IPath Series Etf Forward View - Simple Regression
| VXX Etf | USD 27.50 0.27 0.99% |
IPath Etf outlook is based on your current time horizon.
At this time, the relative strength momentum indicator of IPath Series' share price is approaching 46. This entails that the etf is in nutural position, most likellhy at or near its support level. The main point of RSI analysis is to track how fast people are buying or selling IPath Series, making its price go up or down. Momentum 46
Impartial
Oversold | Overbought |
Using IPath Series hype-based prediction, you can estimate the value of iPath Series B from the perspective of IPath Series response to recently generated media hype and the effects of current headlines on its competitors. We also analyze overall investor sentiment towards IPath Series using IPath Series' stock options and short interest. It helps to benchmark the overall future attitude of investors towards IPath using crowd psychology based on the activity and movement of IPath Series' stock price.
IPath Series Implied Volatility | 1.09 |
IPath Series' implied volatility exposes the market's sentiment of iPath Series B stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if IPath Series' implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that IPath Series stock will not fluctuate a lot when IPath Series' options are near their expiration.
The Simple Regression forecasted value of iPath Series B on the next trading day is expected to be 24.43 with a mean absolute deviation of 1.41 and the sum of the absolute errors of 87.34. IPath Series after-hype prediction price | USD 27.69 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as etf price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Check out Historical Fundamental Analysis of IPath Series to cross-verify your projections. Prediction based on Rule 16 of the current IPath contract
Based on the Rule 16, the options market is currently suggesting that iPath Series B will have an average daily up or down price movement of about 0.0681% per day over the life of the 2026-04-17 option contract. With IPath Series trading at USD 27.5, that is roughly USD 0.0187 . If you think that the market is fully incorporating IPath Series' daily price movement you should consider acquiring iPath Series B options at the current volatility level of 1.09%. But if you have an opposite viewpoint you should avoid it and even consider selling them.
Open Interest Against 2026-04-17 IPath Option Contracts
Although open interest is a measure utilized in the options markets, it could be used to forecast IPath Series' spot prices because the number of available contracts in the market changes daily, and new contracts can be created or liquidated at will. Since open interest in IPath Series' options reflects these daily shifts, investors could use the patterns of these changes to develop long and short-term trading strategies for IPath Series stock based on available contracts left at the end of a trading day.
Please note that to derive more accurate forecasting about market movement from the current IPath Series' open interest, investors have to compare it to IPath Series' spot prices. As Ford's stock price increases, high open interest indicates that money is entering the market, and the market is strongly bullish. Conversely, if the price of IPath Series is decreasing and there is high open interest, that is a sign that the bearish trend will continue, and investors may react by taking short positions in IPath. So, decreasing or low open interest during a bull market indicates that investors are becoming uncertain of the depth of the bullish trend, and a reversal in sentiment will likely follow.
IPath Series Additional Predictive Modules
Most predictive techniques to examine IPath price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for IPath using various technical indicators. When you analyze IPath charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
IPath Series Simple Regression Price Forecast For the 1st of February
Given 90 days horizon, the Simple Regression forecasted value of iPath Series B on the next trading day is expected to be 24.43 with a mean absolute deviation of 1.41, mean absolute percentage error of 3.38, and the sum of the absolute errors of 87.34.Please note that although there have been many attempts to predict IPath Etf prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that IPath Series' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
IPath Series Etf Forecast Pattern
| Backtest IPath Series | IPath Series Price Prediction | Buy or Sell Advice |
IPath Series Forecasted Value
In the context of forecasting IPath Series' Etf value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. IPath Series' downside and upside margins for the forecasting period are 21.18 and 27.68, respectively. We have considered IPath Series' daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of IPath Series etf data series using in forecasting. Note that when a statistical model is used to represent IPath Series 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 | 121.1667 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 1.4086 |
| MAPE | Mean absolute percentage error | 0.0466 |
| SAE | Sum of the absolute errors | 87.3354 |
Predictive Modules for IPath Series
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as iPath Series B. Regardless of method or technology, however, to accurately forecast the etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the etf market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of IPath Series' 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.
IPath Series After-Hype Price Density Analysis
As far as predicting the price of IPath Series at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in IPath Series or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Etf prices, such as prices of IPath Series, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
IPath Series Estimiated After-Hype Price Volatility
In the context of predicting IPath Series' etf value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on IPath Series' historical news coverage. IPath Series' after-hype downside and upside margins for the prediction period are 24.44 and 30.94, respectively. We have considered IPath Series' daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
IPath Series is not too volatile at this time. Analysis and calculation of next after-hype price of iPath Series B is based on 3 months time horizon.
IPath Series Etf Price Outlook Analysis
Have you ever been surprised when a price of a ETF such as IPath Series is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading IPath Series backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Etf price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with IPath Series, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.28 | 3.25 | 0.19 | 0.01 | 3 Events / Month | 3 Events / Month | In about 3 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | |
27.50 | 27.69 | 0.69 |
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IPath Series Hype Timeline
On the 31st of January iPath Series B is traded for 27.50. The entity has historical hype elasticity of 0.19, and average elasticity to hype of competition of 0.01. IPath is anticipated to increase in value after the next headline, with the price projected to jump to 27.69 or above. The average volatility of media hype impact on the company the price is over 100%. The price jump on the next news is anticipated to be 0.69%, whereas the daily expected return is at this time at -0.28%. The volatility of related hype on IPath Series is about 7558.14%, with the expected price after the next announcement by competition of 27.51. The company reported the last year's revenue of 31.81 B. Total Income to common stockholders was 911 M. Considering the 90-day investment horizon the next anticipated press release will be in about 3 days. Check out Historical Fundamental Analysis of IPath Series to cross-verify your projections.IPath Series Related Hype Analysis
Having access to credible news sources related to IPath Series' direct competition is more important than ever and may enhance your ability to predict IPath Series' future price movements. Getting to know how IPath Series' peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how IPath Series may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| VXZ | iPath Series B | (0.07) | 1 per month | 0.00 | (0.11) | 1.50 | (1.85) | 5.95 | |
| GSG | iShares SP GSCI | (0.08) | 2 per month | 0.64 | 0.12 | 1.55 | (1.29) | 3.21 | |
| IWC | iShares Micro Cap ETF | 1.59 | 3 per month | 1.35 | 0.05 | 2.13 | (1.92) | 5.01 | |
| ISPY | ProShares SP 500 | 0.14 | 1 per month | 0.78 | (0.02) | 1.06 | (1.27) | 3.42 | |
| AGQ | ProShares Ultra Silver | (0.84) | 10 per month | 5.08 | 0.38 | 13.58 | (6.59) | 35.80 | |
| DFIP | Dimensional ETF Trust | 0.02 | 5 per month | 0.00 | (0.35) | 0.29 | (0.29) | 0.84 | |
| LDUR | PIMCO Enhanced Low | (0.02) | 1 per month | 0.00 | (0.61) | 0.12 | (0.10) | 0.36 | |
| FJUN | FT Cboe Vest | (0.22) | 4 per month | 0.20 | (0.08) | 0.46 | (0.53) | 1.59 | |
| PSEP | Innovator SP 500 | (0.08) | 5 per month | 0.27 | (0.10) | 0.45 | (0.55) | 1.71 | |
| PDEC | Innovator SP 500 | (0.01) | 4 per month | 0.34 | (0.02) | 0.60 | (0.60) | 2.50 |
Other Forecasting Options for IPath Series
For every potential investor in IPath, whether a beginner or expert, IPath Series' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. IPath Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in IPath. Basic forecasting techniques help filter out the noise by identifying IPath Series' price trends.IPath Series Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with IPath Series etf to make a market-neutral strategy. Peer analysis of IPath Series could also be used in its relative valuation, which is a method of valuing IPath Series by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
IPath Series Market Strength Events
Market strength indicators help investors to evaluate how IPath Series etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading IPath Series shares will generate the highest return on investment. By undertsting and applying IPath Series etf market strength indicators, traders can identify iPath Series B entry and exit signals to maximize returns.
IPath Series Risk Indicators
The analysis of IPath Series' basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in IPath Series' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting ipath etf prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 2.23 | |||
| Standard Deviation | 3.18 | |||
| Variance | 10.12 |
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 IPath Series
The number of cover stories for IPath Series depends on current market conditions and IPath Series' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that IPath Series is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about IPath Series' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
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Check out Historical Fundamental Analysis of IPath Series to cross-verify your projections. You can also try the Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.
The market value of iPath Series B is measured differently than its book value, which is the value of IPath that is recorded on the company's balance sheet. Investors also form their own opinion of IPath Series' value that differs from its market value or its book value, called intrinsic value, which is IPath 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 IPath Series' market value can be influenced by many factors that don't directly affect IPath 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 IPath Series' value and its price as these two are different measures arrived at by different means. Investors typically determine if IPath Series is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. Meanwhile, IPath Series' quoted price indicates the marketplace figure where supply meets demand through bilateral consent.