About FTX US Crypto Price Data
The FTX US Crypto Price dataset by CoinAPI is for Cryptocurrency price and volume data points. The data covers 59 Cryptocurrency pairs, starts on 27th August 2021, and is delivered on any frequency from tick to daily. This dataset is created by monitoring the trading activity on FTX US.
About CoinAPI
CoinAPI was founded by Artur Pietrzyk in 2016 with the goal of providing real-time and historical Cryptocurrency market data, collected from hundreds of exchanges. CoinAPI provides access to Cryptocurrencies for traders, market makers, and developers building third-party applications.
About QuantConnect
QuantConnect was founded in 2012 to serve quants everywhere with the best possible algorithmic trading technology. Seeking to disrupt a notoriously closed-source industry, QuantConnect takes a radically open-source approach to algorithmic trading. Through the QuantConnect web platform, more than 50,000 quants are served every month.
Algorithm Example
class FTXUSAlgorithm(QCAlgorithm):
def Initialize(self) -> None:
self.SetStartDate(2022, 1, 1)
self.SetEndDate(2022, 2, 1)
self.SetCash(100000)
# FTX US accepts both cash and margin account types
self.SetBrokerageModel(BrokerageName.FTXUS, AccountType.Margin)
# Warm up the security with the last known price to avoid conversion error
self.SetSecurityInitializer(lambda security: security.SetMarketPrice(self.GetLastKnownPrice(security)))
# Requesting data
crypto = self.AddCrypto("BTCUSD", Resolution.Minute, Market.FTXUS)
self.btcusd = crypto.Symbol
self.minimum_order_size = crypto.SymbolProperties.MinimumOrderSize
# Historical data
history = self.History(self.btcusd, 30, Resolution.Daily)
self.Debug(f"We got {len(history)} items from our history request")
# Add Crypto Coarse Fundamental Universe Selection
self.AddUniverse(CryptoCoarseFundamentalUniverse(Market.FTXUS, self.UniverseSettings, self.UniverseSelectionFilter))
def UniverseSelectionFilter(self, crypto_coarse: List[CryptoCoarseFundamental]) -> List[Symbol]:
return [datum.Symbol for datum in crypto_coarse
if datum.Volume >= 100
and datum.VolumeInUsd > 10000]
def OnData(self, slice: Slice) -> None:
if self.Portfolio.CashBook['BTC'].Amount == 0:
free_cash = self.Portfolio.CashBook['USD'].Amount * (1-self.Settings.FreePortfolioValuePercentage)
quantity = free_cash / slice[self.btcusd].Price
quantity -= quantity % self.minimum_order_size
if quantity > 0:
self.MarketOrder(self.btcusd, quantity)
Example Applications
The FTX US Crypto Price dataset enables you to accurately design strategies for Cryptocurrencies. Examples include the following strategies:
- Buy and hold with dollar-cost averaging
- Trading Cryptocurrency volatility and price action
- Allocating a small portion of your portfolio to Cryptocurrencies to hedge against inflation
Pricing
Cloud Access
Free access to FTX US Crypto price data from CoinBase via the QuantConnect Cloud platform for your backtesting and research.
Tick Download
Crypto-currencies Tick resolution archives in LEAN format for on premise backtesting and research. One file per ticker/day/brokerage
Second Download
Crypto-currencies Second resolution archives in LEAN format for on premise backtesting and research. One file per ticker/day/brokerage.
Minute Download
Crypto-currencies Minute resolution archives in LEAN format for on premise backtesting and research. One file per ticker/day/brokerage.
Hour Download
Crypto-currencies Hour resolution archives in LEAN format for on premise backtesting and research. One file per ticker/brokerage.
Daily Download
Crypto-currencies Daily resolution archives in LEAN format for on premise backtesting and research. One file per ticker/brokerage.
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