**Outlook:**TRIPLE POINT INCOME VCT PLC assigned short-term Ba3 & long-term B1 forecasted stock rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 09 Dec 2022**for (n+16 weeks)

**Methodology :**Active Learning (ML)

## Abstract

Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks' historical data. Most of these existing approaches have focused on short term prediction using stocks' historical price and technical indicators.(Nelson, D.M., Pereira, A.C. and De Oliveira, R.A., 2017, May. Stock market's price movement prediction with LSTM neural networks. In 2017 International joint conference on neural networks (IJCNN) (pp. 1419-1426). Ieee.)** We evaluate TRIPLE POINT INCOME VCT PLC prediction models with Active Learning (ML) and Logistic Regression ^{1,2,3,4} and conclude that the LON:TPVD stock is predictable in the short/long term. **

**According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy**

## Key Points

- Short/Long Term Stocks
- How do you decide buy or sell a stock?
- Is now good time to invest?

## LON:TPVD Target Price Prediction Modeling Methodology

We consider TRIPLE POINT INCOME VCT PLC Decision Process with Active Learning (ML) where A is the set of discrete actions of LON:TPVD 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(Logistic 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(Active Learning (ML)) X S(n):→ (n+16 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 LON:TPVD 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?

## LON:TPVD Stock Forecast (Buy or Sell) for (n+16 weeks)

**Sample Set:**Neural Network

**Stock/Index:**LON:TPVD TRIPLE POINT INCOME VCT PLC

**Time series to forecast n: 09 Dec 2022**for (n+16 weeks)

**According to price forecasts for (n+16 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 TRIPLE POINT INCOME VCT PLC

- For the purposes of the transition provisions in paragraphs 7.2.1, 7.2.3–7.2.28 and 7.3.2, the date of initial application is the date when an entity first applies those requirements of this Standard and must be the beginning of a reporting period after the issue of this Standard. Depending on the entity's chosen approach to applying IFRS 9, the transition can involve one or more than one date of initial application for different requirements.
- Conversely, if changes in the extent of offset indicate that the fluctuation is around a hedge ratio that is different from the hedge ratio that is currently used for that hedging relationship, or that there is a trend leading away from that hedge ratio, hedge ineffectiveness can be reduced by adjusting the hedge ratio, whereas retaining the hedge ratio would increasingly produce hedge ineffectiveness. Hence, in such circumstances, an entity must evaluate whether the hedging relationship reflects an imbalance between the weightings of the hedged item and the hedging instrument that would create hedge ineffectiveness (irrespective of whether recognised or not) that could result in an accounting outcome that would be inconsistent with the purpose of hedge accounting. If the hedge ratio is adjusted, it also affects the measurement and recognition of hedge ineffectiveness because, on rebalancing, the hedge ineffectiveness of the hedging relationship must be determined and recognised immediately before adjusting the hedging relationship in accordance with paragraph B6.5.8.
- If a variable-rate financial liability bears interest of (for example) three-month LIBOR minus 20 basis points (with a floor at zero basis points), an entity can designate as the hedged item the change in the cash flows of that entire liability (ie three-month LIBOR minus 20 basis points—including the floor) that is attributable to changes in LIBOR. Hence, as long as the three-month LIBOR forward curve for the remaining life of that liability does not fall below 20 basis points, the hedged item has the same cash flow variability as a liability that bears interest at three-month LIBOR with a zero or positive spread. However, if the three-month LIBOR forward curve for the remaining life of that liability (or a part of it) falls below 20 basis points, the hedged item has a lower cash flow variability than a liability that bears interest at threemonth LIBOR with a zero or positive spread.
- The rebuttable presumption in paragraph 5.5.11 is not an absolute indicator that lifetime expected credit losses should be recognised, but is presumed to be the latest point at which lifetime expected credit losses should be recognised even when using forward-looking information (including macroeconomic factors on a portfolio level).

*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

TRIPLE POINT INCOME VCT PLC assigned short-term Ba3 & long-term B1 forecasted stock rating.** We evaluate the prediction models Active Learning (ML) with Logistic Regression ^{1,2,3,4} and conclude that the LON:TPVD stock is predictable in the short/long term.**

**According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy**

### Financial State Forecast for LON:TPVD TRIPLE POINT INCOME VCT PLC Options & Futures

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

Outlook* | Ba3 | B1 |

Operational Risk | 76 | 67 |

Market Risk | 63 | 79 |

Technical Analysis | 51 | 36 |

Fundamental Analysis | 67 | 83 |

Risk Unsystematic | 71 | 38 |

### Prediction Confidence Score

## References

- Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
- Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
- Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
- uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
- Brailsford, T.J. R.W. Faff (1996), "An evaluation of volatility forecasting techniques," Journal of Banking Finance, 20, 419–438.
- Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
- R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000

## Frequently Asked Questions

Q: What is the prediction methodology for LON:TPVD stock?A: LON:TPVD stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Logistic Regression

Q: Is LON:TPVD stock a buy or sell?

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

Q: Is TRIPLE POINT INCOME VCT PLC stock a good investment?

A: The consensus rating for TRIPLE POINT INCOME VCT PLC is Buy and assigned short-term Ba3 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of LON:TPVD stock?

A: The consensus rating for LON:TPVD is Buy.

Q: What is the prediction period for LON:TPVD stock?

A: The prediction period for LON:TPVD is (n+16 weeks)

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