BNP Paribas (Germany) Price Prediction
| 0P0000HR6L | EUR 158.89 2.00 1.24% |
Oversold Vs Overbought
50
Oversold | Overbought |
Using BNP Paribas hype-based prediction, you can estimate the value of BNP Paribas Midcap from the perspective of BNP Paribas response to recently generated media hype and the effects of current headlines on its competitors.
The fear of missing out, i.e., FOMO, can cause potential investors in BNP Paribas to buy its fund at a price that has no basis in reality. In that case, they are not buying BNP because the equity is a good investment, but because they need to do something to avoid the feeling of missing out. On the other hand, investors will often sell funds at prices well below their value during bear markets because they need to stop feeling the pain of losing money.
BNP Paribas after-hype prediction price | EUR 158.89 |
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 fund price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
BNP |
BNP Paribas After-Hype Price Prediction Density Analysis
As far as predicting the price of BNP Paribas 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 BNP Paribas 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 Fund prices, such as prices of BNP Paribas, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
BNP Paribas Estimiated After-Hype Price Volatility
In the context of predicting BNP Paribas' fund value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on BNP Paribas' historical news coverage. BNP Paribas' after-hype downside and upside margins for the prediction period are 158.16 and 159.62, respectively. We have considered BNP Paribas' 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
BNP Paribas is very steady at this time. Analysis and calculation of next after-hype price of BNP Paribas Midcap is based on 3 months time horizon.
BNP Paribas Fund Price Prediction Analysis
Have you ever been surprised when a price of a Fund such as BNP Paribas is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading BNP Paribas 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 Fund 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 BNP Paribas, 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 |
0.10 | 0.73 | 0.00 | 0.00 | 0 Events / Month | 0 Events / Month | In 5 to 10 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
158.89 | 158.89 | 0.00 |
|
BNP Paribas Hype Timeline
BNP Paribas Midcap is presently traded for 158.89on Frankfurt Exchange of Germany. The entity stock is not elastic to its hype. The average elasticity to hype of competition is 0.0. BNP is estimated not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is insignificant. The immediate return on the next news is estimated to be very small, whereas the daily expected return is presently at -0.1%. %. The volatility of related hype on BNP Paribas is about 0.0%, with the expected price after the next announcement by competition of 158.89. The company had not issued any dividends in recent years. Assuming the 90 days trading horizon the next estimated press release will be in 5 to 10 days. Check out BNP Paribas Basic Forecasting Models to cross-verify your projections.BNP Paribas Related Hype Analysis
Having access to credible news sources related to BNP Paribas' direct competition is more important than ever and may enhance your ability to predict BNP Paribas' future price movements. Getting to know how BNP Paribas' 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 BNP Paribas may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| 0P00017QSQ | Esfera Robotics R | 0.00 | 0 per month | 0.88 | 0.15 | 1.64 | (1.62) | 7.05 | |
| 0P00017SX2 | R co Valor F | 0.00 | 0 per month | 0.64 | 0.08 | 1.32 | (1.17) | 3.39 | |
| 0P0001F96C | CM AM Monplus NE | 0.00 | 0 per month | 0.00 | (2.25) | 0.03 | 0.00 | 0.04 | |
| 0P0000MZYR | IE00B0H4TS55 | 0.00 | 0 per month | 0.00 | (0.30) | 0.24 | (0.45) | 1.08 | |
| 0P0001OSNK | BEKA LUX SICAV | 0.00 | 0 per month | 0.19 | (0.07) | 0.45 | (0.35) | 1.16 | |
| XE67 | Nordea 1 SICAV | 0.00 | 0 per month | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | |
| HJUI | DWS Aktien Strategie | 0.00 | 0 per month | 1.00 | (0.01) | 1.33 | (1.77) | 5.94 | |
| ERD8 | BGF Euro Markets | 0.00 | 0 per month | 0.90 | (0) | 1.90 | (1.41) | 5.89 | |
| 0P0000VQ56 | Impact ISR Performance | 0.00 | 0 per month | 0.00 | (0.15) | 0.69 | (1.16) | 2.45 |
BNP Paribas Additional Predictive Modules
Most predictive techniques to examine BNP price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for BNP using various technical indicators. When you analyze BNP 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 |
About BNP Paribas Predictive Indicators
The successful prediction of BNP Paribas stock price could yield a significant profit to investors. But is it possible? The efficient-market hypothesis suggests that all published stock prices of traded companies, such as BNP Paribas Midcap, already reflect all publicly available information. This academic statement is a fundamental principle of many financial and investing theories used today. However, the typical investor usually disagrees with a 'textbook' version of this hypothesis and continually tries to find mispriced stocks to increase returns. We use internally-developed statistical techniques to arrive at the intrinsic value of BNP Paribas based on analysis of BNP Paribas hews, social hype, general headline patterns, and widely used predictive technical indicators.
We also calculate exposure to BNP Paribas's market risk, different technical and fundamental indicators, relevant financial multiples and ratios, and then comparing them to BNP Paribas's related companies.
Story Coverage note for BNP Paribas
The number of cover stories for BNP Paribas depends on current market conditions and BNP Paribas' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that BNP Paribas 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 BNP Paribas' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Other Macroaxis Stories
Our audience includes start-ups and big corporations as well as marketing, public relation firms, and advertising agencies, including technology and finance journalists. Our platform and its news and story outlet are popular among finance students, amateur traders, self-guided investors, entrepreneurs, retirees and baby boomers, academic researchers, financial advisers, as well as professional money managers - a very diverse and influential demographic landscape united by one goal - build optimal investment portfolios
Story Categories
Currently Trending Categories
Other Information on Investing in BNP Fund
BNP Paribas financial ratios help investors to determine whether BNP Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in BNP with respect to the benefits of owning BNP Paribas security.
| Odds Of Bankruptcy Get analysis of equity chance of financial distress in the next 2 years | |
| Portfolio File Import Quickly import all of your third-party portfolios from your local drive in csv format | |
| Sign In To Macroaxis Sign in to explore Macroaxis' wealth optimization platform and fintech modules | |
| Headlines Timeline Stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity |