Our Models

Relative Valuation Model (RVM)

The Relative Valuation Model (RVM) is used to determine whether a company's stock is overvalued or undervalued relative to its peers. It compares a target company's financial metrics (such as EV/EBITDA) with those of other companies in the same industry.

Steps:

  • Fetch financial data for the target company, focusing on the EV/EBITDA ratio.
  • Identify a set of peer companies within the same industry and fetch their financial data.
  • Calculate the average EV/EBITDA ratio of the peer group.
  • Determine the percentage deviation of the target company's EV/EBITDA ratio from the peer group's average.
  • The model returns whether the target company is overvalued or undervalued based on this percentage deviation.

Goal:

The goal of RVM is to provide investors with insights into how a company's valuation compares with its industry peers, helping them make informed decisions about whether to buy, hold, or sell the stock.

Discounted Dividend Model (DDM)

The Discounted Dividend Model (DDM) is used to estimate the intrinsic value of a company's stock based on the present value of expected future dividends. It is particularly useful for companies that pay regular dividends.

Steps:

  • Gather historical dividend data for the company.
  • Calculate the growth rates of dividends over time.
  • Compute the average growth rate of these dividends.
  • Use the most recent annual dividend and the average growth rate to estimate the future dividends.
  • Discount these future dividends back to their present value using the required rate of return.
  • The intrinsic value of the stock is calculated by dividing the last annual dividend by the difference between the required rate of return and the average growth rate.

Goal:

The goal of the DDM is to determine whether a stock is fairly valued, overvalued, or undervalued based on the present value of its expected future dividends. This helps investors assess the attractiveness of dividend-paying stocks.

Discounted Cash Flow Model (DCF)

The Discounted Cash Flow (DCF) model is used to estimate the intrinsic value of a company based on its projected future cash flows. This model is widely used in investment banking and equity research to assess the value of companies.

Steps:

  • Gather financial data, including free cash flow, current stock price, shares outstanding, total debt, and cash equivalents.
  • Project the future free cash flows for a defined forecast period (e.g., 10 years) using an assumed growth rate.
  • Discount these projected cash flows back to their present value using the company's Weighted Average Cost of Capital (WACC).
  • Calculate the terminal value, which represents the value of the company's cash flows beyond the forecast period, and discount it back to the present value.
  • Sum the discounted cash flows and the discounted terminal value to obtain the enterprise value.
  • Adjust for debt and cash to derive the equity value, and divide by the number of shares outstanding to calculate the intrinsic value per share.

Goal:

The goal of the DCF model is to determine the intrinsic value of a company based on its future cash flow projections. This helps investors assess whether a stock is trading below or above its intrinsic value, guiding buy or sell decisions.

Z-Altman Score

The Z-Altman Score is a financial model used to predict the likelihood of a company going bankrupt. It is based on a combination of five financial ratios that measure various aspects of a company's financial health.

Steps:

  • Fetch key financial data, including working capital, retained earnings, EBIT, total assets, market value of equity, total liabilities, and sales.
  • Calculate the five ratios: Working Capital/Total Assets, Retained Earnings/Total Assets, EBIT/Total Assets, Market Value of Equity/Total Liabilities, and Sales/Total Assets.
  • Multiply each ratio by its respective weight (as determined by the Altman Z-Score formula).
  • Sum these weighted ratios to calculate the Z-Score.
  • Interpret the Z-Score: a score below 1.8 suggests a high risk of bankruptcy, while a score above 3.0 suggests a low risk.

Goal:

The goal of the Z-Altman Score is to provide a quantitative measure of a company's financial distress level, helping investors and creditors assess the bankruptcy risk of a company.

Monte Carlo Simulation

The Monte Carlo Simulation is a powerful statistical technique used to estimate the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables. In finance, it's often used to model the probability of different outcomes in a process that involves market volatility.

Steps:

  • Fetch historical stock price data.
  • Calculate log returns of the historical prices.
  • Compute the mean (drift) and standard deviation (volatility) of the log returns.
  • Generate random daily returns based on the calculated drift and volatility.
  • Simulate multiple price paths for a specified number of days.
  • Calculate various statistics from the simulated paths, including average price, median price, and percentiles.
  • Return the simulation results and summary statistics.

Goal:

The goal of the Monte Carlo Simulation in finance is to provide a range of possible outcomes and the probabilities they will occur for any choice of action. This helps in risk assessment, decision-making under uncertainty, and valuation of complex financial instruments.