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Thursday, April 09, 2026

State Street SPDR Bloomberg 1-3 Month T-Bill ETF (BIL): A Strategic Cash Management Solution for Portfolios

By Century Financial in 'Investment Insights'

State Street SPDR Bloomberg 1-3 Month T-Bill...
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Introduction

As an investor, every basis point matters, and idle cash is a drag on returns. Here, SPDR Bloomberg 1-3 Month T-Bill ETF (BIL) offers an opportunity to park your funds risk-free. It is a professionally managed basket of the shortest-duration U.S. Treasury Bills, with underlying instruments maturing in 1-3 months, that are reissued by the U.S. Treasury to fund its short-term obligations. It offers investors a disciplined, low-risk, highly liquid vehicle to make dormant capital work without sacrificing safety or flexibility. The fund tracks the Bloomberg 1-3 Month U.S. Treasury Bill Index.

The Investment Thesis

Cash Management: Investors often keep some cash uninvested while deciding where to allocate it or when adjusting their portfolios. Instead of letting this cash sit idle, BIL allows investors to earn a yield on it. At the same time, the investment remains highly liquid and can be quickly converted back to cash when new investment opportunities arise.
Volatility Hedging: During periods of macro uncertainty — geopolitical shocks, Fed policy pivots, equity market corrections — BIL serves as a high-quality hedge and provides a safe allocation. Its near-zero duration means it does not suffer the price erosion that longer-dated Treasuries experience during yield spikes.
Institutional-Grade Liquidity: With average daily trading volume exceeding 8.65 million shares, BIL offers frictionless entry and exit for transactions of any size. Execution slippage is minimal, and the fund can be deployed or liquidated within a single trading session.
Competitive Yield on Zero-Risk Capital: At a Yield to Maturity (YTM) of 3.68% as of March 10, 2026, BIL is currently generating returns that are meaningfully above inflation expectations while carrying sovereign-backed credit quality.

The government and the treasury department are increasingly focusing on short-dated issuances for T-bills for funding purposes, which creates a more liquid secondary market for the underlying and more issuance means the index contains more discrete instruments, which allows State Street's portfolio managers to better manage maturity laddering and reduce concentration in a single auction date, improving the fund's internal diversification.

US Treasury Bills Weekly Issuance

Source: Bloomberg

ETF Snapshot
Name Ticker Industry Sector Primary Exchange Name Currency Last Price* 52 W Low 52 W High NAV % Premium /Discount Beta Total Assets ($ Millions) Expense Ratio (%)
State Street SPDR Bloomberg 1-3 Month T-BILL ETF BIL Govt/Agency-Short Term NYSE Arca USD $91.46 $91.26 $91.78 $91.46 0.00 0.57 $44.48 0.14%

Source: Bloomberg
*Last Price as of 10th March 2026

Return Analysis
Time Period Return (%)
1 Month 0.26%
3 Month 0.86%
YTD 0.65%
1 Year 4.01%
3 Year 4.71%
5 Year 3.23%
Dividends
Companies Weight (%)
1 year 4.02%
Indicated yield 3.19%
3 yr dividend growth rate 15.82%
5 yr dividend growth rate 120.90%
Payment frequency Monthly
Asset Allocation
Asset Weight (%)
Government 99.97%
Cash and Others 0.03%
Geography Analysis
Comapnies Weight (%)
U.S. 100%
Tod Fund Holdings
Industry Weigh(%)
Sovereign 100%
Risks and Assumptions related to Back-tested trading strategies
The risks and assumptions listed here are not intended to be an exhaustive summary of all the risks and assumptions involved.
The strategy might suffer from look-ahead bias which occurs due to the use of information or data in a study or simulation that would not have been known or available during the period being analyzed. This can lead to inaccurate results in the study or simulation.
Future price movements may not be exactly the same as the historical price movements and this could lead to variation in performance.
Testing can sometimes lead to over-optimization. This is a condition where performance results are tuned so high to the past they are no longer as accurate in the future.
The model assumes no slippages in trading. Slippage refers to the difference between the expected price of a trade and the price at which the trade is actually executed.
The back-tested strategy might be at risk of data dredging, which is the behavior of testing multiple hypotheses at one time, resulting in picking the data that best supports your main hypothesis.
Drawdowns in actual trading can be higher than the tested system and losses could be significant in the event of leverage.
Unforeseen events can lead to variation in performance from the tested trading strategy.
The tested result has been computed with price feeds available from Bloomberg.
The testing environment has not considered transaction or any other costs.
Trading indicators used for the purpose of testing has been provided by Bloomberg.
The strategy might suffer from data mining fallacy, selection bias and backfill bias.
A trading strategy that performs well on multiple datasets from one market (e.g., forex) might not perform as well in another market (e.g., stocks).
The strategy may not depict accuracy in terms of spread changes due to the spread-widening events.

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