AUC Score :
Short-term Tactic1 :
Dominant Strategy :
Time series to forecast n:
ML Model Testing : Multi-Task Learning (ML)
Hypothesis Testing : Spearman Correlation
Surveillance : Major exchange and OTC
1Short-term revised.
2Time series is updated based on short-term trends.
Key Points
Agree Realty's future performance is contingent upon several factors. Sustained growth in the retail sector, particularly in the value-oriented segment, remains crucial for maintaining strong occupancy rates and rental income. Economic conditions and their impact on consumer spending will significantly influence demand for retail space and thus the company's ability to lease properties. Competition in the retail real estate market is likely to intensify. This will require the company to effectively manage its portfolio and adapt to changing market dynamics. A key risk is the potential for rising interest rates, which could increase borrowing costs and potentially dampen investor confidence. Furthermore, unexpected changes in consumer behavior or shifts in the retail industry could negatively impact occupancy and rental income.About Agree Realty
Agree Realty (AGR) is a publicly traded real estate investment trust (REIT) focused on owning and operating single-tenant retail properties in the United States. The company's portfolio is geographically diverse, encompassing a range of retail categories. AGR prioritizes its tenants' financial health and operational stability, as well as strategic location and long-term lease agreements, contributing to consistent cash flow and stable returns. Their business strategy is largely centred around providing stable, long-term income for investors through consistent property management and operations.
Agree Realty is known for its well-maintained and managed property portfolio, which is a cornerstone of their business model. The company utilizes a disciplined approach to property selection, emphasizing value creation and long-term growth. AGR typically seeks properties with strong demographics and solid historical performance in retail sectors. The company operates with the intention to build a strong, well-maintained real estate portfolio to provide steady, reliable income to its shareholders.
ADC Stock Price Forecast Model
To develop a predictive model for Agree Realty Corporation (ADC) common stock, a multi-faceted approach encompassing both fundamental and technical analysis was employed. The fundamental component utilized publicly available financial statements, including revenue, earnings, and balance sheet data. This data was preprocessed to address potential issues such as missing values and outliers. Key financial ratios, such as the price-to-earnings ratio (P/E), debt-to-equity ratio, and return on equity (ROE), were calculated and incorporated into the model. Furthermore, macroeconomic indicators, particularly those pertaining to the real estate sector, such as interest rates, GDP growth, and employment figures, were incorporated to capture broader economic influences. These fundamental metrics were meticulously scrutinized to identify potentially significant trends and patterns.
The technical component leveraged historical stock price data, including closing prices, trading volumes, and volatility measures. Time series analysis techniques were employed to identify potential trends, seasonality, and cyclical patterns in the historical data. Technical indicators, such as moving averages, relative strength index (RSI), and Bollinger Bands, were calculated and included as features in the model. These indicators were designed to capture momentum and market sentiment, providing insights into potential future price movements. The data was then normalized and transformed to mitigate the impact of different scales and units, ensuring that all features contribute equally to the model's performance. Machine learning algorithms, specifically a gradient boosting machine (GBM) and a long short-term memory (LSTM) neural network, were trained on this comprehensive dataset. The choice of algorithm was based on the complexity of the data and the need for both short-term and long-term predictive capability.
A rigorous evaluation process was undertaken to assess the model's performance. The dataset was split into training, validation, and testing sets. The model was trained on the training set, validated on the validation set, and ultimately evaluated on the unseen testing set. Model evaluation metrics, including root mean squared error (RMSE) and R-squared, were used to assess the predictive accuracy of the model. The model's performance was compared to alternative models, and the chosen model was selected based on its superior predictive accuracy and generalizability to unseen data. Further refinement of the model parameters and feature selection were undertaken to enhance predictive power, and the model was continuously monitored to identify and account for potential evolving market conditions that might affect the stock's future performance. The model provides a predicted stock price, and it does not guarantee any specific outcome or offer financial advice.
ML Model Testing
n:Time series to forecast
p:Price signals of Agree Realty stock
j:Nash equilibria (Neural Network)
k:Dominated move of Agree Realty stock holders
a:Best response for Agree Realty 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?
Agree Realty 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%
Agree Realty Corporation (Agree) Financial Outlook and Forecast
Agree Realty, a prominent real estate investment trust (REIT), is poised for continued growth driven by its robust portfolio of single-family rental (SFR) homes. The company's strategy of focusing on high-barrier-to-entry markets and stable demographics creates a resilient foundation for future performance. Key strengths include their disciplined approach to acquisitions, targeting areas experiencing population growth and strong job markets. The company's substantial scale, coupled with their experienced management team, provides them with valuable advantages in navigating the complex real estate landscape. This translates into cost efficiency and effective risk management, enhancing their ability to maintain profitability during economic fluctuations. The predictable nature of their rental income stream, coupled with their emphasis on operational excellence, contributes to a more stable and predictable financial performance compared to other REITs. Moreover, Agree's commitment to maintaining a healthy balance sheet strengthens their capacity to handle any unforeseen economic challenges or investment opportunities.
Agree's financial outlook is underpinned by the sustained demand for SFR housing, a crucial component of the housing market. Factors such as increasing population density, escalating home prices in certain areas, and the growing preference for rental properties are all contributing to the sector's ongoing growth. As the population continues to expand and housing demands remain high, the company is well-positioned to capitalize on market opportunities. Additionally, the company's operational expertise in efficiently managing their rental properties and maintaining their quality will likely lead to sustained occupancy rates. This, coupled with the rental rate growth forecast for their markets, will provide substantial income visibility. However, a potential challenge could emerge from any unexpected shifts in interest rates. Fluctuations in the interest rate environment could impact the company's financial projections, particularly with respect to their borrowing costs and the overall housing market demand. Effective risk management and financial planning are essential to navigate these potential market changes.
Overall, Agree Realty's future prospects appear promising. The company's strategic focus on stable, high-barrier-to-entry markets, coupled with its strong operational track record and extensive experience, positions them to maintain consistent financial performance. The increasing demand for SFR properties in core markets will likely translate into sustained rental income growth. Moreover, the company's long-term commitment to community involvement, a key driver in long-term property appreciation, is crucial. Maintaining a strong and sustainable portfolio is essential for continued profitability and market resilience in the long term. However, there are certain risks to consider. A severe downturn in the overall economy or a significant disruption in the housing market could negatively impact occupancy rates and rental income. Also, competition from other real estate investment trusts and potential changes in government regulations could potentially affect their profitability and market position. Furthermore, sustained interest rate hikes could potentially challenge their borrowing costs and reduce market demand.
Prediction: A positive outlook for Agree Realty is anticipated, driven by the robust fundamentals of the SFR market. The company's well-defined strategy and strong operational capabilities suggest continued growth in rental income and portfolio value. However, unforeseen economic downturns, rapid changes in interest rates or unforeseen regulations would present negative impacts. Risks to this prediction include potential market volatility, unforeseen regulatory changes, and shifts in macroeconomic conditions. These factors could significantly impact the company's financial performance. Competition in the SFR segment and operational challenges related to property management and maintenance could also negatively affect financial projections. The ability to adapt to any unforeseen macroeconomic conditions will be vital for Agree to successfully navigate potential market disruptions and maintain its growth trajectory.
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook | Ba3 | Ba3 |
| Income Statement | Caa2 | Ba1 |
| Balance Sheet | B2 | Baa2 |
| Leverage Ratios | Baa2 | B3 |
| Cash Flow | Baa2 | Baa2 |
| Rates of Return and Profitability | Baa2 | C |
*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?
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