Bitcoin Price History (BTC-USD): Daily USD Spot Prices on a Rolling 365-Day Window

Bitcoin price history tracks the daily USD spot price of BTC, the most liquid and widely traded cryptocurrency. This dataset publishes daily closing prices in USD on a rolling 365-day window, sourced from the CoinGecko aggregated price feed. Beyond the live data, bitcoin price history matters for macro-financial analysis because BTC has evolved from a niche digital asset into a liquidity-sensitive macro instrument whose dynamics co-move with net liquidity, real rates, and global risk appetite.

Dataset: Bitcoin Price in USD (Rolling 365 Days) · Updated 2026-08-04

Source: CoinGecko API — Powered by CoinGecko (aggregated spot prices across major exchanges)

Macro Takeaway

Dataset Overview

Dataset Variables

The CSV and Excel files contain the following columns.

Column names match the CSV headers exactly.

Download the Complete Dataset

The full dataset is available in CSV and Excel formats.

Direct CSV Access — Eco3min Structured Dataset

https://eco3min.fr/dataset/bitcoin-price.csv

This URL returns the complete dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool.

Using the Dataset in Python

import pandas as pd

url = "https://eco3min.fr/dataset/bitcoin-price.csv"
df = pd.read_csv(url, parse_dates=["date"])

print(df.head())
print(df["btc_price_usd"].describe())

Using the Dataset in R

library(readr)

url <- "https://eco3min.fr/dataset/bitcoin-price.csv"
df <- read_csv(url)

head(df)
summary(df$btc_price_usd)

Both examples load the dataset directly from the URL — no download or API key required.

Methodology

Daily closing prices are pulled from the CoinGecko public API (market_chart endpoint, USD currency, daily interval). CoinGecko aggregates spot prices across major centralized exchanges, applying volume weighting after filtering wash-trade activity. The free API tier returns a rolling 365-day window, refreshed at each daily UTC close.

The Eco3min pipeline polls the endpoint once daily and writes a structured CSV with two columns (date, btc_price_usd) to the public dataset endpoint. Attribution: Powered by CoinGecko.

Data Quality & Provider Notes

The bitcoin price history series is sourced from the CoinGecko public API, which aggregates spot prices across major centralized and decentralized exchanges. CoinGecko’s methodology weights exchanges by reported volume after applying anti-wash-trade filters. The Eco3min pipeline pulls the daily endpoint and refreshes the dataset every 24 hours.

• Release latency. CoinGecko publishes daily closing prices in near real-time (UTC midnight close). Eco3min mirrors the feed with a daily pull, so the latest observation typically appears within 24 hours of UTC close.
• Revisions policy. Spot prices are not revised after publication, but CoinGecko may occasionally restate historical aggregated values if an exchange data feed is corrected upstream. Such restatements are infrequent and small in magnitude.
• Alternative sources. Exchange-specific APIs (Coinbase, Binance, Kraken, Bitstamp) provide single-venue closing prices that can diverge from the CoinGecko aggregate during periods of high volatility. Bloomberg’s XBT<CRNCY> ticker and Refinitiv’s BTC=BTSP also publish institutional-grade BTC-USD references with paid access.
• Known gaps. The free CoinGecko tier returns a rolling 365-day window only — extending the series further back requires the paid CoinGecko Pro tier or alternative sources (Bitstamp, which began trading BTC in 2011, is commonly used for long-history reconstructions back to 2010).

For production workflows, verify the most recent observation date before any analysis — UTC-based daily closes mean that intraday users in EST/PST timezones may see a one-day offset relative to local calendar dates.

Common Pitfalls When Using Bitcoin Price History

Bitcoin price history is widely used in macro and asset allocation research, but several recurring interpretation errors distort the signal.

1. CoinGecko aggregate vs exchange-specific divergence. The CoinGecko USD price is a volume-weighted aggregate across multiple exchanges. During periods of high volatility, Coinbase, Binance, and Kraken can diverge by 1–3% intraday. Users comparing bitcoin price history to a strategy backtested on a single venue often misattribute slippage to model error when the gap is purely a data-source artifact.
2. UTC closing vs local timezone. The daily series uses UTC midnight as the close. Analysts in US time zones who join the BTC series to NYSE-closing equity series (16:00 ET ≈ 21:00 UTC) frequently create false lead-lag patterns because the BTC “previous day” already incorporates several hours of post-equity-close trading.
3. Price versus market capitalization. A common confusion is treating BTC-USD price as a proxy for total crypto market cap. With circulating supply growing through halving cycles (~210,000 BTC mined per year currently), price and market cap can diverge over multi-year windows. For aggregate market exposure, market cap or total value locked metrics are more appropriate.
4. Ignoring the halving cycle in regime analysis. The supply schedule produces a discontinuity every ~210,000 blocks (~4 years): May 2020, April 2024, and the next expected around 2028. Studies that pool pre- and post-halving data without explicit regime indicators conflate distinct supply regimes — the post-halving stock-to-flow doubles, structurally shifting marginal seller behavior.

Historical Regimes

While this dataset publishes a rolling 365-day window, bitcoin price history over the full 2009–2026 period decomposes into several distinct macro regimes worth referencing when interpreting current data:

2009–2013 — Emergence (sub-$100 to $1,000). Bitcoin’s first four years saw price discovery from effectively zero to $1,000 by November 2013, driven by early retail adopters and the Silk Road shutdown narrative. Liquidity was thin and exchange infrastructure rudimentary.

2014–2016 — First crypto winter. Following the Mt. Gox collapse (February 2014), bitcoin price history shows a multi-year drawdown to ~$200 by January 2015, then a slow accumulation phase. This regime coincided with stable monetary conditions and limited correlation to traditional macro variables. A related perspective: the case for bitcoin or ethereum.

2017 — First parabolic cycle. Driven by retail FOMO and the ICO boom, BTC rallied from $1,000 in January 2017 to near $20,000 by December — a ~20x move in twelve months. The 2018 correction reversed ~84% of that move.

2018–2020 — Second crypto winter. BTC ranged $3,000–$13,000 with declining volatility. Macro correlations remained weak. The COVID liquidity shock in March 2020 produced a brief drawdown to ~$4,000 before central bank response triggered the next regime.

2020–2021 — Macro coupling and institutional adoption. Following the May 2020 halving and unprecedented monetary expansion, BTC rallied from $9,000 to $69,000 (November 2021). This is the regime where bitcoin price history first synchronized clearly with the M2 expansion and broader risk-on flows. The Ethereum cycle ran in parallel with even higher beta.

2022–2023 — Third crypto winter and macro reset. The Fed hiking cycle, Terra/Luna implosion (May 2022), and FTX collapse (November 2022) drove BTC from $69,000 to $15,500 — a 78% drawdown. Correlation with the S&P 500 reached historical highs as crypto traded primarily on Fed expectations.

2024–2026 — ETF era and fourth halving. The January 2024 approval of US spot bitcoin ETFs and the April 2024 halving anchored a new regime. The specifics are documented in this analysis of spot bitcoin etf microstructure. Institutional inflows reduced realized volatility versus prior cycles, while the dataset’s rolling 365-day window captures the post-halving expansion and consolidation phases. Cross-referencing with gold reveals an emerging “digital gold” valuation channel that prior cycles did not display.

Related Macroeconomic Datasets

Bitcoin price history sits at the intersection of three macro vectors: global liquidity (M2 and dollar dynamics), risk asset cycles (equities), and the alternative store-of-value complex (gold and other crypto). These linked datasets contextualize BTC moves within the broader macro regime.

Macroeconomic Dataset Hub

This dataset is part of the Eco3min macro-financial data repository.

Explore the Eco3min Dataset Hub

Sources

• CoinGecko API — Powered by CoinGecko (aggregated spot prices across major exchanges)

Dataset Reference

Eco3min Research. (2026). Bitcoin Price History (BTC-USD, Rolling 365 Days).<br> https://eco3min.fr/en/bitcoin-price-history-dataset/