GS^A Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A

Outlook: Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 25 Mar 2023 for (n+16 weeks)
Methodology : Statistical Inference (ML)

Abstract

Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A prediction model is evaluated with Statistical Inference (ML) and Chi-Square^1,2,3,4 and it is concluded that the GS^A stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

Key Points

1. Probability Distribution
2. Can machine learning predict?
3. Is Target price a good indicator?

GS^A Target Price Prediction Modeling Methodology

We consider Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A Decision Process with Statistical Inference (ML) where A is the set of discrete actions of GS^A 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(Chi-Square)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Statistical Inference (ML)) X S(n):→ (n+16 weeks) $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of GS^A 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?

GS^A Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: GS^A Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A
Time series to forecast n: 25 Mar 2023 for (n+16 weeks)

According to price forecasts for (n+16 weeks) 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 Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A

1. If there is a hedging relationship between a non-derivative monetary asset and a non-derivative monetary liability, changes in the foreign currency component of those financial instruments are presented in profit or loss.
2. An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods only if it is possible to do so without the use of hindsight. If an entity restates prior periods, the restated financial statements must reflect all the requirements in this Standard for the affected financial instruments. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.
3. For the purposes of measuring expected credit losses, the estimate of expected cash shortfalls shall reflect the cash flows expected from collateral and other credit enhancements that are part of the contractual terms and are not recognised separately by the entity. The estimate of expected cash shortfalls on a collateralised financial instrument reflects the amount and timing of cash flows that are expected from foreclosure on the collateral less the costs of obtaining and selling the collateral, irrespective of whether foreclosure is probable (ie the estimate of expected cash flows considers the probability of a foreclosure and the cash flows that would result from it). Consequently, any cash flows that are expected from the realisation of the collateral beyond the contractual maturity of the contract should be included in this analysis. Any collateral obtained as a result of foreclosure is not recognised as an asset that is separate from the collateralised financial instrument unless it meets the relevant recognition criteria for an asset in this or other Standards.
4. Fluctuation around a constant hedge ratio (and hence the related hedge ineffectiveness) cannot be reduced by adjusting the hedge ratio in response to each particular outcome. Hence, in such circumstances, the change in the extent of offset is a matter of measuring and recognising hedge ineffectiveness but does not require rebalancing.

*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

Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A is assigned short-term Ba1 & long-term Ba1 estimated rating. Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A prediction model is evaluated with Statistical Inference (ML) and Chi-Square^1,2,3,4 and it is concluded that the GS^A stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

GS^A Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B2	B3
Balance Sheet	C	Baa2
Leverage Ratios	B2	Baa2
Cash Flow	Caa2	Caa2
Rates of Return and Profitability	Baa2	B1

*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

Trust metric by Neural Network: 93 out of 100 with 814 signals.

References

1. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
2. Krizhevsky A, Sutskever I, Hinton GE. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems, Vol. 25, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 1097–105. San Diego, CA: Neural Inf. Process. Syst. Found.
3. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
4. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68
5. Swaminathan A, Joachims T. 2015. Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. 16:1731–55
6. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
7. V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014

Frequently Asked Questions

Q: What is the prediction methodology for GS^A stock?
A: GS^A stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Chi-Square
Q: Is GS^A stock a buy or sell?
A: The dominant strategy among neural network is to Buy GS^A Stock.
Q: Is Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A stock a good investment?
A: The consensus rating for Goldman Sachs Group Inc. (The) Depositary Shares each representing 1/1000th Interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series A is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of GS^A stock?
A: The consensus rating for GS^A is Buy.
Q: What is the prediction period for GS^A stock?
A: The prediction period for GS^A is (n+16 weeks)

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