This comprehensive dataset offers a decade's worth of insights into gold price trends, spanning from 2013 to 2023. It meticulously captures the daily opening and closing prices, highs and lows, along with trading volume for each day. Such a wealth of information can be instrumental for those seeking to analyze or visualize market dynamics over this ten-year period. All data was sourced from the authoritative platform: Investing.com Gold Historical Data

Gold rose to 3,754.06 USD/t.oz on September 26, 2025, up 0.11% from the previous day. Over the past month, Gold's price has risen 10.48%, and is up 41.22% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on September of 2025.

Description for Kaggle Project

Title: Gold Price Prediction

Subtitle: Analysis and Forecasting Using Gold Price Data from Kaggle's goldstock.csv

Description This project aims to analyze and forecast gold prices using a comprehensive dataset spanning from January 19, 2014, to January 22, 2024. The dataset, sourced from Kaggle, includes daily gold prices with key financial metrics such as opening and closing prices, trading volume, and the highest and lowest prices recorded each trading day. Through this project, we perform time series analysis, develop predictive models, formulate and backtest trading strategies, and conduct market sentiment and statistical analyses.

Upload an Image - Choose a relevant image such as a graph of gold price trends, a gold bar, or an illustrative image related to financial data analysis.

Datasets - Source: Kaggle - File: goldstock.csv

Context, Sources, and Inspiration -Context: Understanding the dynamics of gold prices is crucial for investors and financial analysts. This project provides insights into historical price trends and equips users with tools to predict future prices. - Sources: The dataset is sourced from Kaggle and contains historical gold price data obtained from Nasdaq. Inspiration: The inspiration behind this project is to enable researchers, analysts, and data enthusiasts to make informed decisions, develop trading strategies, and contribute to a broader understanding of market behavior.

FINAL_USO Dataset

  Overview

The FINAL_USO dataset is a comprehensive collection of financial data, including stock prices, volumes, and other relevant metrics for various market indices and individual securities. This dataset is particularly suited for financial analysis, time series forecasting, and market trend analysis.

  Dataset Structure

The dataset is provided as a single CSV file named FINAL_USO.csv. It contains 1,718 entries and 80 columns, each… See the full description on the dataset page: https://huggingface.co/datasets/mltrev23/gold-price.

This Dataset contains Historical Price of Gold in Indian Commodity Market . The data has been collected from https://in.investing.com/commodities/ using web scrapping . The script can be customized to suit the needs (like customizing frequency interval , commodity type etc ) Link to web scrapping script - https://github.com/Pritam3355/web_scrapping/blob/master/stock_price.py

Column contains - Date, Price ,Open , High ,Low ,Volume ,Chg% these columns can be sorted first in the website then use the url in script to download the data according to your need

Dataset of historical annual gold prices from 1970 to 2024, including significant events and acts that impacted gold prices.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Machine Learning Models for Gold Price Prediction

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Monthly price from 1988 to 2019.

EGPB

About Dataset This benchmark dataset consisting of 8030 rows and 36 variables sourced from multiple credible economic websites, covering a period from January 2001 to December 2022. This dataset can be utilized to predict gold prices specifically or to aid any economic field that is influenced by the variables in this dataset. Key variables & Features include: • Previous gold prices • Future gold prices with predictions for one day, one week, and one month • Oil prices •… See the full description on the dataset page: https://huggingface.co/datasets/Farah42/EGPBD-An-Event-based-Gold-Prices-Benchmark-Dataset.

Dataset historical price data for XAU/USD (gold vs USD) from 2004 to Feb 2025, captured across multiple timeframes including 5-minute, 15-minute, 30-minute, 1-hour, 4-hour, daily, weekly, and monthly intervals. Dataset includes Open, High, Low, Close prices, and Volume data.

Index Time Series for ProShares UltraShort Gold. The frequency of the observation is daily. Moving average series are also typically included. The fund seeks to meet its investment objective by investing under normal market conditions in any one of, or combinations of, Financial Instruments (including swap agreements, futures contracts and forward contracts) based on the fund"s benchmark.

Gold Historically gold coinage was widely used as currency; when paper money was introduced, it typically was a receipt redeemable for gold coin or bullion. In a monetary system known as the gold standard, a certain weight of gold was given the name of a unit of currency. For a long period, the United States government set the value of the US dollar so that one troy ounce was equal to $20.67 ($0.665 per gram), but in 1934 the dollar was devalued to $35.00 per troy ounce ($0.889/g). By 1961, it was becoming hard to maintain this price, and a pool of US and European banks agreed to manipulate the market to prevent further currency devaluation against increased gold demand.

This dataset is a part of this https://www.kaggle.com/datasets/psycon/daily-gold-price-historical-data dataset by BATUCAN SENKAL

Gold Prices Per Troy ounce refence www.gold.org ( World Gold Council)

This dataset is about news. It has 224 rows and is filtered where the keywords includes A model of short-run gold price behaviour?. It features one column called news link.

Permutable AI’s Gold Intelligence dataset (XAU) tracks the drivers of gold prices, from Federal Reserve interest rate policy and inflation trends to central bank buying and geopolitical risk. Advanced story signal detection identifies new narratives, sentiment shifts, and sustained coverage that move gold markets. With structured historical data and real-time sentiment analytics, traders and institutions can forecast gold price movements and hedge risk effectively. Delivered through the Co-Pilot API, gold market intelligence is available with millisecond latency.

The Gold Prices dataset includes daily prices of Gold since April 1968.

Vietnam Gold Price Index: MoM: Hanoi data was reported at 0.400 % in Sep 2018. This records an increase from the previous number of -1.730 % for Aug 2018. Vietnam Gold Price Index: MoM: Hanoi data is updated monthly, averaging -0.045 % from Aug 2008 (Median) to Sep 2018, with 122 observations. The data reached an all-time high of 14.660 % in Sep 2011 and a record low of -8.090 % in Nov 2008. Vietnam Gold Price Index: MoM: Hanoi data remains active status in CEIC and is reported by Hanoi Statistical Office. The data is categorized under Global Database’s Vietnam – Table VN.T030:Table VN.I030: Gold Price Index: MoM & YoY Growth.

This dataset contains the predicted prices of the asset $GOLD over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Gold Price - Historical chart and current data through 2025.

Gold prices in , August, 2025 For that commodity indicator, we provide data from January 1960 to August 2025. The average value during that period was 607.06 USD per troy ounce with a minimum of 34.94 USD per troy ounce in January 1970 and a maximum of 3368.03 USD per troy ounce in August 2025. | TheGlobalEconomy.com