Interactive Demos

A few interactive examples from my quantitative toolkit.

A Note on Simulations

These demos use Monte Carlo methods, which involve randomness. As a result, you may see slightly different results each time a simulation runs, even with the same inputs. This reflects the probabilistic nature of the models.

Customer Lifetime Value (CLV) Simulation

Controls

Average Monthly Spend: $50

Monthly Churn Rate: 5%

Annual Discount Rate: 5%

Customer Acquisition Cost (CAC)

Model Assumptions

Churn rate is constant each month.
Monthly spend is constant for a customer's lifetime.
Future revenue is discounted to present value.

Average Customer Lifetime Value:

$0.00

Probability of Profitability (CLV > CAC):

0.00%

Distribution of Possible CLV

This histogram shows the range of potential lifetime values from thousands of simulated customers. It highlights that CLV is not a single number, but a distribution of possibilities.

Bayesian A/B Testing

Variant A

Successes

Trials

Variant B

Successes

Trials

Model Assumptions (Priors)

The simulation begins with a prior belief that both variants have a ~5% conversion rate, with a confidence strength of 20. This belief is updated as new data is entered.

Credit Portfolio Simulation

Controls

Number of Loans

Avg PD (%)

Asset Correlation: 0.20

Systemic Stress Factor: 0.0

Equity Tranche: 10%

Model Assumptions

This simulation uses the Vasicek one-factor model, assuming all loans share a single systemic risk factor (e.g., the economy). The 'Asset Correlation' slider controls how sensitive each loan is to this common factor.

Loss Distribution

This histogram shows the probability of different portfolio loss levels based on thousands of simulations. The red dashed line indicates the equity tranche, which absorbs initial losses.

Let's Collaborate

Have a specific challenge in mind or interested in how these techniques could apply to your work? I'd love to hear from you.

Get in Touch