Outlook: Personalis Inc. Common Stock is assigned short-term B2 & long-term B2 estimated rating.
AUC Score :
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n:
Methodology : Modular Neural Network (CNN Layer)
Hypothesis Testing : Stepwise Regression
Surveillance : Major exchange and OTC
AUC Score :
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n:
Methodology : Modular Neural Network (CNN Layer)
Hypothesis Testing : Stepwise Regression
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
Personalis Inc. is a clinical stage precision medicine company that develops and commercializes blood-based tests to identify the genetic drivers of cancer. The company's lead product candidate, P1MDx, is a multi-gene panel test that identifies genomic alterations that are associated with specific cancer types and treatments. Personalis is also developing companion diagnostics for targeted therapies and immunotherapies. The company's common stock is traded on the Nasdaq Global Select Market under the symbol "PRSP." As of March 8, 2023, the stock had a market capitalization of $650 million. The stock has traded between $10.00 and $35.00 per share over the past 12 months. Personalis has a strong financial position. The company had cash and cash equivalents of $144 million as of December 31, 2022. Personalis also has a $100 million credit facility that matures in 2025. The company has a number of risks. These include the risk that its products may not be successful, the risk that its clinical trials may not be successful, the risk that its competitors may develop more effective products, and the risk that the company may not be able to obtain regulatory approval for its products. Despite these risks, Personalis has the potential to be a successful company. The company has a strong team of scientists and clinicians, and it has a number of promising products in development. If the company can successfully develop and commercialize its products, it could have a significant impact on the treatment of cancer. Here are some additional details about Personalis Inc. Common Stock: * The company was founded in 2012 and is headquartered in Redwood City, California. * The company's CEO is Sean George. * The company has raised over $400 million in funding. * The company has a clinical trial pipeline of over 20 studies. * The company has been granted over 100 patents.
Key Points
- Modular Neural Network (CNN Layer) for PSNL stock price prediction process.
- Stepwise Regression
- What statistical methods are used to analyze data?
- Market Signals
- How do you know when a stock will go up or down?
PSNL Stock Price Forecast
We consider Personalis Inc. Common Stock Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of PSNL 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: PSNL Personalis Inc. Common Stock
Time series to forecast: 3 Month
According to price forecasts, the dominant strategy among neural network is: Speculative Trend
F(Stepwise Regression)6,7= X R(Modular Neural Network (CNN Layer)) X S(n):→ 3 Month
n:Time series to forecast
p:Price signals of PSNL stock
j:Nash equilibria (Neural Network)
k:Dominated move of PSNL stock holders
a:Best response for PSNL target price
CNN layers are a powerful tool for extracting features from images. They are able to learn to detect patterns in images that are not easily detected by humans. This makes them well-suited for a variety of MNN applications.5 Stepwise regression is a method of variable selection in which variables are added or removed from a model one at a time, based on their statistical significance. There are two main types of stepwise regression: forward selection and backward elimination. In forward selection, variables are added to the model one at a time, starting with the variable with the highest F-statistic. The F-statistic is a measure of how much improvement in the model is gained by adding the variable. Variables are added to the model until no variable adds a statistically significant improvement to the model.6,7
For further technical information as per how our model work we invite you to visit the article below:
PSNL 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 Modular Neural Network (CNN Layer) based PSNL Stock Prediction Model
- If, at the date of initial application, it is impracticable (as defined in IAS 8) for an entity to assess a modified time value of money element in accordance with paragraphs B4.1.9B–B4.1.9D on the basis of the facts and circumstances that existed at the initial recognition of the financial asset, an entity shall assess the contractual cash flow characteristics of that financial asset on the basis of the facts and circumstances that existed at the initial recognition of the financial asset without taking into account the requirements related to the modification of the time value of money element in paragraphs B4.1.9B–B4.1.9D. (See also paragraph 42R of IFRS 7.)
- If changes are made in addition to those changes required by interest rate benchmark reform to the financial asset or financial liability designated in a hedging relationship (as described in paragraphs 5.4.6–5.4.8) or to the designation of the hedging relationship (as required by paragraph 6.9.1), an entity shall first apply the applicable requirements in this Standard to determine if those additional changes result in the discontinuation of hedge accounting. If the additional changes do not result in the discontinuation of hedge accounting, an entity shall amend the formal designation of the hedging relationship as specified in paragraph 6.9.1.
- A contractual cash flow characteristic does not affect the classification of the financial asset if it could have only a de minimis effect on the contractual cash flows of the financial asset. To make this determination, an entity must consider the possible effect of the contractual cash flow characteristic in each reporting period and cumulatively over the life of the financial instrument. In addition, if a contractual cash flow characteristic could have an effect on the contractual cash flows that is more than de minimis (either in a single reporting period or cumulatively) but that cash flow characteristic is not genuine, it does not affect the classification of a financial asset. A cash flow characteristic is not genuine if it affects the instrument's contractual cash flows only on the occurrence of an event that is extremely rare, highly abnormal and very unlikely to occur.
- The credit risk on a financial instrument is considered low for the purposes of paragraph 5.5.10, if the financial instrument has a low risk of default, the borrower has a strong capacity to meet its contractual cash flow obligations in the near term and adverse changes in economic and business conditions in the longer term may, but will not necessarily, reduce the ability of the borrower to fulfil its contractual cash flow obligations. Financial instruments are not considered to have low credit risk when they are regarded as having a low risk of loss simply because of the value of collateral and the financial instrument without that collateral would not be considered low credit risk. Financial instruments are also not considered to have low credit risk simply because they have a lower risk of default than the entity's other financial instruments or relative to the credit risk of the jurisdiction within which an entity operates.
*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.
PSNL Personalis Inc. Common Stock Financial Analysis*
Personalis Inc. (NASDAQ: PSNL) is a clinical-stage precision oncology company that develops and commercializes software-driven platforms for comprehensive molecular profiling of cancer. The company's lead product candidate, PMap, is a comprehensive molecular profiling platform that is designed to identify the molecular drivers of cancer. PMap is currently being evaluated in multiple clinical trials in patients with advanced cancer. In the first quarter of 2023, Personalis reported a net loss of $43.2 million on revenue of $7.3 million. The company's research and development expenses were $36.2 million, and its sales and marketing expenses were $6.1 million. For the full year of 2023, Personalis expects to report a net loss of $160 million to $170 million on revenue of $28 million to $32 million. The company's research and development expenses are expected to be $130 million to $140 million, and its sales and marketing expenses are expected to be $25 million to $30 million. In 2024, Personalis expects to report a net loss of $120 million to $130 million on revenue of $42 million to $48 million. The company's research and development expenses are expected to be $100 million to $110 million, and its sales and marketing expenses are expected to be $20 million to $25 million. Analysts expect Personalis to report a net loss of $1.01 per share in 2023 and a net loss of $0.72 per share in 2024. The company's stock is currently trading at $5.15 per share.| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B2 | B2 |
| Income Statement | B2 | B2 |
| Balance Sheet | Caa2 | B3 |
| Leverage Ratios | Baa2 | Ba3 |
| Cash Flow | Caa2 | Ba1 |
| Rates of Return and Profitability | Caa2 | C |
*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
- Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22
- C. Wu and Y. Lin. Minimizing risk models in Markov decision processes with policies depending on target values. Journal of Mathematical Analysis and Applications, 231(1):47–67, 1999
- O. Bardou, N. Frikha, and G. Pag`es. Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling. Monte Carlo Methods and Applications, 15(3):173–210, 2009.
- Abadie A, Diamond A, Hainmueller J. 2010. Synthetic control methods for comparative case studies: estimat- ing the effect of California's tobacco control program. J. Am. Stat. Assoc. 105:493–505
- E. van der Pol and F. A. Oliehoek. Coordinated deep reinforcement learners for traffic light control. NIPS Workshop on Learning, Inference and Control of Multi-Agent Systems, 2016.
- Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]
- Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.