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BND Vanguard Total Bond Market ETF

ETF

71.65 USD Close 11/5
Since 2024-12-06 +4.9%

Close 11/5

FinLab Studio

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AI finds several complementary traits of Vanguard Total Bond Market ETF across different dimensions, combines them into a multifactor strategy, and backtests it against the market.

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Price and fund-flow snapshot

As of 2026-11-05

Risk / liquidity: Strong.

Momentum Neutral 60-day return is Good, but 240-day return is Average.
60-day return (%) 0.2 71th percentile · Good
240-day return (%) 0.4 28th percentile · Average
Momentum Trading Strategy: A 12-1 Momentum Backtest
Risk / liquidity Strong 60-day annualized volatility is Top; Distance from peak is Good.
60-day annualized volatility (%) 4.7 15th percentile · Top
Distance from peak (%) -2.8 77th percentile · Good
20-day dollar volume 762,503,109.0 83th percentile · Top

Vanguard Total Bond Market ETF (BND) today

1 quant signals active · As of 2026-11-05

Win rate and excess are historical post-trigger stats vs the market. Click a signal for its full definition and samples; history does not predict future results.

Vanguard Total Bond Market ETF (BND) peers and tracking

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Vanguard Total Bond Market ETF (BND) quant signal backtests

Signals active now

Each active condition is tested against this ETF’s own history and benchmarked versus the S&P 500.

Back above the 200-day average

Active · now 0.1%

Adjusted close crosses from below to above its 200-day moving average; repeated crosses within 20 days count once.

23 historical occurrences (since 2017-04-12)

Average forward return after Back above the 200-day average

20-day: Win 54.5%, Sample 22, Median +0.1%, Excess -0.4%, Beat mkt rate 36.4%

60-day: Win 57.1%, Sample 21, Median +0.9%, Excess -2.7%, Beat mkt rate 33.3%

120-day: Win 63.2%, Sample 19, Median +2.8%, Excess -6.2%, Beat mkt rate 26.3%

120 days after: historical avg +1.1%

20-day +0.6%
60-day +0.2%
120-day +1.1%
20-day
60-day
120-day
Win
54.5%
57.1%
63.2%
Sample
22
21
19
Median
+0.1%
+0.9%
+2.8%
Excess
-0.4%
-2.7%
-6.2%
Beat mkt rate
36.4%
33.3%
26.3%

Over 19 occurrences, 120-day forward avg gained 1.1%, lagged the market by 6.2 pts; win rate 63.2%.

More history: Holding-period returns in its own history, Signals not active now

Holding-period returns in its own history

Since 2016-01-04, 64.0% of 2,475 one-year holding periods ended with a gain; the median one-year return was +1.7%. Over three-year holding periods, 64.3% of 1,971 ended with a gain (median +7.3%).

A holding period starts on every trading day, so periods overlap; they describe the historical distribution rather than independent outcomes.

Signals not active now

Inactive signals still show this ETF’s historical forward-return distribution for context.

52-week adjusted-price high

Pending

Adjusted close first reaches a 252-trading-day high; repeated hits within 20 days count once.

16 times historically; 60-day forward avg +1.4%, win rate 81.2%, beating the market by -3.7 pts on average.

20% below its peak

Pending

Adjusted close first falls 20% or more below its highest level so far; repeated hits within 20 days count once.

Top-quintile 6-month momentum

Pending

The ETF ranks in the top 20% of liquid US-listed ETFs by 126-day adjusted return.

10 times historically; 60-day forward avg +2.0%, win rate 90.0%, beating the market by -5.6 pts on average.

Method and limits

  • Returns use us_fund_price:adj_close (finlab data.set_market('us_fund')), adjusted for splits and for distributions where the data includes them.
  • Excess returns use world_index:^GSPC, the S&P 500 price index without dividends, as the benchmark.
  • Percentiles and the 6-month momentum signal compare against the most liquid US-listed ETFs by 20-day dollar volume; mutual funds are excluded.
  • Category labels come from the fund data where it provides one (bond, income, crypto) and from the fund name for leveraged, inverse and commodity ETFs.
  • Overlapping event windows are descriptive distributions, not independent samples.
  • us_fund_price:adj_close records this ETF’s distributions regularly only from 2018-03-01; returns before that date mostly reflect price changes and splits, so they understate its total return.

This page is for historical data analysis and education only. It is not investment advice. Backtests and historical return distributions do not predict future performance; evaluate risk independently before trading.