**Outlook:**SLR Investment Corp. Common Stock assigned short-term Ba3 & long-term B1 forecasted stock rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 14 Dec 2022**for (n+8 weeks)

**Methodology :**Modular Neural Network (News Feed Sentiment Analysis)

## Abstract

This paper studies the possibilities of making prediction of stock market prices using historical data and machine learning algorithms.(Siew, H.L. and Nordin, M.J., 2012, September. Regression techniques for the prediction of stock price trend. In 2012 International Conference on Statistics in Science, Business and Engineering (ICSSBE) (pp. 1-5). IEEE.)** We evaluate SLR Investment Corp. Common Stock prediction models with Modular Neural Network (News Feed Sentiment Analysis) and Linear Regression ^{1,2,3,4} and conclude that the SLRC 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

- What are the most successful trading algorithms?
- Prediction Modeling
- What are the most successful trading algorithms?

## SLRC Target Price Prediction Modeling Methodology

We consider SLR Investment Corp. Common Stock Decision Process with Modular Neural Network (News Feed Sentiment Analysis) where A is the set of discrete actions of SLRC 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(Modular Neural Network (News Feed Sentiment Analysis)) X S(n):→ (n+8 weeks) $\overrightarrow{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of SLRC 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?

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

**Sample Set:**Neural Network

**Stock/Index:**SLRC SLR Investment Corp. Common Stock

**Time series to forecast n: 14 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 SLR Investment Corp. Common Stock

- An entity's estimate of expected credit losses on loan commitments shall be consistent with its expectations of drawdowns on that loan commitment, ie it shall consider the expected portion of the loan commitment that will be drawn down within 12 months of the reporting date when estimating 12-month expected credit losses, and the expected portion of the loan commitment that will be drawn down over the expected life of the loan commitment when estimating lifetime expected credit losses.
- For floating-rate financial assets and floating-rate financial liabilities, periodic re-estimation of cash flows to reflect the movements in the market rates of interest alters the effective interest rate. If a floating-rate financial asset or a floating-rate financial liability is recognised initially at an amount equal to the principal receivable or payable on maturity, re-estimating the future interest payments normally has no significant effect on the carrying amount of the asset or the liability.
- Expected credit losses shall be discounted to the reporting date, not to the expected default or some other date, using the effective interest rate determined at initial recognition or an approximation thereof. If a financial instrument has a variable interest rate, expected credit losses shall be discounted using the current effective interest rate determined in accordance with paragraph B5.4.5.
- An entity that first applies IFRS 17 as amended in June 2020 after it first applies this Standard shall apply paragraphs 7.2.39–7.2.42. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).

*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

SLR Investment Corp. Common Stock assigned short-term Ba3 & long-term B1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) with Linear Regression ^{1,2,3,4} and conclude that the SLRC 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 SLRC SLR Investment Corp. Common Stock Options & Futures

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

Outlook* | Ba3 | B1 |

Operational Risk | 83 | 30 |

Market Risk | 41 | 78 |

Technical Analysis | 56 | 80 |

Fundamental Analysis | 56 | 30 |

Risk Unsystematic | 90 | 60 |

### Prediction Confidence Score

## References

- Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
- T. Shardlow and A. Stuart. A perturbation theory for ergodic Markov chains and application to numerical approximations. SIAM journal on numerical analysis, 37(4):1120–1137, 2000
- Chen X. 2007. Large sample sieve estimation of semi-nonparametric models. In Handbook of Econometrics, Vol. 6B, ed. JJ Heckman, EE Learner, pp. 5549–632. Amsterdam: Elsevier
- Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
- G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011
- Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
- Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.

## Frequently Asked Questions

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

Q: Is SLRC stock a buy or sell?

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

Q: Is SLR Investment Corp. Common Stock stock a good investment?

A: The consensus rating for SLR Investment Corp. Common Stock is Buy and assigned short-term Ba3 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of SLRC stock?

A: The consensus rating for SLRC is Buy.

Q: What is the prediction period for SLRC stock?

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