About US Treasury Yield Curve
The US Treasury Yield Curve datasets tracks the yield curve rate from the US Department of the Treasury. The data starts in January 1990 and is delivered on a daily frequency. This dataset is calculated from composites of indicative, bid-side market quotations (not actual transactions) obtained by the Federal Reserve Bank of New York at or near 3:30 PM Eastern Time (ET) each trading day.
About Treasury Department
The Treasury Department is the executive agency responsible for promoting economic prosperity and ensuring the financial security of the United States. The Department is responsible for a wide range of activities such as advising the President on economic and financial issues, encouraging sustainable economic growth, and fostering improved governance in financial institutions. The Department of the Treasury operates and maintains systems that are critical to the nation's financial infrastructure, such as the production of coin and currency, the disbursement of payments to the American public, revenue collection, and the borrowing of funds necessary to run the federal government.
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
from AlgorithmImports import *
from QuantConnect.DataSource import *
class USTreasuryDataAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self.set_start_date(2000, 3, 1)
self.set_end_date(2021, 6, 1)
self.set_cash(100000)
self.spy_symbol = self.add_equity("SPY", Resolution.HOUR).symbol
# Requesting data
self.yield_curve_symbol = self.add_data(USTreasuryYieldCurveRate, "USTYCR").symbol
# Historical data
history = self.history(USTreasuryYieldCurveRate, self.yield_curve_symbol, 60, Resolution.DAILY)
self.debug(f"We got {len(history)} items from our history request")
self.last_inversion = datetime.min
def on_data(self, slice: Slice) -> None:
if not slice.contains_key(self.yield_curve_symbol):
return
rates = slice[self.yield_curve_symbol]
# Check for null before using the values
if not (rates.ten_year is not None and rates.two_year is not None):
return
# Only advance if a year has gone by
if (self.time - self.last_inversion < timedelta(days=365)):
return
# if there is a yield curve inversion after not having one for a year, short sell SPY for two years
if (not self.portfolio.invested and rates.two_year > rates.ten_year):
self.debug(f"{self.time} - Yield curve inversion! Shorting the market for two years")
self.set_holdings(self.spy_symbol, -0.5)
self.last_inversion = self.time
return
# If two years have passed, liquidate our position in SPY
if (self.time - self.last_inversion >= timedelta(days=365 * 2)):
self.liquidate(self.spy_symbol)
Example Applications
The US Treasury Yield Curve dataset enables you to monitor the yields of bonds with numerous maturities in your strategies. Examples include the following strategies:
- Short selling SPY when the yield curve inverts
- Buying short-term Treasuries and short selling long-term Treasuries when the yield curve becomes steeper (aka curve steepener trade)
Pricing
Cloud Access
Freely harness US Treasure Yeild Curve data in the QuantConnect Cloud for your backtesting and live trading purposes.
Download On Premise
US Treasury Yield Curve data archived in LEAN format for on premise backtesting and research. One file that is updated daily.
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