SSIAM VN30 (Vietnam) Market Value
| FUESSV30 | 16,280 130.00 0.80% |
| Symbol | SSIAM |
SSIAM VN30 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to SSIAM VN30's etf what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of SSIAM VN30.
| 06/05/2024 |
| 12/02/2024 |
If you would invest 0.00 in SSIAM VN30 on June 5, 2024 and sell it all today you would earn a total of 0.00 from holding SSIAM VN30 ETF or generate 0.0% return on investment in SSIAM VN30 over 180 days.
SSIAM VN30 Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure SSIAM VN30's etf current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess SSIAM VN30 ETF upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.20) | |||
| Maximum Drawdown | 4.14 | |||
| Value At Risk | (1.30) | |||
| Potential Upside | 1.07 |
SSIAM VN30 Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for SSIAM VN30's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as SSIAM VN30's standard deviation. In reality, there are many statistical measures that can use SSIAM VN30 historical prices to predict the future SSIAM VN30's volatility.| Risk Adjusted Performance | (0.01) | |||
| Jensen Alpha | (0.06) | |||
| Total Risk Alpha | (0.14) | |||
| Treynor Ratio | (0.06) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of SSIAM VN30's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
SSIAM VN30 ETF Backtested Returns
SSIAM VN30 ETF owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.0054, which indicates the etf had a -0.0054% return per unit of volatility over the last 3 months. SSIAM VN30 ETF exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate SSIAM VN30's variance of 0.5581, and Risk Adjusted Performance of (0.01) to confirm the risk estimate we provide. The entity has a beta of 0.3, which indicates not very significant fluctuations relative to the market. As returns on the market increase, SSIAM VN30's returns are expected to increase less than the market. However, during the bear market, the loss of holding SSIAM VN30 is expected to be smaller as well.
Auto-correlation | -0.25 |
Weak reverse predictability
SSIAM VN30 ETF has weak reverse predictability. Overlapping area represents the amount of predictability between SSIAM VN30 time series from 5th of June 2024 to 3rd of September 2024 and 3rd of September 2024 to 2nd of December 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of SSIAM VN30 ETF price movement. The serial correlation of -0.25 indicates that over 25.0% of current SSIAM VN30 price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.25 | |
| Spearman Rank Test | 0.01 | |
| Residual Average | 0.0 | |
| Price Variance | 110 K |
SSIAM VN30 ETF lagged returns against current returns
Autocorrelation, which is SSIAM VN30 etf's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting SSIAM VN30's etf expected returns. We can calculate the autocorrelation of SSIAM VN30 returns to help us make a trade decision. For example, suppose you find that SSIAM VN30 has exhibited high autocorrelation historically, and you observe that the etf is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
SSIAM VN30 regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If SSIAM VN30 etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if SSIAM VN30 etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in SSIAM VN30 etf over time.
Current vs Lagged Prices |
| Timeline |
SSIAM VN30 Lagged Returns
When evaluating SSIAM VN30's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of SSIAM VN30 etf have on its future price. SSIAM VN30 autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, SSIAM VN30 autocorrelation shows the relationship between SSIAM VN30 etf current value and its past values and can show if there is a momentum factor associated with investing in SSIAM VN30 ETF.
Regressed Prices |
| Timeline |
Pair Trading with SSIAM VN30
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if SSIAM VN30 position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in SSIAM VN30 will appreciate offsetting losses from the drop in the long position's value.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.
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 perfect positive correlation (i.e., a correlation coefficient of +1) implies that as SSIAM VN30 moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if SSIAM VN30 ETF moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for SSIAM VN30 can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.