Spdr Ssga Sector Etf Market Value
| XLSR Etf | USD 54.38 0.21 0.39% |
| Symbol | SPDR |
The market value of SPDR SSGA Sector 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 SSGA's value that differs from its market value or its book value, called intrinsic value, which is SPDR SSGA'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 SSGA's market value can be influenced by many factors that don't directly affect SPDR SSGA'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 SSGA's value and its price as these two are different measures arrived at by different means. Investors typically determine if SPDR SSGA is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, SPDR SSGA'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 SSGA '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 SSGA'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 SSGA.
| 11/30/2023 |
| 11/24/2024 |
If you would invest 0.00 in SPDR SSGA on November 30, 2023 and sell it all today you would earn a total of 0.00 from holding SPDR SSGA Sector or generate 0.0% return on investment in SPDR SSGA over 360 days. SPDR SSGA is related to or competes with Morningstar Unconstrained, High-yield Municipal, Via Renewables, Knife River, Klckner Co, CarMax, and SEI Investments. The fund is a fund of funds, meaning that it primarily invests its assets in securities of other exchange-traded funds More
SPDR SSGA 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 SSGA'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 SSGA Sector upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.8809 | |||
| Information Ratio | (0.02) | |||
| Maximum Drawdown | 3.82 | |||
| Value At Risk | (1.24) | |||
| Potential Upside | 1.14 |
SPDR SSGA Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for SPDR SSGA's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as SPDR SSGA's standard deviation. In reality, there are many statistical measures that can use SPDR SSGA historical prices to predict the future SPDR SSGA's volatility.| Risk Adjusted Performance | 0.1074 | |||
| Jensen Alpha | (0) | |||
| Total Risk Alpha | (0.02) | |||
| Sortino Ratio | (0.02) | |||
| Treynor Ratio | 0.1181 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of SPDR SSGA'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.
SPDR SSGA Sector Backtested Returns
Currently, SPDR SSGA Sector is very steady. SPDR SSGA Sector 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 have found thirty technical indicators for SPDR SSGA Sector, which you can use to evaluate the volatility of the etf. Please validate SPDR SSGA's coefficient of variation of 716.77, and Risk Adjusted Performance of 0.1074 to confirm if the risk estimate we provide is consistent with the expected return of 0.1%. The entity has a beta of 0.86, which indicates possible diversification benefits within a given portfolio. SPDR SSGA returns are very sensitive to returns on the market. As the market goes up or down, SPDR SSGA is expected to follow.
Auto-correlation | 0.40 |
Average predictability
SPDR SSGA Sector has average predictability. Overlapping area represents the amount of predictability between SPDR SSGA time series from 30th of November 2023 to 28th of May 2024 and 28th of May 2024 to 24th 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 SSGA Sector price movement. The serial correlation of 0.4 indicates that just about 40.0% of current SPDR SSGA price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.4 | |
| Spearman Rank Test | 0.55 | |
| Residual Average | 0.0 | |
| Price Variance | 2.25 |
SPDR SSGA Sector lagged returns against current returns
Autocorrelation, which is SPDR SSGA 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 SSGA's etf expected returns. We can calculate the autocorrelation of SPDR SSGA returns to help us make a trade decision. For example, suppose you find that SPDR SSGA 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 SSGA 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 SSGA etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if SPDR SSGA etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in SPDR SSGA etf over time.
Current vs Lagged Prices |
| Timeline |
SPDR SSGA Lagged Returns
When evaluating SPDR SSGA's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of SPDR SSGA etf have on its future price. SPDR SSGA 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 SSGA autocorrelation shows the relationship between SPDR SSGA etf current value and its past values and can show if there is a momentum factor associated with investing in SPDR SSGA Sector.
Regressed Prices |
| Timeline |
Pair Trading with SPDR SSGA
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 SPDR SSGA 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 SPDR SSGA will appreciate offsetting losses from the drop in the long position's value.Moving together with SPDR Etf
| 0.99 | VTI | Vanguard Total Stock | PairCorr |
| 0.99 | SPY | SPDR SP 500 Aggressive Push | PairCorr |
| 0.99 | IVV | iShares Core SP | PairCorr |
| 0.91 | VIG | Vanguard Dividend | PairCorr |
| 0.99 | VV | Vanguard Large Cap | PairCorr |
Moving against SPDR Etf
| 0.86 | YCL | ProShares Ultra Yen | PairCorr |
| 0.86 | VIIX | VIIX | PairCorr |
| 0.85 | FXY | Invesco CurrencyShares | PairCorr |
| 0.84 | ULE | ProShares Ultra Euro | PairCorr |
The ability to find closely correlated positions to SPDR SSGA could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace SPDR SSGA 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 SPDR SSGA - 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 SPDR SSGA Sector to buy it.
The correlation of SPDR SSGA 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 SPDR SSGA moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if SPDR SSGA Sector 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 SPDR SSGA 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.Check out SPDR SSGA Correlation, SPDR SSGA Volatility and SPDR SSGA Alpha and Beta module to complement your research on SPDR SSGA. You can also try the Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
SPDR SSGA 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.