SPDR SP (Australia) Market Value
| WEMG Etf | 26.07 0.06 0.23% |
| Symbol | SPDR |
SPDR SP '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 SPDR SP'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 SPDR SP.
| 05/16/2024 |
| 12/12/2024 |
If you would invest 0.00 in SPDR SP on May 16, 2024 and sell it all today you would earn a total of 0.00 from holding SPDR SP Emerging or generate 0.0% return on investment in SPDR SP over 210 days. SPDR SP is related to or competes with Betashares Asia, BetaShares Australia, Australian High, and Vanguard Australian. SPDR SP is entity of Australia. It is traded as Etf on AU exchange. More
SPDR SP 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 SPDR SP'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 SPDR SP Emerging upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.7087 | |||
| Information Ratio | 0.0814 | |||
| Maximum Drawdown | 4.13 | |||
| Value At Risk | (1.10) | |||
| Potential Upside | 1.88 |
SPDR SP Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for SPDR SP's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as SPDR SP's standard deviation. In reality, there are many statistical measures that can use SPDR SP historical prices to predict the future SPDR SP's volatility.| Risk Adjusted Performance | 0.167 | |||
| Jensen Alpha | 0.1695 | |||
| Total Risk Alpha | 0.0496 | |||
| Sortino Ratio | 0.0967 | |||
| Treynor Ratio | 1.54 |
SPDR SP Emerging Backtested Returns
Currently, SPDR SP Emerging is very steady. SPDR SP Emerging owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.21, which indicates the etf had a 0.21% return per unit of volatility over the last 3 months. We have found twenty-eight technical indicators for SPDR SP Emerging, which you can use to evaluate the volatility of the etf. Please validate SPDR SP's risk adjusted performance of 0.167, and Coefficient Of Variation of 436.24 to confirm if the risk estimate we provide is consistent with the expected return of 0.18%. The entity has a beta of 0.12, which indicates not very significant fluctuations relative to the market. As returns on the market increase, SPDR SP's returns are expected to increase less than the market. However, during the bear market, the loss of holding SPDR SP is expected to be smaller as well.
Auto-correlation | 0.46 |
Average predictability
SPDR SP Emerging has average predictability. Overlapping area represents the amount of predictability between SPDR SP time series from 16th of May 2024 to 29th of August 2024 and 29th of August 2024 to 12th 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 SPDR SP Emerging price movement. The serial correlation of 0.46 indicates that about 46.0% of current SPDR SP price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.46 | |
| Spearman Rank Test | 0.22 | |
| Residual Average | 0.0 | |
| Price Variance | 0.85 |
SPDR SP Emerging lagged returns against current returns
Autocorrelation, which is SPDR SP 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 SPDR SP's etf expected returns. We can calculate the autocorrelation of SPDR SP returns to help us make a trade decision. For example, suppose you find that SPDR SP 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 |
SPDR SP 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 SPDR SP etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if SPDR SP etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in SPDR SP etf over time.
Current vs Lagged Prices |
| Timeline |
SPDR SP Lagged Returns
When evaluating SPDR SP's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of SPDR SP etf have on its future price. SPDR SP 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, SPDR SP autocorrelation shows the relationship between SPDR SP etf current value and its past values and can show if there is a momentum factor associated with investing in SPDR SP Emerging.
Regressed Prices |
| Timeline |
Thematic Opportunities
Explore Investment Opportunities
Check out SPDR SP Correlation, SPDR SP Volatility and SPDR SP Alpha and Beta module to complement your research on SPDR SP. You can also try the Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
SPDR SP technical etf analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, etf market cycles, or different charting patterns.