Dominant Strategy : Hold
Time series to forecast n: 09 Apr 2023 for (n+1 year)
Methodology : Modular Neural Network (Speculative Sentiment Analysis)
Abstract
Goldman Sachs BDC Inc. Common Stock prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the GSBD stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: HoldKey Points
- Market Risk
- Can stock prices be predicted?
- Market Risk
GSBD Target Price Prediction Modeling Methodology
We consider Goldman Sachs BDC Inc. Common Stock Decision Process with Modular Neural Network (Speculative Sentiment Analysis) where A is the set of discrete actions of GSBD 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(Wilcoxon Rank-Sum Test)5,6,7= X R(Modular Neural Network (Speculative Sentiment Analysis)) X S(n):→ (n+1 year)
n:Time series to forecast
p:Price signals of GSBD 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?
GSBD Stock Forecast (Buy or Sell) for (n+1 year)
Sample Set: Neural NetworkStock/Index: GSBD Goldman Sachs BDC Inc. Common Stock
Time series to forecast n: 09 Apr 2023 for (n+1 year)
According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold
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 Goldman Sachs BDC Inc. Common Stock
- For lifetime expected credit losses, an entity shall estimate the risk of a default occurring on the financial instrument during its expected life. 12-month expected credit losses are a portion of the lifetime expected credit losses and represent the lifetime cash shortfalls that will result if a default occurs in the 12 months after the reporting date (or a shorter period if the expected life of a financial instrument is less than 12 months), weighted by the probability of that default occurring. Thus, 12-month expected credit losses are neither the lifetime expected credit losses that an entity will incur on financial instruments that it predicts will default in the next 12 months nor the cash shortfalls that are predicted over the next 12 months.
- All investments in equity instruments and contracts on those instruments must be measured at fair value. However, in limited circumstances, cost may be an appropriate estimate of fair value. That may be the case if insufficient more recent information is available to measure fair value, or if there is a wide range of possible fair value measurements and cost represents the best estimate of fair value within that range.
- All investments in equity instruments and contracts on those instruments must be measured at fair value. However, in limited circumstances, cost may be an appropriate estimate of fair value. That may be the case if insufficient more recent information is available to measure fair value, or if there is a wide range of possible fair value measurements and cost represents the best estimate of fair value within that range.
- Time value of money is the element of interest that provides consideration for only the passage of time. That is, the time value of money element does not provide consideration for other risks or costs associated with holding the financial asset. In order to assess whether the element provides consideration for only the passage of time, an entity applies judgement and considers relevant factors such as the currency in which the financial asset is denominated and the period for which the interest rate is set.
*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
Goldman Sachs BDC Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Goldman Sachs BDC Inc. Common Stock prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the GSBD stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold
GSBD Goldman Sachs BDC Inc. Common Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | B2 | Ba3 |
Balance Sheet | C | Baa2 |
Leverage Ratios | Caa2 | Baa2 |
Cash Flow | Baa2 | C |
Rates of Return and Profitability | Baa2 | Baa2 |
*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

References
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- Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
- Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79
- V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
- Mullainathan S, Spiess J. 2017. Machine learning: an applied econometric approach. J. Econ. Perspect. 31:87–106
- V. Konda and J. Tsitsiklis. Actor-Critic algorithms. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1008–1014, 2000
- V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
Frequently Asked Questions
Q: What is the prediction methodology for GSBD stock?A: GSBD stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Wilcoxon Rank-Sum Test
Q: Is GSBD stock a buy or sell?
A: The dominant strategy among neural network is to Hold GSBD Stock.
Q: Is Goldman Sachs BDC Inc. Common Stock stock a good investment?
A: The consensus rating for Goldman Sachs BDC Inc. Common Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of GSBD stock?
A: The consensus rating for GSBD is Hold.
Q: What is the prediction period for GSBD stock?
A: The prediction period for GSBD is (n+1 year)