ProShares Short Etf Forward View - Simple Exponential Smoothing
| PSQ Etf | USD 31.64 -0.21 -0.66% |
The Simple Exponential Smoothing forecast shown here for ProShares Short is reference data produced from its historical price series. The projected value and error measures below serve as reference information.
The Simple Exponential Smoothing forecasted value of ProShares Short QQQ on the next trading day is expected to be 31.65 with a mean absolute deviation of 0.25 and the sum of the absolute errors of 15.02.This simple exponential smoothing model begins by setting ProShares Short QQQ forecast for the second period equal to the observation of the first period. In other words, recent ProShares Short observations are given relatively more weight in forecasting than the older observations. This Simple Exponential Smoothing reference page for ProShares Short presents model-generated projections from historical price data for informational purposes. Simple Exponential Smoothing Price Forecast For the 27th of March
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of ProShares Short QQQ on the next trading day is expected to be 31.65 with a mean absolute deviation of 0.25 , mean absolute percentage error of 0.09 , and the sum of the absolute errors of 15.02 .Please note that although there have been many attempts to predict ProShares Etf prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that ProShares Short's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Etf Forecast Pattern
| Backtest ProShares Short | ProShares Short Price Prediction | Research Analysis |
Forecasted Value
Forecasting ProShares Short QQQ for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. At the moment, the model places downside around 30.64 and upside around 32.65 for the forecasting period.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of ProShares Short etf data series using in forecasting. Note that when a statistical model is used to represent ProShares Short etf, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 115.7088 |
| Bias | Arithmetic mean of the errors | -0.0427 |
| MAD | Mean absolute deviation | 0.2462 |
| MAPE | Mean absolute percentage error | 0.0081 |
| SAE | Sum of the absolute errors | 15.0186 |
Other Forecasting Options for ProShares Short
The distribution of ProShares Short's daily returns is typically non-normal, with fatter tails than a Gaussian model predicts. This can reveal hidden support and resistance zones in ProShares Short's chart that simple price charts miss.ProShares Short Related Equities
These firms work in a similar space as ProShares Short within the Trading--Inverse Equity space and serve as useful points for comparison. Checking ProShares Short against peers on P/E, margins, and return on equity helps put its position in context. Firms that trade at big discounts to peers on core metrics may be worth more research. This type of review is most useful when done often to track how positions shift over time.
| Risk & Return | Correlation |
ProShares Short Market Strength Events
Market strength indicators for ProShares Short give insight into the etf's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in ProShares Short QQQ.
ProShares Short Risk Indicators
A thorough review of ProShares Short's risk indicators is an important first step in forecasting its price. Quantifying the risk involved in ProShares Short's allows investors to make better decisions about entry, sizing, and hedging.
| Mean Deviation | 0.7954 | |||
| Semi Deviation | 0.8008 | |||
| Standard Deviation | 0.9837 | |||
| Variance | 0.9677 | |||
| Downside Variance | 0.8068 | |||
| Semi Variance | 0.6413 | |||
| Expected Short fall | -0.89 |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
Story Coverage note for ProShares Short
A coverage review of ProShares Short QQQ shows when the security is attracting above-average attention from contributors and market observers. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.
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More Resources for ProShares Etf Analysis
Analysis of ProShares Short QQQ often begins with its financial statements and historical patterns. Ratios connect earnings, costs, and operational efficiency.Historical Fundamental Analysis of ProShares Short offers a historical basis for evaluating projection assumptions about ProShares Short. This analysis of ProShares Short works best as a complementary layer when evaluating how the security fits in a broader portfolio. ProShares Short analysis across multiple dimensions - risk, valuation, diversification - produces a more informed position-sizing decision. You can also try the Money Managers module to screen money managers from public funds and ETFs managed around the world.
ProShares Short QQQ can be assessed through both market valuation and accounting book value, which often tell different stories. Intrinsic value provides a third perspective, grounded in fundamentals rather than accounting convention or market sentiment.
ProShares Short's value is shaped by fundamental inputs, whereas price is shaped by supply and demand dynamics. All values are based on available data and provided as reference information.