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  Historical Price Use Cases for the GoogleFinance Function in Google Sheets In the quest to develop smarter, more reliable trading strategies tailored to individual preferences, historical price data plays a vital role. It helps analysts, developers, and self-directed traders fine-tune algorithms, validate models, and uncover patterns that might otherwise go unnoticed. But despite its significant benefits, acquiring and processing high-quality historical data often requires substantial investments in time, money, or both. As a security price data analyst and quantitative analysis trainer, I gravitate toward rich historical data sources that are both free and easy to use. This is because I want readers like you to be able to try out the analyses and models discussed in my articles.  For years — including the early days of this blog — I relied heavily on free historical data from Yahoo Finance. That changed abruptly when Yahoo Finance discontinued free access to its data . In ...
  Security Trading Analytics Blog Posts through May, 2025 (Click on Title to Navigate to a Post) Title Date Comparative Market Performance for a Buy-Sell Model Versus a Buy-and-Hold Strategy for Eight Tickers 5/27/2025 Programming and Backtesting Demonstrations for a Buy-Sell Model for Eight Tickers 5/2/2025 Building and Backtesting a Buy-Sell Model with Close Prices and EMAs 3/29/2025 What are Single-Stock ETFs and Should I Invest in Them? 2/23/2025 An Assessment of Selected Bitcoin-Related Securities from 2020 Through 2024 1/27/2025 Assessing Returns for Stocks In Watchlists 1/1/2025 Do Returns from the GOOGLEFINANCE Function In Google Sheets Match Returns from Yahoo Finance? 10/30/2024 GOOLEFINANCE Function in Google Sheets Can Download Historical Data via CSV Files 9/26/2024 Yahoo Finance No longer Supports the Free Download of Historical Data via CSV Files 9/11/2024 Compound Annual Growth Rates for Leveraged Versus Unleveraged Exchange Traded Funds 7/25/2024 An Introduction to...
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  Comparative Market Performance for a Buy-Sell Model Versus a Buy-and-Hold Strategy for Eight Tickers The last couple of Security Trading Analytics blog posts introduced and examined the logic of a buy-sell model based on close prices and two exponential moving averages (EMAs).  The first post pulled data from the Google Finance site and showed how to implement the model manually within a Google Sheets workbook for two tickers (SPY and SPXL) over a couple of different timeframes.  The second post illustrated how to use T-SQL to programmatically implement the buy-sell model and perform backtests from their original close price with a Google Sheets workbook of the model for eight tickers (SPY, SPXL, QQQ, TQQQ, GOOGL, MSFT, NVDA, and PLTR).  The current post compares the market performance of the buy-sell model to a buy-and-hold strategy for the eight tickers in the second post.  All eight tickers in this post are compared from the first trading date in 20...