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HL Swiss Optimised
Performance
Return for Risk
Dividends
Drawdowns
Volatility
Diversification

Asset Allocation


Asset allocation is not available

S&P 500 Index

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Performance

Performance Chart

The chart shows the growth of an initial investment of $10,000 in HL Swiss Optimised, comparing it to the performance of the S&P 500 index or another benchmark. All prices have been adjusted for splits and dividends.


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Returns By Period


Position1D1MYTD6M1Y3Y*5Y*10Y*
Benchmark
S&P 500 Index
0.30%0.09%8.18%8.17%23.42%19.88%11.91%13.45%
Portfolio
HL Swiss Optimised
*Multi-year figures are annualized to reflect compound growth (CAGR)

Monthly Returns


JanFebMarAprMayJunJulAugSepOctNovDecTotal
20240.82%0.71%3.39%-2.19%5.57%8.41%
20230.13%-0.71%6.13%3.64%-1.89%0.82%0.03%0.28%0.90%-4.86%4.73%2.44%11.74%
2022-4.17%-0.12%3.20%0.00%-3.87%-1.30%4.33%-1.33%1.59%0.24%3.26%-2.47%-1.06%
2021-0.65%0.49%0.78%0.73%3.80%4.37%0.18%3.88%-2.84%4.75%0.92%6.35%24.84%

Benchmark Metrics

HL Swiss Optimised has an annualized alpha of 11.36%, beta of 0.17, and R2 of 0.10 versus S&P 500 Index. Calculated based on daily prices since January 02, 2020.

  • This portfolio participates in less of S&P 500 Index's moves in both directions, but captures a larger share of gains (45.32%) than losses (28.04%) - typical of diversified or defensive assets.
  • Beta of 0.17 may look defensive, but with R2 of 0.10 this portfolio is largely uncorrelated with S&P 500 Index - low beta reflects independence, not downside protection. See the Volatility section for a true picture of this portfolio's risk.
  • R2 of 0.10 means this portfolio moves largely independently of S&P 500 Index - capture ratios reflect limited market correlation rather than active downside protection. Consider using a more representative benchmark.

Alpha
11.36%
Beta
0.17
0.10
Upside Capture
45.32%
Downside Capture
28.04%

Return for Risk

Sharpe Ratio

There isn't enough data available to calculate the Sharpe ratio for HL Swiss Optimised. This metric is based on the past 12 months of trading data. Please check back later for updated information.


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Dividends

Dividend yield


HL Swiss Optimised doesn't pay dividends

Drawdowns

Drawdowns Chart

The Drawdowns chart displays portfolio losses from any high point along the way. Drawdowns are calculated considering price movements and all distributions paid, if any.


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Worst Drawdowns

The table below displays the maximum drawdowns of the HL Swiss Optimised. A maximum drawdown is a measure of risk, indicating the largest reduction in portfolio value due to a series of losing trades.

The maximum drawdown for the HL Swiss Optimised was 11.10%, occurring on Mar 9, 2020. Recovery took 29 trading sessions.


Related event

Drawdown

Fall

Recovery

Underwater

COVID crash2020
-11.10%Mar 2020
18d1mo 12d
2moFeb 2020 - Apr 2020
Bear market2022
-9.56%Jun 2022
5mo 21d4mo 20d
10mo 11dJan 2022 - Nov 2022
2020 pullback2020
-9.04%Oct 2020
3mo 14d2mo 15d
5mo 29dJul 2020 - Jan 2021
2023 pullback2023
-6.07%Jul 2023
1mo 29d5mo 4d
7mo 3dMay 2023 - Dec 2023
2020 pullback2020
-4.94%May 2020
13d24d
1mo 7dApr 2020 - May 2020

Volatility

Volatility Chart

The chart below shows the rolling one-month volatility.


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Diversification

Diversification Metrics


Number of Effective Assets

The portfolio contains 0 assets, with an effective number of assets of 0.00, reflecting the diversification based on asset allocation. null


Diversification Ratio

Not enough data to calculate this metric.

HL Swiss Optimised correlation to the S&P 500 Index

HL Swiss Optimised has a 0.22 correlation to S&P 500 Index over the trailing 12 months. This section compares each holding's correlation to the benchmark and to the portfolio.

Correlation
Correlation (1Y)
Calculated over the trailing 1-year period

0.22

Correlation (3Y)
Calculated over the trailing 3-year period

0.26

Correlation (All Time)
Calculated using the full available price history since Jan 2, 2020

0.28

Diversification Analysis

Find what HL Swiss Optimised is missing

See which holdings overlap, where HL Swiss Optimised is concentrated, and which low-correlation assets could fill the gaps.

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