Spdr Series Trust Etf Market Value
| CERY Etf | 25.82 0.03 0.12% |
| Symbol | SPDR |
The market value of SPDR Series Trust 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 Series' value that differs from its market value or its book value, called intrinsic value, which is SPDR Series' 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 Series' market value can be influenced by many factors that don't directly affect SPDR Series' 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 Series' value and its price as these two are different measures arrived at by different means. Investors typically determine if SPDR Series is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, SPDR Series' 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 Series '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 Series' 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 Series.
| 10/29/2024 |
| 11/28/2024 |
If you would invest 0.00 in SPDR Series on October 29, 2024 and sell it all today you would earn a total of 0.00 from holding SPDR Series Trust or generate 0.0% return on investment in SPDR Series over 30 days. SPDR Series is related to or competes with ETRACS Bloomberg, Neuberger Berman, Invesco DB, IPath Bloomberg, WisdomTree Continuous, and IShares SP. More
SPDR Series 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 Series' 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 Series Trust upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.9135 | |||
| Information Ratio | (0.08) | |||
| Maximum Drawdown | 3.47 | |||
| Value At Risk | (1.40) | |||
| Potential Upside | 1.39 |
SPDR Series Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for SPDR Series' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as SPDR Series' standard deviation. In reality, there are many statistical measures that can use SPDR Series historical prices to predict the future SPDR Series' volatility.| Risk Adjusted Performance | 0.0548 | |||
| Jensen Alpha | 0.0217 | |||
| Total Risk Alpha | (0.07) | |||
| Sortino Ratio | (0.07) | |||
| Treynor Ratio | 0.2136 |
SPDR Series Trust Backtested Returns
SPDR Series is out of control given 3 months investment horizon. SPDR Series Trust owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.13, which indicates the etf had a 0.13% return per unit of volatility over the last 3 months. We were able to interpolate data for twenty-eight different technical indicators, which can help you to evaluate if expected returns of 16.45% are justified by taking the suggested risk. Use SPDR Series Trust coefficient of variation of 1410.7, and Risk Adjusted Performance of 0.0548 to evaluate company specific risk that cannot be diversified away. The entity has a beta of 0.22, which indicates not very significant fluctuations relative to the market. As returns on the market increase, SPDR Series' returns are expected to increase less than the market. However, during the bear market, the loss of holding SPDR Series is expected to be smaller as well.
Auto-correlation | 0.31 |
Below average predictability
SPDR Series Trust has below average predictability. Overlapping area represents the amount of predictability between SPDR Series time series from 29th of October 2024 to 13th of November 2024 and 13th of November 2024 to 28th 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 Series Trust price movement. The serial correlation of 0.31 indicates that nearly 31.0% of current SPDR Series price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.31 | |
| Spearman Rank Test | -0.21 | |
| Residual Average | 0.0 | |
| Price Variance | 0.05 |
SPDR Series Trust lagged returns against current returns
Autocorrelation, which is SPDR Series 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 Series' etf expected returns. We can calculate the autocorrelation of SPDR Series returns to help us make a trade decision. For example, suppose you find that SPDR Series 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 Series 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 Series etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if SPDR Series etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in SPDR Series etf over time.
Current vs Lagged Prices |
| Timeline |
SPDR Series Lagged Returns
When evaluating SPDR Series' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of SPDR Series etf have on its future price. SPDR Series 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 Series autocorrelation shows the relationship between SPDR Series etf current value and its past values and can show if there is a momentum factor associated with investing in SPDR Series Trust.
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 Series Trust offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of SPDR Series' financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Spdr Series Trust Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Spdr Series Trust Etf:Check out SPDR Series Correlation, SPDR Series Volatility and SPDR Series Alpha and Beta module to complement your research on SPDR Series. You can also try the Sign In To Macroaxis module to sign in to explore Macroaxis' wealth optimization platform and fintech modules.
SPDR Series 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.