘2023-03-25’, auto_adjust=True) Df = Df[[‘Close’]] Df = Df.dropna() Let’s…

  • Predicting the JPM Stock Price and Breakouts with Auto ARIMA, FFT, LSTM and Technical Trading Indicators

    Predicting the JPM Stock Price and Breakouts with Auto ARIMA, FFT, LSTM and Technical Trading Indicators

    Featured Photo by Pixabay In this post, we will look at the JPM stock price and relevant breakout strategies for 2022-23. Referring to the previous case study, our goal is to combine the Auto ARIMA, FFT, LSTM models and Technical Trading Indicators (TTIs) into a single framework to optimize advantages of each. Specifically, we will…

  • Revision 360 of Risk Aware Investing after SVB Collapse – 1. The Financial Sector

    Revision 360 of Risk Aware Investing after SVB Collapse – 1. The Financial Sector

    Following our recent analysis of the US banking crisis, let’s perform revision 360 of risk aware investing after the collapse of Silicon Valley Bank and Signature Bank. Clickable Table of Contents: Headlines The Guardian Mon 13 Mar 2023 06.42 GMT: Seeking Alpha Update Zacks Investment Research 15 March 2023: Stocks Close Higher On Moderating CPI…

  • The Donchian Channel vs Buy-and-Hold Breakout Trading Systems – $MO Use-Case

    The Donchian Channel vs Buy-and-Hold Breakout Trading Systems – $MO Use-Case

    Featured Photo Graham Wizardo on Pexels In fact, this algo trading Python project was inspired by the recent thread by @simply_robo Indeed, this is all about Altria Group, Inc. (NYSE: MO) – a Dividend King moving beyond smoking.   In this article, the historical data of $MO will be used to backtest and compare trading…

  • A Comparative Analysis of The 3 Best Global Growth Stocks in Q1’23 – 2. AZN

    A Comparative Analysis of The 3 Best  Global Growth Stocks in Q1’23 – 2. AZN

    StockNews TradingView The 1-week summary of AZN based on the most popular technical indicators, such as Moving Averages, Oscillators and Pivots: TradingView Analyst Rating based upon 42 analysts giving stock ratings to AZN in the past 3 months. The 37 analysts offering 1 year price forecast for AZN. AlgoTrading Let’s set the working directory YOURPATH…

  • A Comparative Analysis of The 3 Best U.S. Growth Stocks in Q1’23 – 1. WMT

    A Comparative Analysis of The 3 Best U.S. Growth Stocks in Q1’23 – 1. WMT

    Featured Photo by Karolina Grabowska on Pexels Let’s begin with WMT that operates a chain of hypermarkets (also called supercenters), discount department stores, and grocery stores in the United States, headquartered in Bentonville, Arkansas. Table of Contents StockNews Rating TradingView Screening The 1-week summary of Walmart Inc is based on the most popular technical indicators, such as Moving Averages, Oscillators and…

  • Biotech Genmab Hold Alert via Fibonacci Retracement Trading Simulations

    Biotech Genmab Hold Alert via  Fibonacci Retracement Trading Simulations

    SeekingAlpha: A ‘Strong Buy’ Call on Genmab. While analysts were issuing bearish calls on Danish biotech Genmab (GMAB), Seeking Alpha contributor Biologics had different thoughts. In fact, Genmab has risen about 6% for 2022 even as the broader biotech sector has shed about 27% for the year. Let’s examine the Genmab stock in terms of…

  • XOM SMA-EMA-RSI Golden Crosses ’22

    XOM SMA-EMA-RSI Golden Crosses ’22

    Featured Photo by Johannes Plenio on Pexels. Today we will discuss the XOM stock using most basic technical trading indicators (TTIs) within the Python library ta-lib. Recall that this library is widely used by algo traders requiring to perform technical analysis of financial market data. It includes 150+ indicators such as ADX, MACD, RSI, Stochastic,…

  • Energy E&P: XOM Technical Analysis Nov ’22

    Energy E&P: XOM Technical Analysis Nov ’22

    Featured Photo by Kayden The last few years offer a case study of how quickly energy markets can shift. According to our recent post, Oil & Gas Exploration and Production (E&P) stays the top energy sector, remaining firmly at Very Attractive to Buy. In the light of what we know about E&P business, let’s take…

  • The $ASML Trading Strategies via the Plotly Stock Market Dashboard

    The $ASML Trading Strategies via the Plotly Stock Market Dashboard

    Featured Photo by Jeremy Waterhouse. Recently, Dr. Dividend shared his insights into $ASML EUV business. This post is a follow-up based upon the highly interactive Plotly Stock Market Dashboard. Let’s import/install the key libraries !pip install pandas_datareader Successfully installed pandas_datareader-0.10.0 !pip install ta Successfully installed ta-0.10.2 import numpy as npimport pandas as pdfrom pandas_datareader import…

  • A TradeSanta’s Quick Guide to Best Swing Trading Indicators

    A TradeSanta’s Quick Guide to Best Swing Trading Indicators

    This post was motivated by the recent TradeSanta’s insights into Top 6 Indicators For Swing Trading. Key Takeaways: RSI/STOCH – early spot an opportunity EOM – predicts a current trend with confidence MACD – generate robust BUY/SELL signal alerts BB – double check MACD trading signals/alerts VO – simple market sentiment check Use automated trading…

  • Risk/Return POA – Dr. Dividend’s Positions

    Risk/Return POA – Dr. Dividend’s Positions

    Based upon the Portfolio Optimization Algorithm (POA) discussed earlier and the relevant POA QC analysis and comparisons, let’s look at the current stock positions suggested by Dr. Dividend (DD). Let’s define the following POA parameters: benchmark_ = [“^GSPC”,]portfolio_ = [‘AAPL’, ‘GOOG’, ‘COST’, ‘SBUX’, ‘DE’,’SOFI’,’APD’,’UNH’,’SHW’,’NVDA’] start_date_ = “2021-01-01”end_date_ = “2022-10-05”number_of_scenarios = 10000 trade_days_per_year = 252 delta_risk…

  • Algorithmic Testing Stock Portfolios to Optimize the Risk/Reward Ratio

    Algorithmic Testing Stock Portfolios to Optimize the Risk/Reward Ratio

    Investors can optimize their stock portfolio by invoking backtesting within the realm of algorithmic trading. The goal is to optimize the specific portfolio by maximizing returns and the Sharpe ratio.

  • 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.