Outlook: Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 07 Feb 2023 for (n+6 month)
Methodology : Inductive Learning (ML)

## Abstract

Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares prediction model is evaluated with Inductive Learning (ML) and Lasso Regression1,2,3,4 and it is concluded that the RENN stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

## Key Points

1. Trust metric by Neural Network
2. What is the use of Markov decision process?
3. Can we predict stock market using machine learning?

## RENN Target Price Prediction Modeling Methodology

We consider Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares Decision Process with Inductive Learning (ML) where A is the set of discrete actions of RENN 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Inductive Learning (ML)) X S(n):→ (n+6 month) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of RENN 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?

## RENN Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: RENN Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares
Time series to forecast n: 07 Feb 2023 for (n+6 month)

According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

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 Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares

1. As noted in paragraph B4.3.1, when an entity becomes a party to a hybrid contract with a host that is not an asset within the scope of this Standard and with one or more embedded derivatives, paragraph 4.3.3 requires the entity to identify any such embedded derivative, assess whether it is required to be separated from the host contract and, for those that are required to be separated, measure the derivatives at fair value at initial recognition and subsequently. These requirements can be more complex, or result in less reliable measures, than measuring the entire instrument at fair value through profit or loss. For that reason this Standard permits the entire hybrid contract to be designated as at fair value through profit or loss.
2. An entity that first applies IFRS 17 as amended in June 2020 at the same time it first applies this Standard shall apply paragraphs 7.2.1–7.2.28 instead of paragraphs 7.2.38–7.2.42.
3. Paragraph 5.5.4 requires that lifetime expected credit losses are recognised on all financial instruments for which there has been significant increases in credit risk since initial recognition. In order to meet this objective, if an entity is not able to group financial instruments for which the credit risk is considered to have increased significantly since initial recognition based on shared credit risk characteristics, the entity should recognise lifetime expected credit losses on a portion of the financial assets for which credit risk is deemed to have increased significantly. The aggregation of financial instruments to assess whether there are changes in credit risk on a collective basis may change over time as new information becomes available on groups of, or individual, financial instruments.
4. Compared to a business model whose objective is to hold financial assets to collect contractual cash flows, this business model will typically involve greater frequency and value of sales. This is because selling financial assets is integral to achieving the business model's objective instead of being only incidental to it. However, there is no threshold for the frequency or value of sales that must occur in this business model because both collecting contractual cash flows and selling financial assets are integral to achieving its objective.

*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

Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares is assigned short-term Ba1 & long-term Ba1 estimated rating. Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares prediction model is evaluated with Inductive Learning (ML) and Lasso Regression1,2,3,4 and it is concluded that the RENN stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

### RENN Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2C
Balance SheetBaa2Baa2
Leverage RatiosCCaa2
Cash FlowB3B2
Rates of Return and ProfitabilityCCaa2

*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: 72 out of 100 with 804 signals.

## References

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2. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
3. Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
4. M. Benaim, J. Hofbauer, and S. Sorin. Stochastic approximations and differential inclusions, Part II: Appli- cations. Mathematics of Operations Research, 31(4):673–695, 2006
5. Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22
6. Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
7. K. Tumer and D. Wolpert. A survey of collectives. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pages 1–42. Springer, 2004.
Frequently Asked QuestionsQ: What is the prediction methodology for RENN stock?
A: RENN stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Lasso Regression
Q: Is RENN stock a buy or sell?
A: The dominant strategy among neural network is to Hold RENN Stock.
Q: Is Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares stock a good investment?
A: The consensus rating for Renren Inc. American Depositary Shares each representing fifteen Class A ordinary shares is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of RENN stock?
A: The consensus rating for RENN is Hold.
Q: What is the prediction period for RENN stock?
A: The prediction period for RENN is (n+6 month)

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