Outlook: Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 08 Mar 2023 for (n+1 year)
Methodology : Active Learning (ML)

## Abstract

Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares prediction model is evaluated with Active Learning (ML) and Sign Test1,2,3,4 and it is concluded that the TGH^B stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

## Key Points

1. What are the most successful trading algorithms?
2. What are the most successful trading algorithms?
3. Is now good time to invest?

## TGH^B Target Price Prediction Modeling Methodology

We consider Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares Decision Process with Active Learning (ML) where A is the set of discrete actions of TGH^B 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(Sign Test)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(Active Learning (ML)) X S(n):→ (n+1 year) $∑ i = 1 n s i$

n:Time series to forecast

p:Price signals of TGH^B 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?

## TGH^B Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: TGH^B Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares
Time series to forecast n: 08 Mar 2023 for (n+1 year)

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

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 Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares

1. The accounting for the forward element of forward contracts in accordance with paragraph 6.5.16 applies only to the extent that the forward element relates to the hedged item (aligned forward element). The forward element of a forward contract relates to the hedged item if the critical terms of the forward contract (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the forward contract and the hedged item are not fully aligned, an entity shall determine the aligned forward element, ie how much of the forward element included in the forward contract (actual forward element) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.16). An entity determines the aligned forward element using the valuation of the forward contract that would have critical terms that perfectly match the hedged item.
2. 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.
3. Rebalancing refers to the adjustments made to the designated quantities of the hedged item or the hedging instrument of an already existing hedging relationship for the purpose of maintaining a hedge ratio that complies with the hedge effectiveness requirements. Changes to designated quantities of a hedged item or of a hedging instrument for a different purpose do not constitute rebalancing for the purpose of this Standard
4. In some jurisdictions, the government or a regulatory authority sets interest rates. For example, such government regulation of interest rates may be part of a broad macroeconomic policy or it may be introduced to encourage entities to invest in a particular sector of the economy. In some of these cases, the objective of the time value of money element is not to provide consideration for only the passage of time. However, despite paragraphs B4.1.9A–B4.1.9D, a regulated interest rate shall be considered a proxy for the time value of money element for the purpose of applying the condition in paragraphs 4.1.2(b) and 4.1.2A(b) if that regulated interest rate provides consideration that is broadly consistent with the passage of time and does not provide exposure to risks or volatility in the contractual cash flows that are inconsistent with a basic lending arrangement.

*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

Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares prediction model is evaluated with Active Learning (ML) and Sign Test1,2,3,4 and it is concluded that the TGH^B stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

### TGH^B Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2C
Balance SheetCBa2
Leverage RatiosCaa2Baa2
Cash FlowBaa2Ba1
Rates of Return and ProfitabilityBaa2B1

*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: 73 out of 100 with 836 signals. ## References

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2. S. Bhatnagar and K. Lakshmanan. An online actor-critic algorithm with function approximation for con- strained Markov decision processes. Journal of Optimization Theory and Applications, 153(3):688–708, 2012.
3. Hastie T, Tibshirani R, Wainwright M. 2015. Statistical Learning with Sparsity: The Lasso and Generalizations. New York: CRC Press
4. Bengio Y, Ducharme R, Vincent P, Janvin C. 2003. A neural probabilistic language model. J. Mach. Learn. Res. 3:1137–55
5. Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
6. Candès EJ, Recht B. 2009. Exact matrix completion via convex optimization. Found. Comput. Math. 9:717
7. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
Frequently Asked QuestionsQ: What is the prediction methodology for TGH^B stock?
A: TGH^B stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Sign Test
Q: Is TGH^B stock a buy or sell?
A: The dominant strategy among neural network is to Sell TGH^B Stock.
Q: Is Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares stock a good investment?
A: The consensus rating for Textainer Group Holdings Limited Depositary Shares each representing a 1/1000th interest in a share of 6.250% Series B Cumulative Redeemable Perpetual Preference Shares is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of TGH^B stock?
A: The consensus rating for TGH^B is Sell.
Q: What is the prediction period for TGH^B stock?
A: The prediction period for TGH^B is (n+1 year)