Philippine Macro: Gold, Oil & Forex (March 2026)

Context:
At first glance, the global price of gold and the cost of crude oil seem entirely detached from everyday life in emerging markets. However, these massive macroeconomic indicators trickle down into local economies in profound ways.

This dataset takes two foundational global assets—Gold (a "safe haven" store of value) and Crude Oil (the ultimate "growth and energy" metric)—and runs them through a localized Southeast Asian lens using the Philippine Peso (PHP) exchange rate.

By standardizing daily and monthly data into a single, clean monthly timeline from 2014 to early 2026, this dataset allows researchers to explore how global market shocks the 2020 Pandemic, and the 2026 Middle Eastern geopolitical escalations) directly impact local purchasing power and domestic energy inflation.

Content:
This dataset contains a single, pre-cleaned CSV file (data.csv) containing 6 columns. The data has been resampled and aligned to a monthly frequency (Month Start).

Data Dictionary:

Date (datetime): The monthly timestamp (YYYY-MM-01 format).

Gold_USD (float): The global closing price of gold in US Dollars per troy ounce.

Oil_USD (float): The global closing price of crude oil in US Dollars per barrel.

PHP_Rate (float): The monthly average Foreign Exchange Rate (1 USD to PHP).

Gold_PHP (float): Calculated feature. The localized price of one troy ounce of gold in Philippine Pesos (Gold_USD * PHP_Rate).

Oil_PHP (float): Calculated feature. The localized price of one barrel of crude oil in Philippine Pesos (Oil_USD * PHP_Rate).

Inspiration & Starter Ideas
What can you do with this data? Here are a few research questions to kickstart your notebooks:

The FX Premium: How much extra wealth did local investors generate from gold simply due to the depreciation of the Philippine Peso against the US Dollar?

Crisis Detection (Gold-to-Oil Ratio): Can you calculate the historical Gold-to-Oil ratio to pinpoint major global market crashes?

Dynamic Correlation: Build a rolling correlation model to see when Gold and Oil move together (inflationary periods) versus when they move inversely (panic/risk-off periods).

Time-Series Forecasting: Use statistical or machine learning models to predict the compounding local cost of energy (Oil_PHP) based on global oil and forex trends.

Acknowledgements & Credits
This merged dataset was computationally aligned and engineered using publicly available data. Full credit and attribution go to the original creators of the foundational datasets used in this compilation:

Forex Exchange Rates Since 2004 (Updated Daily) by asaniczka: https://www.kaggle.com/datasets/asaniczka/forex-exchange-rate-since-2004-updated-daily
Crude Oil Price by sc231997: https://www.kaggle.com/datasets/sc231997/crude-oil-price
Global Gold Price Dataset (1833–2026) – Monthly by Md Mahfuz Sumon: https://www.kaggle.com/datasets/mdmahfuzsumon/global-gold-price-dataset-18332026-monthly

(Note: The original daily forex data from asaniczka was resampled into monthly averages for this project's time-series alignment).