Spdr Msci Emerging Etf Market Value
| EEMX Etf | USD 33.30 0.02 0.06% |
| Symbol | SPDR |
The market value of SPDR MSCI Emerging is measured differently than its book value, which is the value of SPDR that is recorded on the company's balance sheet. Investors also form their own opinion of SPDR MSCI's value that differs from its market value or its book value, called intrinsic value, which is SPDR MSCI's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because SPDR MSCI's market value can be influenced by many factors that don't directly affect SPDR MSCI's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between SPDR MSCI's value and its price as these two are different measures arrived at by different means. Investors typically determine if SPDR MSCI is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, SPDR MSCI's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.
SPDR MSCI '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 MSCI'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 MSCI.
| 10/31/2024 |
| 11/30/2024 |
If you would invest 0.00 in SPDR MSCI on October 31, 2024 and sell it all today you would earn a total of 0.00 from holding SPDR MSCI Emerging or generate 0.0% return on investment in SPDR MSCI over 30 days. SPDR MSCI is related to or competes with SPDR MSCI, SPDR MSCI, SPDR DoubleLine, SPDR MSCI, and SPDR SP. Under normal market conditions, the fund generally invests substantially all, but at least 80, of its total assets in th... More
SPDR MSCI 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 MSCI'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 MSCI Emerging upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.17 | |||
| Information Ratio | (0.1) | |||
| Maximum Drawdown | 6.65 | |||
| Value At Risk | (2.08) | |||
| Potential Upside | 2.01 |
SPDR MSCI Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for SPDR MSCI's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as SPDR MSCI's standard deviation. In reality, there are many statistical measures that can use SPDR MSCI historical prices to predict the future SPDR MSCI's volatility.| Risk Adjusted Performance | 0.0149 | |||
| Jensen Alpha | (0.04) | |||
| Total Risk Alpha | (0.20) | |||
| Sortino Ratio | (0.10) | |||
| Treynor Ratio | 0.0212 |
SPDR MSCI Emerging Backtested Returns
At this stage we consider SPDR Etf to be very steady. SPDR MSCI Emerging owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0389, which indicates the etf had a 0.0389% return per unit of volatility over the last 3 months. We have found thirty technical indicators for SPDR MSCI Emerging, which you can use to evaluate the volatility of the etf. Please validate SPDR MSCI's risk adjusted performance of 0.0149, and Coefficient Of Variation of 6857.44 to confirm if the risk estimate we provide is consistent with the expected return of 0.0471%. The entity has a beta of 0.37, which indicates possible diversification benefits within a given portfolio. As returns on the market increase, SPDR MSCI's returns are expected to increase less than the market. However, during the bear market, the loss of holding SPDR MSCI is expected to be smaller as well.
Auto-correlation | 0.53 |
Modest predictability
SPDR MSCI Emerging has modest predictability. Overlapping area represents the amount of predictability between SPDR MSCI time series from 31st of October 2024 to 15th of November 2024 and 15th of November 2024 to 30th of November 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 MSCI Emerging price movement. The serial correlation of 0.53 indicates that about 53.0% of current SPDR MSCI price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.53 | |
| Spearman Rank Test | -0.24 | |
| Residual Average | 0.0 | |
| Price Variance | 0.02 |
SPDR MSCI Emerging lagged returns against current returns
Autocorrelation, which is SPDR MSCI 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 MSCI's etf expected returns. We can calculate the autocorrelation of SPDR MSCI returns to help us make a trade decision. For example, suppose you find that SPDR MSCI 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 MSCI 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 MSCI etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if SPDR MSCI etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in SPDR MSCI etf over time.
Current vs Lagged Prices |
| Timeline |
SPDR MSCI Lagged Returns
When evaluating SPDR MSCI's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of SPDR MSCI etf have on its future price. SPDR MSCI 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 MSCI autocorrelation shows the relationship between SPDR MSCI etf current value and its past values and can show if there is a momentum factor associated with investing in SPDR MSCI Emerging.
Regressed Prices |
| Timeline |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.When determining whether SPDR MSCI Emerging is a strong investment it is important to analyze SPDR MSCI's competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact SPDR MSCI's future performance. For an informed investment choice regarding SPDR Etf, refer to the following important reports:Check out SPDR MSCI Correlation, SPDR MSCI Volatility and SPDR MSCI Alpha and Beta module to complement your research on SPDR MSCI. You can also try the Portfolio Anywhere module to track or share privately all of your investments from the convenience of any device.
SPDR MSCI 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.