BNP Paribas (India) Probability of Future Fund Price Finishing Over 62.22

0P00005X1I -  India Fund  

INR 62.22  0.75  1.19%

BNP Paribas' future price is the expected price of BNP Paribas instrument. It is based on its current growth rate as well as the projected cash flow expected by the investors. This tool provides a mechanism to make assumptions about the upside potential and downside risk of BNP Paribas Long performance during a given time horizon utilizing its historical volatility.

0P00005X1I Price Probability 

 
Refresh
Please continue to BNP Paribas Backtesting, Portfolio Optimization, BNP Paribas Correlation, BNP Paribas Hype Analysis, BNP Paribas Volatility, BNP Paribas History as well as BNP Paribas Performance. Please specify BNP Paribas time horizon, a valid symbol (red box) and a target price (blue box) you would like BNP Paribas odds to be computed.
Apply Odds

BNP Paribas Target Price Odds to finish over 62.22

The tendency of 0P00005X1I Fund price to converge on an average value over time is a known aspect in finance that investors have used since the beginning of the stock market for foresting. However, many studies suggest that some traded equity instruments are consistently mispriced before traders' demand and supply correct the spread. One possible conclusion to this anomaly is that these stocks have additional risk, for which investors demand compensation in the form of extra returns.
Current PriceHorizonTarget PriceOdds to move above the current price in 90 days
 62.22 90 days 62.22  under 4
Based on a normal probability distribution, the odds of BNP Paribas to move above the current price in 90 days from now is under 4 (This BNP Paribas Long probability density function shows the probability of 0P00005X1I Fund to fall within a particular range of prices over 90 days) .
Assuming the 90 days trading horizon BNP Paribas has a beta of 0.12. This suggests as returns on the market go up, BNP Paribas average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding BNP Paribas Long will be expected to be much smaller as well. Additionally The company has an alpha of 0.184, implying that it can generate a 0.18 percent excess return over DOW after adjusting for the inherited market risk (beta).
 BNP Paribas Price Density 
      Price 

Predictive Modules for BNP Paribas

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as BNP Paribas Long. Regardless of method or technology, however, to accurately forecast the stock or bond market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock 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, frequently view the market will even out over time. This tendency of BNP Paribas' 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. Please use the tools below to analyze the current value of BNP Paribas in the context of predictive analytics.
Hype
Prediction
LowEstimated ValueHigh
61.4962.2262.95
Details
Intrinsic
Valuation
LowReal ValueHigh
56.0066.8667.59
Details
Naive
Forecast
LowNext ValueHigh
62.7163.4564.18
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
56.4359.8663.28
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as BNP Paribas. Your research has to be compared to or analyzed against BNP Paribas' peers to derive any actionable benefits. When done correctly, BNP Paribas' competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy towards taking a position in BNP Paribas Long.

BNP Paribas Risk Indicators

For the most part, the last 10-20 years have been a very volatile time for the stock market. BNP Paribas is not an exception. The market had few large corrections towards the BNP Paribas' value, including both sudden drops in prices as well as massive rallies. These swings have made and broken many portfolios. An investor can limit the violent swings in their portfolio by implementing a hedging strategy designed to limit downside losses. If you hold BNP Paribas Long, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of BNP Paribas within the framework of very fundamental risk indicators.
α
Alpha over DOW
0.18
β
Beta against DOW0.12
σ
Overall volatility
2.40
Ir
Information ratio 0.21

BNP Paribas Alerts and Suggestions

In today's market, stock alerts give investors the competitive edge they need to time the market and increase returns. Checking the ongoing alerts of BNP Paribas for significant developments is a great way to find new opportunities for your next move. Suggestions and notifications for BNP Paribas Long can help investors quickly react to important events or material changes in technical or fundamental conditions and significant headlines that can affect investment decisions.
BNP Paribas Long is unlikely to experience financial distress in the next 2 years
The fund holds 95.79% of its total net assets in equities

BNP Paribas Technical Analysis

BNP Paribas' future price can be derived by breaking down and analyzing its technical indicators over time. 0P00005X1I Fund technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of BNP Paribas Long. In general, you should focus on analyzing 0P00005X1I Fund price patterns and their correlations with different microeconomic environments and drivers.

BNP Paribas Predictive Forecast Models

BNP Paribas time-series forecasting models is one of many BNP Paribas' fund analysis techniquest aimed to predict future share value based on previously observed values. Time-series forecasting models ae widely used for non-stationary data. Non-stationary data are called the data whose statistical properties e.g. the mean and standard deviation are not constant over time but instead, these metrics vary over time. These non-stationary BNP Paribas' historical data is usually called time-series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the stock market movement and maximize returns from investment trading.

Things to note about BNP Paribas Long

Checking the ongoing alerts about BNP Paribas for important developments is a great way to find new opportunities for your next move. Our stock alerts and notifications screener for BNP Paribas Long help investors to be notified of important events, changes in technical or fundamental conditions, and significant headlines that can affect investment decisions.

BNP Paribas Alerts

BNP Paribas Alerts and Suggestions

BNP Paribas Long is unlikely to experience financial distress in the next 2 years
The fund holds 95.79% of its total net assets in equities
Please continue to BNP Paribas Backtesting, Portfolio Optimization, BNP Paribas Correlation, BNP Paribas Hype Analysis, BNP Paribas Volatility, BNP Paribas History as well as BNP Paribas Performance. Note that the BNP Paribas Long information on this page should be used as a complementary analysis to other BNP Paribas' statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try Sync Your Broker module to sync your existing holdings, watchlists, positions or portfolios from thousands of online brokerage services, banks, investment account aggregators and robo-advisors..

Other Tools for 0P00005X1I Fund

When running BNP Paribas Long price analysis, check to measure BNP Paribas' market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy BNP Paribas is operating at the current time. Most of BNP Paribas' value examination focuses on studying past and present price action to predict the probability of BNP Paribas' future price movements. You can analyze the entity against its peers and financial market as a whole to determine factors that move BNP Paribas' price. Additionally, you may evaluate how the addition of BNP Paribas to your portfolios can decrease your overall portfolio volatility.
Portfolio Suggestion
Get suggestions outside of your existing asset allocation including your own model portfolios
Go
Cryptocurrency Center
Build and monitor diversified portfolio of extremely risky digital assets and cryptocurrency
Go
Equity Search
Search for activelly traded equities including funds and ETFs from over 30 global markets
Go
Volatility Analysis
Get historical volatility and risk analysis based on latest market data
Go
Shere Portfolio
Track or share privately all of your investments from the convenience of any device
Go
Portfolio Comparator
Compare the composition, asset allocations and performance of any two portfolios in your account
Go
Focused Opportunities
Build portfolios using our predefined set of ideas and optimize them against your investing preferences
Go
Content Syndication
Quickly integrate customizable finance content to your own investment portal
Go
Equity Valuation
Check real value of public entities based on technical and fundamental data
Go
My Watchlist Analysis
Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like
Go
Portfolio Volatility
Check portfolio volatility and analyze historical return density to properly model market risk
Go