Financial Mirroring Strategy: A Data-Driven Approach
Achieve financial resilience and data-backed insights for strategic growth. Schemata’s Financial Mirroring Strategy adapts real-time data from public markets to provide you with actionable insights, helping you build cash strategies aligned with industry benchmarks and investor expectations.
- Maximize Business Stability with Data-Driven Cash Strategies Leverage real-time financial data from market leaders to shape long-term cash flow strategies that withstand economic uncertainties.
- Empower Investors with Transparent, Predictive Insights Investors can access mirrored financial data and metrics from relevant sectors, empowering more accurate and informed investment decisions.
How it Works
Utilising Public Financial Data:
Many publicly traded companies in these sectors make their financial data accessible through platforms like the S&P 500 and other stock exchanges. This data includes essential financial metrics like multiples, enterprise values, and other key financial ratios. Schemata considers companies with Similar Macroeconomic Conditions and then gathers this real-time financial information as the baseline for analysis.
Adjusting for Market Specifics
To adapt the financial data from public companies and apply it to private firms, Schemata adjust these figures using factors such as Small-Size Discount, Liquidity Adjustment, Sector-Specific Growth Rates, Geographical Adjustments and Valuation Multiples
Mirroring Private Companies:
Using this adjusted data, Schemata creates a financial mirror that reflects the expected financial performance of private companies. This mirrored data serves as a proxy for private firms, allowing us to forecast trends, simulate financial scenarios, and conduct variance analyses between expected and actual performance.
Providing Forecast and Simulation Tools:
Schemata’s mirrored data enables both businesses and investors to run simulations and check variances in financial performance. For businesses, this can help with financial planning and decision-making based on realistic, sustainable assumptions. For investors, this mirrored financial model serves as a valuable tool for forecasting the financial health of private companies they are interested in.
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Schemata’s goal is to help businesses develop a sustainable cash management strategy that can withstand market fluctuations and economic uncertainties. Through real-time financial insights and forecasting, Schemata provides businesses with the tools they need to optimise cash flow, reduce financial risks, and make informed decisions that contribute to long-term success.
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For investors, Schemata acts as a transparent lens into financial performance. By utilising real-time financial data and analytics, we offer investors valuable insights into the health and performance of companies within key industries—specifically FinTech and Energy. Schemata’s platform helps investors forecast trends, evaluate risks, and make well-informed investment decisions based on credible, data-backed insights
See a Glimpse of the adjusted market conditions Schemata Would employ in building sustainable financial Model
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Small-Size Discount
- Rationale: Smaller companies tend to be less liquid and carry more risk compared to larger public companies. Investors typically expect higher returns to compensate for this additional risk. By applying a small-size discount, Schemata can adjust for the difference in scale between large public companies and smaller private firms.
- Application: Adjusting financial metrics like the Price-to-Earnings (P/E) ratio or enterprise value to account for the smaller scale of private companies.
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Liquidity AdjustmentRationale: Publicly traded companies have higher liquidity since their shares can be easily bought and sold. Private companies, on the other hand, have much lower liquidity, making them riskier investments. Adjusting for liquidity ensures that the mirrored data more accurately reflects the marketability risks faced by private firms.
Application: Applying liquidity discounts, typically using Discount for Lack of Marketability (DLOM), will provide a better representation of private company valuations based on public comparables. -
Sector-Specific Growth RatesRationale: Different sectors (e.g., FinTech vs. Energy) have varied growth patterns, so it’s important to adjust financial modelling based on sector-specific trends. For example, the renewable energy sector might be growing faster than traditional energy companies, and FinTech might see different regulatory constraints.
Application: Using growth metrics and historical data from sector-specific performance to mirror how similar private companies would perform. -
Geographical AdjustmentsRationale: Companies operating in different regions face unique macroeconomic conditions, including local regulations, taxation, inflation, and consumer behaviour. Cross-continental markets may experience different economic conditions compared to African markets.
Application: Companies operating in different regions face unique macroeconomic conditions, including local regulations, taxation, inflation, and consumer behaviour. Cross-continental markets may experience different economic conditions compared to African markets. -
Valuation MultiplesRationale: Valuation multiples such as Enterprise Value (EV)/EBITDA, Price-to-Earnings (P/E), or Price-to-Sales (P/S) can vary significantly between public and private companies due to market perception, growth potential, and risk profiles.
Application: Adjusting these multiples by applying discounts or premiums based on factors such as size, marketability, and sector-specific performance.
The Financial Mirroring Strategy allows Schemata to provide meaningful, real-time insights for businesses and investors even when access to internal data is limited. By using a proven financial model adjusted to reflect the realities of private firms, we offer a reliable, data-driven basis for financial forecasting and decision-making.
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