## Abstract

**Outlook:**AT&T Inc. 5.350% Global Notes due 2066 assigned short-term B1 & long-term Ba3 forecasted stock rating.

**Signal:**Sell

**Time series to forecast n: 05 Dec 2022**for (n+3 month)

Predictions on stock market prices are a great challenge due to the fact that it is an immensely complex, chaotic and dynamic environment. There are many studies from various areas aiming to take on that challenge and Machine Learning approaches have been the focus of many of them. There are many examples of Machine Learning algorithms been able to reach satisfactory results when doing that type of prediction. This article studies the usage of LSTM networks on that scenario, to predict future trends of stock prices based on the price history, alongside with technical analysis indicators.(Porshnev, A., Redkin, I. and Shevchenko, A., 2013, December. Machine learning in prediction of stock market indicators based on historical data and data from twitter sentiment analysis. In 2013 IEEE 13th International Conference on Data Mining Workshops (pp. 440-444). IEEE.)** We evaluate AT&T Inc. 5.350% Global Notes due 2066 prediction models with Modular Neural Network (News Feed Sentiment Analysis) and ElasticNet Regression ^{1,2,3,4} and conclude that the TBB stock is predictable in the short/long term. **

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell TBB stock.**

## Key Points

- How can neural networks improve predictions?
- Market Outlook
- Short/Long Term Stocks

## TBB Target Price Prediction Modeling Methodology

We consider AT&T Inc. 5.350% Global Notes due 2066 Decision Process with Modular Neural Network (News Feed Sentiment Analysis) where A is the set of discrete actions of TBB 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(ElasticNet 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 (News Feed Sentiment Analysis)) X S(n):→ (n+3 month) $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of TBB 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?

## TBB Stock Forecast (Buy or Sell) for (n+3 month)

**Sample Set:**Neural Network

**Stock/Index:**TBB AT&T Inc. 5.350% Global Notes due 2066

**Time series to forecast n: 05 Dec 2022**for (n+3 month)

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell TBB stock.**

**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 (Yellow to Green): *Technical Analysis%**

## Adjusted IFRS* Prediction Methods for AT&T Inc. 5.350% Global Notes due 2066

- If an entity measures a hybrid contract at fair value in accordance with paragraphs 4.1.2A, 4.1.4 or 4.1.5 but the fair value of the hybrid contract had not been measured in comparative reporting periods, the fair value of the hybrid contract in the comparative reporting periods shall be the sum of the fair values of the components (ie the non-derivative host and the embedded derivative) at the end of each comparative reporting period if the entity restates prior periods (see paragraph 7.2.15).
- The methods used to determine whether credit risk has increased significantly on a financial instrument since initial recognition should consider the characteristics of the financial instrument (or group of financial instruments) and the default patterns in the past for comparable financial instruments. Despite the requirement in paragraph 5.5.9, for financial instruments for which default patterns are not concentrated at a specific point during the expected life of the financial instrument, changes in the risk of a default occurring over the next 12 months may be a reasonable approximation of the changes in the lifetime risk of a default occurring. In such cases, an entity may use changes in the risk of a default occurring over the next 12 months to determine whether credit risk has increased significantly since initial recognition, unless circumstances indicate that a lifetime assessment is necessary
- 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.
- An entity can also designate only changes in the cash flows or fair value of a hedged item above or below a specified price or other variable (a 'one-sided risk'). The intrinsic value of a purchased option hedging instrument (assuming that it has the same principal terms as the designated risk), but not its time value, reflects a one-sided risk in a hedged item. For example, an entity can designate the variability of future cash flow outcomes resulting from a price increase of a forecast commodity purchase. In such a situation, the entity designates only cash flow losses that result from an increase in the price above the specified level. The hedged risk does not include the time value of a purchased option, because the time value is not a component of the forecast transaction that affects profit or loss.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

## Conclusions

AT&T Inc. 5.350% Global Notes due 2066 assigned short-term B1 & long-term Ba3 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) with ElasticNet Regression ^{1,2,3,4} and conclude that the TBB stock is predictable in the short/long term.**

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell TBB stock.**

### Financial State Forecast for TBB AT&T Inc. 5.350% Global Notes due 2066 Options & Futures

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

Outlook* | B1 | Ba3 |

Operational Risk | 45 | 57 |

Market Risk | 43 | 60 |

Technical Analysis | 87 | 30 |

Fundamental Analysis | 59 | 88 |

Risk Unsystematic | 58 | 79 |

### Prediction Confidence Score

## References

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## Frequently Asked Questions

Q: What is the prediction methodology for TBB stock?A: TBB stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and ElasticNet Regression

Q: Is TBB stock a buy or sell?

A: The dominant strategy among neural network is to Sell TBB Stock.

Q: Is AT&T Inc. 5.350% Global Notes due 2066 stock a good investment?

A: The consensus rating for AT&T Inc. 5.350% Global Notes due 2066 is Sell and assigned short-term B1 & long-term Ba3 forecasted stock rating.

Q: What is the consensus rating of TBB stock?

A: The consensus rating for TBB is Sell.

Q: What is the prediction period for TBB stock?

A: The prediction period for TBB is (n+3 month)