**Outlook:**PCSB Financial Corporation Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 04 Jan 2023**for (n+1 year)

**Methodology :**Modular Neural Network (Market Volatility Analysis)

## Abstract

PCSB Financial Corporation Common Stock prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Lasso Regression^{1,2,3,4}and it is concluded that the PCSB stock is predictable in the short/long term.

**According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy**

## Key Points

- How do predictive algorithms actually work?
- What are main components of Markov decision process?
- Which neural network is best for prediction?

## PCSB Target Price Prediction Modeling Methodology

We consider PCSB Financial Corporation Common Stock Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of PCSB 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}

F(Lasso Regression)

^{5,6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market Volatility Analysis)) X S(n):→ (n+1 year) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of PCSB stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

For further technical information as per how our model work we invite you to visit the article below:

How do AC Investment Research machine learning (predictive) algorithms actually work?

## PCSB Stock Forecast (Buy or Sell) for (n+1 year)

**Sample Set:**Neural Network

**Stock/Index:**PCSB PCSB Financial Corporation Common Stock

**Time series to forecast n: 04 Jan 2023**for (n+1 year)

**According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy**

**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%**

## IFRS Reconciliation Adjustments for PCSB Financial Corporation Common Stock

- Annual Improvements to IFRSs 2010–2012 Cycle, issued in December 2013, amended paragraphs 4.2.1 and 5.7.5 as a consequential amendment derived from the amendment to IFRS 3. An entity shall apply that amendment prospectively to business combinations to which the amendment to IFRS 3 applies.
- A contractually specified inflation risk component of the cash flows of a recognised inflation-linked bond (assuming that there is no requirement to account for an embedded derivative separately) is separately identifiable and reliably measurable, as long as other cash flows of the instrument are not affected by the inflation risk component.
- In some circumstances, the renegotiation or modification of the contractual cash flows of a financial asset can lead to the derecognition of the existing financial asset in accordance with this Standard. When the modification of a financial asset results in the derecognition of the existing financial asset and the subsequent recognition of the modified financial asset, the modified asset is considered a 'new' financial asset for the purposes of this Standard.
- At the date of initial application, an entity shall use reasonable and supportable information that is available without undue cost or effort to determine the credit risk at the date that a financial instrument was initially recognised (or for loan commitments and financial guarantee contracts at the date that the entity became a party to the irrevocable commitment in accordance with paragraph 5.5.6) and compare that to the credit risk at the date of initial application of this Standard.

*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.

## Conclusions

PCSB Financial Corporation Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. PCSB Financial Corporation Common Stock prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Lasso Regression^{1,2,3,4} and it is concluded that the PCSB stock is predictable in the short/long term. ** According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy**

### PCSB PCSB Financial Corporation Common Stock Financial Analysis*

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | Ba1 | Ba1 |

Income Statement | B3 | Baa2 |

Balance Sheet | Baa2 | Caa2 |

Leverage Ratios | C | Baa2 |

Cash Flow | B3 | Ba1 |

Rates of Return and Profitability | Baa2 | 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?

### Prediction Confidence Score

## References

- Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40
- Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
- Mnih A, Hinton GE. 2007. Three new graphical models for statistical language modelling. In International Conference on Machine Learning, pp. 641–48. La Jolla, CA: Int. Mach. Learn. Soc.
- M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
- Thompson WR. 1933. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25:285–94
- P. Artzner, F. Delbaen, J. Eber, and D. Heath. Coherent measures of risk. Journal of Mathematical Finance, 9(3):203–228, 1999
- R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998

## Frequently Asked Questions

Q: What is the prediction methodology for PCSB stock?A: PCSB stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Lasso Regression

Q: Is PCSB stock a buy or sell?

A: The dominant strategy among neural network is to Buy PCSB Stock.

Q: Is PCSB Financial Corporation Common Stock stock a good investment?

A: The consensus rating for PCSB Financial Corporation Common Stock is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of PCSB stock?

A: The consensus rating for PCSB is Buy.

Q: What is the prediction period for PCSB stock?

A: The prediction period for PCSB is (n+1 year)