**Outlook:**Compass Digital Acquisition Corp. Unit assigned short-term B1 & long-term Ba2 forecasted stock rating.

**Dominant Strategy :**Sell

**Time series to forecast n: 06 Dec 2022**for (n+3 month)

**Methodology :**Deductive Inference (ML)

## Abstract

Financial markets are fascinating if you can predict them. Also, the traders acting on financial markets produce a vast amount of information to analyse the consequences of investing according to the current market trends. Stock Market prediction is the technique to determine whether stock value will go up or down as it plays an active role in the financial gain of nation's economic status.(Anand, C., 2021. Comparison of stock price prediction models using pre-trained neural networks. Journal of Ubiquitous Computing and Communication Technologies (UCCT), 3(02), pp.122-134.)** We evaluate Compass Digital Acquisition Corp. Unit prediction models with Deductive Inference (ML) and Linear Regression ^{1,2,3,4} and conclude that the CDAQU 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 CDAQU stock.**

## Key Points

- Market Risk
- What are main components of Markov decision process?
- How do predictive algorithms actually work?

## CDAQU Target Price Prediction Modeling Methodology

We consider Compass Digital Acquisition Corp. Unit Decision Process with Deductive Inference (ML) where A is the set of discrete actions of CDAQU 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(Linear 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(Deductive Inference (ML)) X S(n):→ (n+3 month) $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of CDAQU 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?

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

**Sample Set:**Neural Network

**Stock/Index:**CDAQU Compass Digital Acquisition Corp. Unit

**Time series to forecast n: 06 Dec 2022**for (n+3 month)

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell CDAQU 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 Compass Digital Acquisition Corp. Unit

- When measuring the fair values of the part that continues to be recognised and the part that is derecognised for the purposes of applying paragraph 3.2.13, an entity applies the fair value measurement requirements in IFRS 13 Fair Value Measurement in addition to paragraph 3.2.14.
- Paragraphs 6.9.7–6.9.13 provide exceptions to the requirements specified in those paragraphs only. An entity shall apply all other hedge accounting requirements in this Standard, including the qualifying criteria in paragraph 6.4.1, to hedging relationships that were directly affected by interest rate benchmark reform.
- If any instrument in the pool does not meet the conditions in either paragraph B4.1.23 or paragraph B4.1.24, the condition in paragraph B4.1.21(b) is not met. In performing this assessment, a detailed instrument-byinstrument analysis of the pool may not be necessary. However, an entity must use judgement and perform sufficient analysis to determine whether the instruments in the pool meet the conditions in paragraphs B4.1.23–B4.1.24. (See also paragraph B4.1.18 for guidance on contractual cash flow characteristics that have only a de minimis effect.)
- Adjusting the hedge ratio by decreasing the volume of the hedged item does not affect how the changes in the fair value of the hedging instrument are measured. The measurement of the changes in the value of the hedged item related to the volume that continues to be designated also remains unaffected. However, from the date of rebalancing, the volume by which the hedged item was decreased is no longer part of the hedging relationship. For example, if an entity originally hedged a volume of 100 tonnes of a commodity at a forward price of CU80 and reduces that volume by 10 tonnes on rebalancing, the hedged item after rebalancing would be 90 tonnes hedged at CU80. The 10 tonnes of the hedged item that are no longer part of the hedging relationship would be accounted for in accordance with the requirements for the discontinuation of hedge accounting (see paragraphs 6.5.6–6.5.7 and B6.5.22–B6.5.28).

*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

Compass Digital Acquisition Corp. Unit assigned short-term B1 & long-term Ba2 forecasted stock rating.** We evaluate the prediction models Deductive Inference (ML) with Linear Regression ^{1,2,3,4} and conclude that the CDAQU 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 CDAQU stock.**

### Financial State Forecast for CDAQU Compass Digital Acquisition Corp. Unit Options & Futures

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

Outlook* | B1 | Ba2 |

Operational Risk | 81 | 72 |

Market Risk | 78 | 62 |

Technical Analysis | 36 | 90 |

Fundamental Analysis | 61 | 63 |

Risk Unsystematic | 35 | 58 |

### Prediction Confidence Score

## References

- B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765
- 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
- A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
- D. Bertsekas. Nonlinear programming. Athena Scientific, 1999.
- Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
- Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
- Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.

## Frequently Asked Questions

Q: What is the prediction methodology for CDAQU stock?A: CDAQU stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Linear Regression

Q: Is CDAQU stock a buy or sell?

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

Q: Is Compass Digital Acquisition Corp. Unit stock a good investment?

A: The consensus rating for Compass Digital Acquisition Corp. Unit is Sell and assigned short-term B1 & long-term Ba2 forecasted stock rating.

Q: What is the consensus rating of CDAQU stock?

A: The consensus rating for CDAQU is Sell.

Q: What is the prediction period for CDAQU stock?

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

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