B. Gaming Group Projected to See Continued Growth, Analyst Forecasts for (BRAG)

Outlook: Bragg Gaming Group is assigned short-term B2 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-term Tactic¹ :
Dominant Strategy :
Time series to forecast n: for Weeks²
ML Model Testing : Supervised Machine Learning (ML)
Hypothesis Testing : Wilcoxon Rank-Sum Test
Surveillance : Major exchange and OTC

¹Short-term revised.

²Time series is updated based on short-term trends.

Key Points

Based on current trends, Bragg Gaming is predicted to experience moderate growth, driven by its expansion in North America and the increasing demand for online gaming content. Further market penetration and strategic partnerships could significantly boost revenue. However, the company faces risks including intense competition within the iGaming sector and potential regulatory changes that could impact its operational capabilities. Economic downturns and changes in consumer spending may also pose risks. Furthermore, Bragg Gaming is exposed to volatility in its stock price due to shifts in market sentiment and the impact of acquisitions. Failure to maintain technological excellence and offer attractive gaming experiences may hamper its growth potential and ability to retain customer interest.

About Bragg Gaming Group

Bragg Gaming Group Inc. (BRAG) is a global B2B gaming technology and content provider. The company offers a comprehensive suite of products and services to iGaming operators, including proprietary and third-party casino content, player account management (PAM) platforms, and various marketing tools. BRAG's business model revolves around licensing its content and platform solutions to regulated online gaming markets worldwide. This allows operators to offer diverse gaming experiences to their players while also leveraging BRAG's expertise in compliance, technology, and market analysis.

The company focuses on expanding its presence in established and emerging regulated markets. BRAG actively seeks partnerships with operators and regulators to drive growth. This strategy involves obtaining licenses in new jurisdictions, integrating its content with operators' platforms, and localizing its offerings to meet regional player preferences. The company's product portfolio includes a wide variety of slot games, table games, and other gaming solutions. It aims to deliver engaging and innovative gaming experiences to players across various platforms.

BRAG Stock Prediction Model

Our team of data scientists and economists has developed a machine learning model to forecast the performance of Bragg Gaming Group Inc. (BRAG) common shares. The model incorporates a multifaceted approach, leveraging both fundamental and technical indicators. Fundamental analysis incorporates macroeconomic variables such as inflation rates, interest rates, and overall market sentiment, aiming to capture the broader economic forces impacting the gaming industry. Simultaneously, we consider company-specific financial data, including revenue growth, profit margins, debt levels, and cash flow. These factors are crucial in assessing Bragg Gaming Group's financial health and potential for future earnings.

The technical analysis component of the model utilizes a variety of time-series techniques. We analyze historical price data, trading volumes, and several technical indicators like moving averages, relative strength index (RSI), and Bollinger Bands. These indicators help identify trends, potential support and resistance levels, and overbought or oversold conditions. The model employs a Recurrent Neural Network (RNN) architecture, particularly Long Short-Term Memory (LSTM) layers, capable of processing sequential data and recognizing patterns over time. This type of model is particularly well-suited to capturing the temporal dependencies inherent in stock prices.

Model training employs a comprehensive dataset spanning several years, including historical BRAG stock data, financial data, and macroeconomic indicators. The model's performance will be continuously monitored and refined using a rolling window validation approach. The output of this model offers an estimate of future direction of BRAG stock performance, helping in strategic portfolio management. The model provides valuable insights, but it is essential to consider that it is not a guarantee of future results. External factors, which the model may not capture, could influence stock prices. Consequently, our forecasts are intended for informational purposes only and should not be considered as financial advice. Investors should always conduct their own research and seek advice from a financial professional.

ML Model Testing

F(Wilcoxon Rank-Sum Test)^6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Supervised Machine Learning (ML))^3,4,5 X S(n):→ 1 Year $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of Bragg Gaming Group stock

j:Nash equilibria (Neural Network)

k:Dominated move of Bragg Gaming Group stock holders

a:Best response for Bragg Gaming Group target price

 

For further technical information as per how our model work we invite you to visit the article below: 

How do KappaSignal algorithms actually work?

Bragg Gaming Group Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

This exclusive content is only available to premium users.

Rating	Short-Term	Long-Term Senior
Outlook	B2	B2
Income Statement	Ba1	B1
Balance Sheet	Caa2	B1
Leverage Ratios	Caa2	Caa2
Cash Flow	Baa2	B2
Rates of Return and Profitability	Caa2	Caa2

*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?

References

1. Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
2. Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
3. Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
4. LeCun Y, Bengio Y, Hinton G. 2015. Deep learning. Nature 521:436–44
5. S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
6. Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
7. Varian HR. 2014. Big data: new tricks for econometrics. J. Econ. Perspect. 28:3–28