**Outlook:**Nauticus Robotics Inc. Warrant assigned short-term B1 & long-term B3 forecasted stock rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 15 Dec 2022**for (n+8 weeks)

**Methodology :**Transfer Learning (ML)

## Abstract

Investors raise profit from stock market by maximising gains and minimising loses. The profit is difficult to raise because of the volatile nature of stock market prices. Predictive modelling allows investors to make informed decisions. (Ampomah, E.K., Nyame, G., Qin, Z., Addo, P.C., Gyamfi, E.O. and Gyan, M., 2021. Stock market prediction with gaussian naïve bayes machine learning algorithm. Informatica, 45(2).)** We evaluate Nauticus Robotics Inc. Warrant prediction models with Transfer Learning (ML) and Linear Regression ^{1,2,3,4} and conclude that the KITTW stock is predictable in the short/long term. **

**According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Buy**

## Key Points

- Market Risk
- Can statistics predict the future?
- Short/Long Term Stocks

## KITTW Target Price Prediction Modeling Methodology

We consider Nauticus Robotics Inc. Warrant Decision Process with Transfer Learning (ML) where A is the set of discrete actions of KITTW 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(Transfer Learning (ML)) X S(n):→ (n+8 weeks) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of KITTW 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?

## KITTW Stock Forecast (Buy or Sell) for (n+8 weeks)

**Sample Set:**Neural Network

**Stock/Index:**KITTW Nauticus Robotics Inc. Warrant

**Time series to forecast n: 15 Dec 2022**for (n+8 weeks)

**According to price forecasts for (n+8 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%**

## Adjusted IFRS* Prediction Methods for Nauticus Robotics Inc. Warrant

- For a financial guarantee contract, the entity is required to make payments only in the event of a default by the debtor in accordance with the terms of the instrument that is guaranteed. Accordingly, cash shortfalls are the expected payments to reimburse the holder for a credit loss that it incurs less any amounts that the entity expects to receive from the holder, the debtor or any other party. If the asset is fully guaranteed, the estimation of cash shortfalls for a financial guarantee contract would be consistent with the estimations of cash shortfalls for the asset subject to the guarantee
- A single hedging instrument may be designated as a hedging instrument of more than one type of risk, provided that there is a specific designation of the hedging instrument and of the different risk positions as hedged items. Those hedged items can be in different hedging relationships.
- The underlying pool must contain one or more instruments that have contractual cash flows that are solely payments of principal and interest on the principal amount outstanding
- When designating a group of items as the hedged item, or a combination of financial instruments as the hedging instrument, an entity shall prospectively cease applying paragraphs 6.8.4–6.8.6 to an individual item or financial instrument in accordance with paragraphs 6.8.9, 6.8.10, or 6.8.11, as relevant, when the uncertainty arising from interest rate benchmark reform is no longer present with respect to the hedged risk and/or the timing and the amount of the interest rate benchmark-based cash flows of that item or financial instrument.

*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

Nauticus Robotics Inc. Warrant assigned short-term B1 & long-term B3 forecasted stock rating.** We evaluate the prediction models Transfer Learning (ML) with Linear Regression ^{1,2,3,4} and conclude that the KITTW stock is predictable in the short/long term.**

**According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Buy**

### Financial State Forecast for KITTW Nauticus Robotics Inc. Warrant Options & Futures

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

Outlook* | B1 | B3 |

Operational Risk | 89 | 36 |

Market Risk | 40 | 79 |

Technical Analysis | 39 | 34 |

Fundamental Analysis | 77 | 34 |

Risk Unsystematic | 64 | 58 |

### Prediction Confidence Score

## References

- Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
- Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Is DOW Stock Expected to Go Up?(Stock Forecast). AC Investment Research Journal, 101(3).
- Friedman JH. 2002. Stochastic gradient boosting. Comput. Stat. Data Anal. 38:367–78
- G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011
- Mnih A, Hinton GE. 2007. Three new graphical models for statistical language modelling. In International Conference on Machine Learning, pp. 641–48. La Jolla, CA: Int. Mach. Learn. Soc.
- Hoerl AE, Kennard RW. 1970. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12:55–67
- Sutton RS, Barto AG. 1998. Reinforcement Learning: An Introduction. Cambridge, MA: MIT Press

## Frequently Asked Questions

Q: What is the prediction methodology for KITTW stock?A: KITTW stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Linear Regression

Q: Is KITTW stock a buy or sell?

A: The dominant strategy among neural network is to Buy KITTW Stock.

Q: Is Nauticus Robotics Inc. Warrant stock a good investment?

A: The consensus rating for Nauticus Robotics Inc. Warrant is Buy and assigned short-term B1 & long-term B3 forecasted stock rating.

Q: What is the consensus rating of KITTW stock?

A: The consensus rating for KITTW is Buy.

Q: What is the prediction period for KITTW stock?

A: The prediction period for KITTW is (n+8 weeks)

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