PHD Etf Forecast - Accumulation Distribution
| PHD Etf | USD 10.12 0.00 0.00% |
PHD Etf Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast PHD stock prices and determine the direction of PHD's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of PHD's historical fundamentals, such as revenue growth or operating cash flow patterns.
At the present time the relative strength momentum indicator of PHD's share price is below 20 indicating that the etf is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards. Momentum 0
Sell Peaked
Oversold | Overbought |
Using PHD hype-based prediction, you can estimate the value of PHD from the perspective of PHD response to recently generated media hype and the effects of current headlines on its competitors.
PHD after-hype prediction price | $ 10.12 |
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 Your Equity Center to better understand how to build diversified portfolios. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in rate. PHD Additional Predictive Modules
Most predictive techniques to examine PHD price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for PHD using various technical indicators. When you analyze PHD 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 |
| Check PHD Volatility | Backtest PHD | Information Ratio |
PHD Trading Date Momentum
| On January 25 2026 PHD was traded for 10.12 at the closing time. Highest PHD's price during the trading hours was 10.12 and the lowest price during the day was 10.12 . There was no trading activity during the period 0.0. Lack of trading volume on the 25th of January did not cause price change. The trading delta at closing time to current price is 0.00% . |
Accumulation distribution indicator can signal that a trend is either nearing completion, at a continuation, or is about to break-outs. The actual value of this indicator is of no significance. What is significant is the change in value of over time. The formula for A/D of a given trading day can be expressed as follow: ((Close - Low) - (High - Close)) / (High - Low) X Volume
Compare PHD to competition
PHD 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 PHD etf to make a market-neutral strategy. Peer analysis of PHD could also be used in its relative valuation, which is a method of valuing PHD by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
PHD Market Strength Events
Market strength indicators help investors to evaluate how PHD etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading PHD shares will generate the highest return on investment. By undertsting and applying PHD etf market strength indicators, traders can identify PHD entry and exit signals to maximize returns.
PHD Risk Indicators
The analysis of PHD's 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 PHD's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting phd 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 | 0.2399 | |||
| Semi Deviation | 0.1214 | |||
| Standard Deviation | 0.4017 | |||
| Variance | 0.1614 | |||
| Downside Variance | 0.1049 | |||
| Semi Variance | 0.0147 | |||
| Expected Short fall | (0.33) |
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 PHD
The number of cover stories for PHD depends on current market conditions and PHD's risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that PHD 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 PHD's long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
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PHD Short Properties
PHD's future price predictability will typically decrease when PHD's long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of PHD often depends not only on the future outlook of the potential PHD's investors but also on the ongoing dynamics between investors with different trading styles. Because the market risk indicators may have small false signals, it is better to identify suitable times to hedge a portfolio using different long/short signals. PHD's indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 12.4 M | |
| Cash And Short Term Investments | 159 K |
Check out Your Equity Center to better understand how to build diversified portfolios. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in rate. You can also try the Idea Breakdown module to analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes.
The market value of PHD is measured differently than its book value, which is the value of PHD that is recorded on the company's balance sheet. Investors also form their own opinion of PHD's value that differs from its market value or its book value, called intrinsic value, which is PHD'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 PHD's market value can be influenced by many factors that don't directly affect PHD'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 PHD's value and its price as these two are different measures arrived at by different means. Investors typically determine if PHD is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, PHD'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.