Modelling A.I. in Economics

OXLCN Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock (Forecast)

Outlook: Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 16 May 2023 for (n+3 month)
Methodology : Supervised Machine Learning (ML)

Abstract

Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock prediction model is evaluated with Supervised Machine Learning (ML) and Stepwise Regression1,2,3,4 and it is concluded that the OXLCN stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

Key Points

  1. Trading Interaction
  2. Why do we need predictive models?
  3. Is now good time to invest?

OXLCN Target Price Prediction Modeling Methodology

We consider Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of OXLCN 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(Stepwise Regression)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Supervised Machine Learning (ML)) X S(n):→ (n+3 month) i = 1 n a i

n:Time series to forecast

p:Price signals of OXLCN 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?

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

Sample Set: Neural Network
Stock/Index: OXLCN Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock
Time series to forecast n: 16 May 2023 for (n+3 month)

According to price forecasts for (n+3 month) 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%

IFRS Reconciliation Adjustments for Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock

  1. If an entity previously accounted at cost (in accordance with IAS 39), for an investment in an equity instrument that does not have a quoted price in an active market for an identical instrument (ie a Level 1 input) (or for a derivative asset that is linked to and must be settled by delivery of such an equity instrument) it shall measure that instrument at fair value at the date of initial application. Any difference between the previous carrying amount and the fair value shall be recognised in the opening retained earnings (or other component of equity, as appropriate) of the reporting period that includes the date of initial application.
  2. When an entity first applies this Standard, it may choose as its accounting policy to continue to apply the hedge accounting requirements of IAS 39 instead of the requirements in Chapter 6 of this Standard. An entity shall apply that policy to all of its hedging relationships. An entity that chooses that policy shall also apply IFRIC 16 Hedges of a Net Investment in a Foreign Operation without the amendments that conform that Interpretation to the requirements in Chapter 6 of this Standard.
  3. The following are examples of when the objective of the entity's business model may be achieved by both collecting contractual cash flows and selling financial assets. This list of examples is not exhaustive. Furthermore, the examples are not intended to describe all the factors that may be relevant to the assessment of the entity's business model nor specify the relative importance of the factors.
  4. 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.

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

Conclusions

Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock prediction model is evaluated with Supervised Machine Learning (ML) and Stepwise Regression1,2,3,4 and it is concluded that the OXLCN stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

OXLCN Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCC
Balance SheetCaa2B2
Leverage RatiosCaa2Ba1
Cash FlowBaa2C
Rates of Return and ProfitabilityCBa2

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

Prediction Confidence Score

Trust metric by Neural Network: 83 out of 100 with 594 signals.

References

  1. Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
  2. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99
  3. Mnih A, Teh YW. 2012. A fast and simple algorithm for training neural probabilistic language models. In Proceedings of the 29th International Conference on Machine Learning, pp. 419–26. La Jolla, CA: Int. Mach. Learn. Soc.
  4. V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
  5. Chipman HA, George EI, McCulloch RE. 2010. Bart: Bayesian additive regression trees. Ann. Appl. Stat. 4:266–98
  6. Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
  7. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
Frequently Asked QuestionsQ: What is the prediction methodology for OXLCN stock?
A: OXLCN stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Stepwise Regression
Q: Is OXLCN stock a buy or sell?
A: The dominant strategy among neural network is to Buy OXLCN Stock.
Q: Is Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock stock a good investment?
A: The consensus rating for Oxford Lane Capital Corp. 7.125% Series 2029 Term Preferred Stock is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of OXLCN stock?
A: The consensus rating for OXLCN is Buy.
Q: What is the prediction period for OXLCN stock?
A: The prediction period for OXLCN is (n+3 month)

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