Series Portfolios Trust Etf Market Value
| SCAP Etf | USD 35.89 0.00 0.00% |
| Symbol | Series |
The market value of Series Portfolios Trust is measured differently than its book value, which is the value of Series that is recorded on the company's balance sheet. Investors also form their own opinion of Series Portfolios' value that differs from its market value or its book value, called intrinsic value, which is Series Portfolios' 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 Series Portfolios' market value can be influenced by many factors that don't directly affect Series Portfolios' 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 Series Portfolios' value and its price as these two are different measures arrived at by different means. Investors typically determine if Series Portfolios is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Series Portfolios' 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.
Series Portfolios '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 Series Portfolios' 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 Series Portfolios.
| 12/21/2024 |
| 01/20/2025 |
If you would invest 0.00 in Series Portfolios on December 21, 2024 and sell it all today you would earn a total of 0.00 from holding Series Portfolios Trust or generate 0.0% return on investment in Series Portfolios over 30 days. Series Portfolios is related to or competes with FundX Aggressive, FT Vest, Zillow Group, Northern Lights, VanEck Vectors, and Freedom Day. The investment seeks to provide total return through long-term capital appreciation and current income More
Series Portfolios 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 Series Portfolios' 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 Series Portfolios Trust upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.09 | |||
| Information Ratio | 0.006 | |||
| Maximum Drawdown | 8.91 | |||
| Value At Risk | (1.52) | |||
| Potential Upside | 1.96 |
Series Portfolios Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Series Portfolios' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Series Portfolios' standard deviation. In reality, there are many statistical measures that can use Series Portfolios historical prices to predict the future Series Portfolios' volatility.| Risk Adjusted Performance | 0.0288 | |||
| Jensen Alpha | 0.0161 | |||
| Total Risk Alpha | (0) | |||
| Sortino Ratio | 0.0065 | |||
| Treynor Ratio | 0.0491 |
Series Portfolios Trust Backtested Returns
Currently, Series Portfolios Trust is very steady. Series Portfolios Trust owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0416, which indicates the etf had a 0.0416 % return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Series Portfolios Trust, which you can use to evaluate the volatility of the etf. Please validate Series Portfolios' Semi Deviation of 1.04, coefficient of variation of 3240.68, and Risk Adjusted Performance of 0.0288 to confirm if the risk estimate we provide is consistent with the expected return of 0.0496%. The entity has a beta of 0.55, which indicates possible diversification benefits within a given portfolio. As returns on the market increase, Series Portfolios' returns are expected to increase less than the market. However, during the bear market, the loss of holding Series Portfolios is expected to be smaller as well.
Auto-correlation | 0.66 |
Good predictability
Series Portfolios Trust has good predictability. Overlapping area represents the amount of predictability between Series Portfolios time series from 21st of December 2024 to 5th of January 2025 and 5th of January 2025 to 20th of January 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Series Portfolios Trust price movement. The serial correlation of 0.66 indicates that around 66.0% of current Series Portfolios price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.66 | |
| Spearman Rank Test | 0.55 | |
| Residual Average | 0.0 | |
| Price Variance | 0.41 |
Series Portfolios Trust lagged returns against current returns
Autocorrelation, which is Series Portfolios 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 Series Portfolios' etf expected returns. We can calculate the autocorrelation of Series Portfolios returns to help us make a trade decision. For example, suppose you find that Series Portfolios 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 |
Series Portfolios 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 Series Portfolios etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Series Portfolios etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Series Portfolios etf over time.
Current vs Lagged Prices |
| Timeline |
Series Portfolios Lagged Returns
When evaluating Series Portfolios' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Series Portfolios etf have on its future price. Series Portfolios 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, Series Portfolios autocorrelation shows the relationship between Series Portfolios etf current value and its past values and can show if there is a momentum factor associated with investing in Series Portfolios Trust.
Regressed Prices |
| Timeline |
Pair Trading with Series Portfolios
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 Series Portfolios 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 Series Portfolios will appreciate offsetting losses from the drop in the long position's value.Moving together with Series Etf
| 0.99 | VBR | Vanguard Small Cap | PairCorr |
| 0.97 | IWN | iShares Russell 2000 | PairCorr |
| 0.97 | DFAT | Dimensional Targeted | PairCorr |
| 0.94 | IJS | iShares SP Small | PairCorr |
| 0.93 | SLYV | SPDR SP 600 | PairCorr |
Moving against Series Etf
The ability to find closely correlated positions to Series Portfolios could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Series Portfolios 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 Series Portfolios - 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 Series Portfolios Trust to buy it.
The correlation of Series Portfolios 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 Series Portfolios moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Series Portfolios Trust 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 Series Portfolios 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 Series Portfolios Correlation, Series Portfolios Volatility and Series Portfolios Alpha and Beta module to complement your research on Series Portfolios. You can also try the Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
Series Portfolios 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.