SSIAM VN30 Correlations
| FUESSV30 | 16,280 130.00 0.80% |
The current 90-days correlation between SSIAM VN30 ETF and SSIAM VNFIN LEAD is 0.64 (i.e., Poor diversification). The correlation of SSIAM VN30 is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
SSIAM VN30 Correlation With Market
Weak diversification
The correlation between SSIAM VN30 ETF and DJI is 0.3 (i.e., Weak diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding SSIAM VN30 ETF and DJI in the same portfolio, assuming nothing else is changed.
SSIAM |
The ability to find closely correlated positions to SSIAM VN30 could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace SSIAM VN30 when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back SSIAM VN30 - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling SSIAM VN30 ETF to buy it.
Related Correlations Analysis
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Correlation Matchups
Over a given time period, the two securities move together when the Correlation Coefficient is positive. Conversely, the two assets move in opposite directions when the Correlation Coefficient is negative. Determining your positions' relationship to each other is valuable for analyzing and projecting your portfolio's future expected return and risk.High positive correlations
| High negative correlations
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SSIAM VN30 Competition Risk-Adjusted Indicators
There is a big difference between SSIAM Etf performing well and SSIAM VN30 ETF doing well as a business compared to the competition. There are so many exceptions to the norm that investors cannot definitively determine what's good or bad unless they analyze SSIAM VN30's multiple risk-adjusted performance indicators across the competitive landscape. These indicators are quantitative in nature and help investors forecast volatility and risk-adjusted expected returns across various positions.| Mean Deviation | Jensen Alpha | Sortino Ratio | Treynor Ratio | Semi Deviation | Expected Shortfall | Potential Upside | Value @Risk | Maximum Drawdown | ||
|---|---|---|---|---|---|---|---|---|---|---|
| META | 1.07 | 0.07 | 0.02 | 0.23 | 1.41 | 2.62 | 8.02 | |||
| MSFT | 0.90 | (0.04) | (0.05) | 0.07 | 1.50 | 2.09 | 8.19 | |||
| UBER | 1.61 | (0.11) | (0.04) | 0.02 | 2.32 | 2.69 | 20.10 | |||
| F | 1.42 | (0.15) | (0.04) | 0.03 | 2.23 | 2.53 | 11.21 | |||
| T | 0.92 | 0.26 | 0.12 | (7.83) | 0.86 | 2.56 | 6.47 | |||
| A | 1.17 | (0.09) | 0.00 | (0.06) | 0.00 | 2.71 | 9.02 | |||
| CRM | 1.31 | 0.23 | 0.18 | 0.34 | 1.08 | 3.18 | 9.98 | |||
| JPM | 1.12 | (0.04) | 0.05 | 0.11 | 1.38 | 2.05 | 15.87 | |||
| MRK | 0.91 | (0.24) | 0.00 | (0.86) | 0.00 | 2.00 | 4.89 | |||
| XOM | 1.00 | (0.03) | (0.07) | 0.06 | 1.31 | 2.10 | 5.74 |
SSIAM VN30 Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with SSIAM VN30 etf to make a market-neutral strategy. Peer analysis of SSIAM VN30 could also be used in its relative valuation, which is a method of valuing SSIAM VN30 by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |