Simulation Settings
Category: Fixed Income
Period: January 2015 - October 2024 (~10 years)
Consolidated Returns as of 31 October 2024
Consolidated Returns as of 31 October 2024
Currency:
USD
1.00$
Initial Capital
November 2019
November 2019
1.17$
Final Capital
October 2024
October 2024
3.21%
Yearly Return
5.59
Std Deviation
-12.85%
Max Drawdown
32months
Recovery Period
1.00$
Initial Capital
January 2015
January 2015
1.21$
Final Capital
October 2024
October 2024
1.97%
Yearly Return
5.60
Std Deviation
-12.85%
Max Drawdown
32months
Recovery Period
Live update: October 2024 (USD)
-1.48%
Month - October 2024
The VanEck Vectors ChinaAMC China Bond (CBON) ETF covers to the following investment themes:
- Asset Class: Bond
- Region: Emerging Asia Pacific
- Country: China
- Bond - Duration: All-Term
As of October 2024, over the analyzed timeframe, the VanEck Vectors ChinaAMC China Bond (CBON) ETF obtained a 1.97% compound annual return, with a 5.60% standard deviation. It suffered a maximum drawdown of -12.85% that required 32 months to be recovered.
Disclaimer: The simulations on this website are provided in good faith but should NOT be taken as investment advice. We are not liable for any errors or actions based on this information.
The authors of the website are not affiliated with the ETFs/Assets issuers. Content is for informational, educational, illustrative and entertainment purposes only.
Table of contents
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Investment Returns as of Oct 31, 2024
The VanEck Vectors ChinaAMC China Bond (CBON) ETF guaranteed the following returns.
Returns are calculated in USD, assuming:
- no fees or capital gain taxes.
- dividend reinvestment, when applicable.
VANECK VECTORS CHINAAMC CHINA BOND (CBON) ETF
1 January 2015 - 31 October 2024 (~10 years)
Swipe left to see all data
| Chg (%) | Return (%) | Return (%) as of Oct 31, 2024 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 Day | Time ET(*) | Nov 2024 |
YTD
(10M) |
1M | 6M | 1Y | 5Y |
MAX
(~10Y) |
|||
| Investment Return | n.a. | n.a. | 3.12 | -1.48 | 3.38 | 7.59 | 3.21 | 1.97 | |||
| Returns over 1 year are annualized | |||||||||||
| (*) Eastern Time (ET - America/New York) | |||||||||||
In 2023, the VanEck Vectors ChinaAMC China Bond (CBON) ETF granted a 3.05% dividend yield. If you are interested in getting periodic income, please refer to the VanEck Vectors ChinaAMC China Bond (CBON) ETF: Dividend Yield page.
Capital Growth as of Oct 31, 2024
An investment of 1$, from November 2019 to October 2024,
would be worth 1.17$, with a total return of 17.09% (3.21% annualized).
The Inflation Adjusted Capital would be 0.95$, with a net total return of -4.55% (-0.93% annualized).
The Inflation Adjusted Capital would be 0.95$, with a net total return of -4.55% (-0.93% annualized).
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An investment of 1$, from January 2015 to October 2024,
would be worth 1.21$, with a total return of 21.18% (1.97% annualized).
The Inflation Adjusted Capital would be 0.91$, with a net total return of -9.25% (-0.98% annualized).
The Inflation Adjusted Capital would be 0.91$, with a net total return of -9.25% (-0.98% annualized).
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Investment Metrics as of Oct 31, 2024
Metrics of VanEck Vectors ChinaAMC China Bond (CBON) ETF, updated as of 31 October 2024, provide a comprehensive overview of the portfolio's performance and risk characteristics.
These metrics include detailed data on returns, volatility, drawdowns and other key performance indicators. By examining them, you can gain insights into how the portfolio has performed over various time periods and understand its risk profile.
Metrics are calculated based on monthly returns, assuming:
- no fees or capital gain taxes.
- dividend reinvestment, when applicable.
VANECK VECTORS CHINAAMC CHINA BOND (CBON) ETF
Advanced Metrics
1 January 2015 - 31 October 2024 (~10 years)
Swipe left to see all data
| Metrics as of Oct 31, 2024 | ||||||||
|---|---|---|---|---|---|---|---|---|
|
YTD
(10M) |
1M | 3M | 6M | 1Y | 3Y | 5Y |
MAX
(~10Y) |
|
| Investment Return (%) | 3.12 | -1.48 | 1.83 | 3.38 | 7.59 | -0.38 | 3.21 | 1.97 |
| Growth of 1$ | 1.03 | 0.99 | 1.02 | 1.03 | 1.08 | 0.99 | 1.17 | 1.21 |
| US Inflation (%) | 2.17 | 0.24 | 0.61 | 0.72 | 2.58 | 4.50 | 4.17 | 2.98 |
| Returns / Inflation rates over 1 year are annualized. | ||||||||
|
DRAWDOWN
|
Current | 1Y | 3Y | 5Y | MAX | |||
| Deepest Drawdown Depth (%) | -3.77 | -1.48 | -12.85 | -12.85 | -12.85 | |||
| Start to Recovery (# months) | 32* | 1* | 32* | 32* | 32* | |||
| Start (yyyy mm) | 2024 10 | 2022 03 | 2022 03 | 2022 03 | ||||
| Start to Bottom (# months) | 1 | 8 | 8 | 8 | ||||
| Bottom (yyyy mm) | 2024 10 | 2022 10 | 2022 10 | 2022 10 | ||||
| Bottom to End (# months) | 0 | 24 | 24 | 24 | ||||
| End (yyyy mm) | - | - | - | - | ||||
| Longest Drawdown Depth (%) | -0.80 |
same |
same |
same |
||||
| Start to Recovery (# months) | 5 | |||||||
| Start (yyyy mm) | 2024 01 | 2022 03 | 2022 03 | 2022 03 | ||||
| Start to Bottom (# months) | 3 | 8 | 8 | 8 | ||||
| Bottom (yyyy mm) | 2024 03 | 2022 10 | 2022 10 | 2022 10 | ||||
| Bottom to End (# months) | 2 | 24 | 24 | 24 | ||||
| End (yyyy mm) | 2024 05 | - | - | - | ||||
| Longest negative period (# months) | 6 | 36* | 42 | 51 | ||||
| Start (yyyy mm) | 2024 01 | 2021 11 | 2021 01 | 2015 07 | ||||
| End (yyyy mm) | 2024 06 | 2024 10 | 2024 06 | 2019 09 | ||||
| Annualized Return (%) | -0.41 | -0.38 | -0.18 | -0.02 | ||||
| Drawdowns / Negative periods marked with * are in progress | ||||||||
| Deepest Drawdown Depth (%) | -15.60 | -1.91 | -17.88 | -19.53 | -19.53 | |||
| Start to Recovery (# months) | 41* | 8 | 35* | 41* | 41* | |||
| Start (yyyy mm) | 2024 01 | 2021 12 | 2021 06 | 2021 06 | ||||
| Start to Bottom (# months) | 3 | 23 | 29 | 29 | ||||
| Bottom (yyyy mm) | 2024 03 | 2023 10 | 2023 10 | 2023 10 | ||||
| Bottom to End (# months) | 5 | 12 | 12 | 12 | ||||
| End (yyyy mm) | 2024 08 | - | - | - | ||||
| Longest Drawdown Depth (%) |
same |
same |
same |
-11.39 | ||||
| Start to Recovery (# months) | 63 | |||||||
| Start (yyyy mm) | 2024 01 | 2021 12 | 2021 06 | 2015 08 | ||||
| Start to Bottom (# months) | 3 | 23 | 29 | 21 | ||||
| Bottom (yyyy mm) | 2024 03 | 2023 10 | 2023 10 | 2017 04 | ||||
| Bottom to End (# months) | 5 | 12 | 12 | 42 | ||||
| End (yyyy mm) | 2024 08 | - | - | 2020 10 | ||||
| Longest negative period (# months) | 7 | 36* | 60* | 118* | ||||
| Start (yyyy mm) | 2023 12 | 2021 11 | 2019 11 | 2015 01 | ||||
| End (yyyy mm) | 2024 06 | 2024 10 | 2024 10 | 2024 10 | ||||
| Annualized Return (%) | -2.07 | -4.67 | -0.93 | -0.98 | ||||
| Drawdowns / Negative periods marked with * are in progress | ||||||||
|
RISK INDICATORS
|
1Y | 3Y | 5Y | MAX | ||||
| Standard Deviation (%) | 4.54 | 6.12 | 5.59 | 5.60 | ||||
| Sharpe Ratio | 0.50 | -0.64 | 0.17 | 0.07 | ||||
| Sortino Ratio | 0.80 | -0.89 | 0.23 | 0.10 | ||||
| Ulcer Index | 0.50 | 7.19 | 5.62 | 5.02 | ||||
| Ratio: Return / Standard Deviation | 1.67 | -0.06 | 0.57 | 0.35 | ||||
| Ratio: Return / Deepest Drawdown | 5.13 | -0.03 | 0.25 | 0.15 | ||||
| Positive Months (%) | 66.66 | 50.00 | 61.66 | 55.93 | ||||
| Positive Months | 8 | 18 | 37 | 66 | ||||
| Negative Months | 4 | 18 | 23 | 52 | ||||
|
TIMEFRAMES
|
1M | 3M | 6M | 1Y | 3Y | 5Y | MAX | |
| ··· As of Oct 2024 - Over the previous 5Y | ||||||||
| Best Rolling Return (%) - Annualized | 14.77 | 3.80 | 3.21 | |||||
| Worst Rolling Return (%) - Annualized | -10.46 | -1.24 | ||||||
| Positive Periods (%) | 63.2 | 56.0 | 100.0 | |||||
| Best Rolling Return (%) - Annualized | 11.14 | -1.21 | -0.93 | |||||
| Worst Rolling Return (%) - Annualized | -16.91 | -6.19 | ||||||
| Positive Periods (%) | 40.8 | 0.0 | 0.0 | |||||
| 95% VaR - Value at Risk (%) - Cumulative | 2.38 | 3.77 | 4.85 | |||||
| 95% CVaR - Conditional Value at Risk (%) | 3.05 | 4.93 | 6.49 | |||||
| 99% VaR - Value at Risk (%) - Cumulative | 3.48 | 5.68 | 7.54 | |||||
| 99% CVaR - Conditional Value at Risk (%) | 4.18 | 6.89 | 9.26 | |||||
| Short term VaRs: analytical | ||||||||
| Safe Withdrawal Rate (%) | 90.60 | 29.37 | 20.15 | |||||
| Perpetual Withdrawal Rate (%) | --- | --- | --- | |||||
| % based on initial capital, inflation-adj. monthly withdrawals afterwards | Credits: BestRetirementPortfolio.com | ||||||||
| ··· All available data (Jan 2015 - Oct 2024) | ||||||||
| Best Rolling Return (%) - Annualized | 14.77 | 7.07 | 5.72 | |||||
| Worst Rolling Return (%) - Annualized | -10.46 | -1.24 | 0.83 | |||||
| Positive Periods (%) | 63.5 | 84.3 | 100.0 | |||||
| Best Rolling Return (%) - Annualized | 11.47 | 3.76 | 2.68 | |||||
| Worst Rolling Return (%) - Annualized | -16.91 | -6.19 | -2.26 | |||||
| Positive Periods (%) | 40.1 | 42.1 | 38.9 | |||||
| 95% VaR - Value at Risk (%) - Cumulative | 2.48 | 4.08 | 5.46 | |||||
| 95% CVaR - Conditional Value at Risk (%) | 3.16 | 5.24 | 7.11 | |||||
| 99% VaR - Value at Risk (%) - Cumulative | 3.59 | 5.99 | 8.16 | |||||
| 99% CVaR - Conditional Value at Risk (%) | 4.29 | 7.20 | 9.88 | |||||
| Short term VaRs: analytical | ||||||||
| Safe Withdrawal Rate (%) | 90.60 | 29.37 | 18.85 | |||||
| Perpetual Withdrawal Rate (%) | --- | --- | --- | |||||
| % based on initial capital, inflation-adj. monthly withdrawals afterwards | Credits: BestRetirementPortfolio.com | ||||||||
- Annualized Portfolio Return: it's the annualized geometric mean return of the portfolio.
- Deepest/Longest Drawdown: a drawdown refers to the decline in value from a relative peak value to a relative trough. The deepest (or maximum) drawdown is the maximum observed loss from a peak to a trough of a portfolio before a new peak is attained. The longest drawdown is the period observed from a peak to the subsequent peak with the greatest duration.
- Longest negative period: it's the maximum period for which an overall negative return has been observed.
- Standard Deviation: it's a measure of the dispersion of returns around the mean.
- Sharpe Ratio: it's a measure of risk-adjusted performance of the portfolio. It's calculated by dividing the excess return of the portfolio over the risk-free rate by the portfolio standard deviation. The risk-free rate here considered is the 1-3 Mth T-Bill return.
- Sortino Ratio: another measure of risk-adjusted performance of the portfolio. It's a modification of the Sharpe Ratio (same formula but the denominator is the portfolio downside standard deviation).
- Ulcer Index: it's a measure of downside risk that quantifies the depth and duration of drawdowns in an investment portfolio.
- Best/Worst 10Y returns: the best and the worst 10-year return over a time frame.
- Rolling Returns: N-year returns over a time frame, calculated over all the available data source (best, worst, % of positive returns). Each rolling period, longer than the longest negative period, yielded a non-negative minimum return.
- Value at Risk (VaR): it's an evaluation of a cumulative worst-case loss (in absolute value), associated with a probability (95%-99%) and a time horizon. For short term, it's calculated based on the expected return and standard deviation, assuming a normal distribution of monthly returns. For long term is retrieved by the historical rolling return data.
- Conditional Value at Risk (CVaR): it represents the average expected loss if that worst-case threshold (95%-99%) is ever crossed.
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Correlations as of Oct 31, 2024
Correlation measures to what degree the returns of two assets move in relation to each other. It is a statistical measure that describes the extent to which the returns of one asset are related to the returns of another asset.
The following table shows the monthly correlations of VanEck Vectors ChinaAMC China Bond (CBON) ETF vs the main Asset Classes, over different timeframes. Columns are sortable (click on table header to sort).
VANECK VECTORS CHINAAMC CHINA BOND (CBON) ETF
Monthly correlations as of 31 October 2024
Swipe left to see all data
| Correlation vs CBON | |||||
|---|---|---|---|---|---|
| Asset Class | 1 Year | 5 Years | 10 Years | 30 Years | |
|
VTI
|
US Total Stock Market | 0.49 | 0.39 | - | - |
|
SPY
|
US Large Cap Blend | 0.47 | 0.38 | - | - |
|
IJH
|
US Mid Cap Blend | 0.38 | 0.33 | - | - |
|
IJR
|
US Small Cap Blend | 0.43 | 0.34 | - | - |
|
VNQ
|
US REITs | 0.67 | 0.43 | - | - |
|
QQQ
|
US Technology | 0.38 | 0.39 | - | - |
|
PFF
|
US Preferred Stocks | 0.68 | 0.50 | - | - |
|
EFA
|
EAFE Stocks | 0.67 | 0.48 | - | - |
|
VT
|
World All Countries | 0.61 | 0.46 | - | - |
|
EEM
|
Emerging Markets | 0.65 | 0.58 | - | - |
|
BND
|
US Total Bond Market | 0.69 | 0.66 | - | - |
|
TLT
|
US Long Term Treasuries | 0.67 | 0.54 | - | - |
|
BIL
|
US Cash | 0.79 | -0.03 | - | - |
|
TIP
|
US TIPS | 0.63 | 0.58 | - | - |
|
LQD
|
US Invest. Grade Bonds | 0.73 | 0.62 | - | - |
|
HYG
|
US High Yield Bonds | 0.77 | 0.43 | - | - |
|
CWB
|
US Convertible Bonds | 0.50 | 0.40 | - | - |
|
BNDX
|
International Bonds | 0.62 | 0.53 | - | - |
|
EMB
|
Emerg. Market Bonds | 0.74 | 0.50 | - | - |
|
GLD
|
Gold | 0.02 | 0.47 | - | - |
|
DBC
|
Commodities | -0.61 | 0.04 | - | - |
Correlation values range between -1 and +1
- A correlation of +1 indicates that the returns of the two assets move in perfect synchrony; when one asset's returns go up, the other asset's returns also go up by the same percentage, and vice versa. This perfect positive correlation implies that the assets perform similarly in different market conditions.
- A correlation of -1 indicates a perfect inverse relationship between the returns of the two assets. When one asset's returns go up, the other asset's returns go down by the same percentage. This perfect negative correlation suggests that the assets move in opposite directions, providing a diversification benefit by reducing overall portfolio risk.
- A correlation of 0 means that there is no linear relationship between the returns of the two assets. The returns of one asset do not predict the returns of the other.
Learn about historical correlations here: see how the main asset classes relate to each other.
Drawdowns
A drawdown refers to the decline in value from a relative peak value to a relative trough. A maximum drawdown is the maximum observed loss from a peak to a trough of a portfolio before a new peak is attained.
VANECK VECTORS CHINAAMC CHINA BOND (CBON) ETF
Drawdown periods
Drawdown periods - Inflation Adjusted
1 November 2019 - 31 October 2024 (5 Years)
1 January 2015 - 31 October 2024 (~10 years)
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Rolling Returns
For a detailed rolling return analysis, click here
VanEck Vectors ChinaAMC China Bond (CBON) ETF: Rolling Returns
VanEck Vectors ChinaAMC China Bond (CBON) ETF: Rolling Returns
A rolling return is a measure of investment performance that calculates the return of an investment over a set period of time, with the starting date rolling forward. This approach can provide a more accurate representation of the investment's historical performance and helps investors to evaluate the investment's consistency over time.
VANECK VECTORS CHINAAMC CHINA BOND (CBON) ETF
Annualized Rolling Returns
Annualized Rolling Returns - Inflation Adjusted
1 November 2019 - 31 October 2024 (5 Years)
1 January 2015 - 31 October 2024 (~10 years)
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The values shown for the rolling periods represent key statistical points: the minimum, maximum, median, and the 15th and 85th percentiles. These percentiles give insight into the distribution of the data, indicating the range within which the central 70% of the values lie, while the median represents the middle value.
Seasonality
In which months is it better to invest in VanEck Vectors ChinaAMC China Bond (CBON) ETF?
Both the Average Return and the Gain Frequency (Win %) are useful to get an idea of what happened in the past. They are retrieved considering the time period from January 2015 to October 2024.
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For further information about the seasonality, check the Asset Class Seasonality page.
Monthly Returns
This section provides a visual/tabular representation of the performance variability in the VanEck Vectors ChinaAMC China Bond (CBON) ETF over time. It illustrates the distribution of monthly returns, showcasing the range and frequency of positive and negative returns.
VANECK VECTORS CHINAAMC CHINA BOND (CBON) ETF
Monthly Returns Distribution
1 November 2019 - 31 October 2024 (5 Years)
1 January 2015 - 31 October 2024 (~10 years)
37 Positive Months (62%) - 23 Negative Months (38%)
66 Positive Months (56%) - 52 Negative Months (44%)
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The first official book of
Build wealth
with Lazy Portfolios and Passive Investing
with Lazy Portfolios and Passive Investing