AUC Score :
Short-Term Revised1 :
Dominant Strategy : SellHold
Time series to forecast n:
Methodology : Statistical Inference (ML)
Hypothesis Testing : Factor
Surveillance : Major exchange and OTC
1The accuracy of the model is being monitored on a regular basis.(15-minute period)
2Time series is updated based on short-term trends.
Summary
Nanobiotix S.A. American Depositary Shares prediction model is evaluated with Statistical Inference (ML) and Factor1,2,3,4 and it is concluded that the NBTX stock is predictable in the short/long term. Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen.5 According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: SellHold
Key Points
- Statistical Inference (ML) for NBTX stock price prediction process.
- Factor
- Trust metric by Neural Network
- What are the most successful trading algorithms?
- Why do we need predictive models?
NBTX Stock Price Forecast
We consider Nanobiotix S.A. American Depositary Shares Decision Process with Statistical Inference (ML) where A is the set of discrete actions of NBTX stock holders, F is the set of discrete states, P : S × F × S → R is the transition probability distribution, R : S × F → R is the reaction function, and γ ∈ [0, 1] is a move factor for expectation.1,2,3,4
Sample Set: Neural Network
Stock/Index: NBTX Nanobiotix S.A. American Depositary Shares
Time series to forecast: 16 Weeks
According to price forecasts, the dominant strategy among neural network is: SellHold
n:Time series to forecast
p:Price signals of NBTX stock
j:Nash equilibria (Neural Network)
k:Dominated move of NBTX stock holders
a:Best response for NBTX target price
Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen.5 In statistics, a factor is a variable that can influence the value of another variable. Factors can be categorical or continuous. Categorical factors have a limited number of possible values, such as gender (male or female) or blood type (A, B, AB, or O). Continuous factors can have an infinite number of possible values, such as height or weight. Factors can be used to explain the variation in a dependent variable. For example, a study might find that there is a relationship between gender and height. In this case, gender would be the independent variable, height would be the dependent variable, and the factor would be gender.6,7
For further technical information as per how our model work we invite you to visit the article below:
NBTX Stock Forecast (Buy or Sell) Strategic Interaction Table
Strategic Interaction Table Legend:
X axis: *Likelihood% (The higher the percentage value, the more likely the event will occur.)
Y axis: *Potential Impact% (The higher the percentage value, the more likely the price will deviate.)
Z axis (Grey to Black): *Technical Analysis%
Financial Data Adjustments for Statistical Inference (ML) based NBTX Stock Prediction Model
- Subject to the conditions in paragraphs 4.1.5 and 4.2.2, this Standard allows an entity to designate a financial asset, a financial liability, or a group of financial instruments (financial assets, financial liabilities or both) as at fair value through profit or loss provided that doing so results in more relevant information.
- Lifetime expected credit losses are not recognised on a financial instrument simply because it was considered to have low credit risk in the previous reporting period and is not considered to have low credit risk at the reporting date. In such a case, an entity shall determine whether there has been a significant increase in credit risk since initial recognition and thus whether lifetime expected credit losses are required to be recognised in accordance with paragraph 5.5.3.
- If there are changes in circumstances that affect hedge effectiveness, an entity may have to change the method for assessing whether a hedging relationship meets the hedge effectiveness requirements in order to ensure that the relevant characteristics of the hedging relationship, including the sources of hedge ineffectiveness, are still captured.
- A net position is eligible for hedge accounting only if an entity hedges on a net basis for risk management purposes. Whether an entity hedges in this way is a matter of fact (not merely of assertion or documentation). Hence, an entity cannot apply hedge accounting on a net basis solely to achieve a particular accounting outcome if that would not reflect its risk management approach. Net position hedging must form part of an established risk management strategy. Normally this would be approved by key management personnel as defined in IAS 24.
*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.
NBTX Nanobiotix S.A. American Depositary Shares Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B2 | B1 |
Income Statement | B2 | Baa2 |
Balance Sheet | Baa2 | Caa2 |
Leverage Ratios | Ba3 | B2 |
Cash Flow | C | Caa2 |
Rates of Return and Profitability | C | Baa2 |
*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?
References
- Ruiz FJ, Athey S, Blei DM. 2017. SHOPPER: a probabilistic model of consumer choice with substitutes and complements. arXiv:1711.03560 [stat.ML]
- Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
- S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
- Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
- Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
- Hartigan JA, Wong MA. 1979. Algorithm as 136: a k-means clustering algorithm. J. R. Stat. Soc. Ser. C 28:100–8
- J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017
Frequently Asked Questions
Q: Is NBTX stock expected to rise?A: NBTX stock prediction model is evaluated with Statistical Inference (ML) and Factor and it is concluded that dominant strategy for NBTX stock is SellHold
Q: Is NBTX stock a buy or sell?
A: The dominant strategy among neural network is to SellHold NBTX Stock.
Q: Is Nanobiotix S.A. American Depositary Shares stock a good investment?
A: The consensus rating for Nanobiotix S.A. American Depositary Shares is SellHold and is assigned short-term B2 & long-term B1 estimated rating.
Q: What is the consensus rating of NBTX stock?
A: The consensus rating for NBTX is SellHold.
Q: What is the forecast for NBTX stock?
A: NBTX target price forecast: SellHold