Rewards Emission

Reward Overview

In the Web3 economy, reward allocation is crucial for distributing tokens and incentivizing behaviors that align with the objectives of decentralized platforms. A total of 250 million tokens have been allocated to Rewards, representing 23% of the total initial supply. These tokens will be vested over 120 months with no lock-up period.

Reward Distribution Methodology

There are several distribution functions (e.g., Declining curve, Beta curve, Exponential curve, etc.) each with different objectives for distributing and issuing a reward. At this stage, the Wow Earn rewards token emission curve is modeled using an S-shape (Sigmoid) function, which allows for a controlled and predictable emission rate over a 10-year period (120 months). This function ensures that the total token supply is managed effectively, preventing excessive inflation. The formula for the function is:

𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛(𝑡) = 1/ 1 + 𝐵 × 𝑒 − 𝑡 /𝑠

Where :

• B (Backweight Factor): Determines the steepness of the curve before it starts to level off.

• S (Slope Factor): Controls the slope of the sigmoid function, influencing how quickly the curve transitions from the initial rapid increase to the plateau.

• t: The period in months. The emissions are then normalized to fit within the 120-month period.

Although the distribution of the rewards must favor the early adopter participants, it should maintain relative fairness to avoid discouraging newcomers from discovering the platform and learning how it works. To meet a certain level of fairness, the model's parameters (backweight and slope factors) have been optimized to converge towards a Gini coefficient of approximately 0.3 (this low coefficient indicates a high level of equality in token distribution overtime, aiming to minimize wealth concentration and promote a fairer ecosystem). Once the protocol is live, this coefficient could be monitored to maintain this objective.

To calculate the Gini coefficient based on the Lorenz curve and ensure a certain level of equity in the reward distribution, the following method was used:

1. Normalize the values and sort them in ascending order.

2. Multiply each value by its rank.

3. Apply the formula: 𝐺𝑖𝑛𝑖 = ( 2 × 𝐼𝑛𝑑𝑒𝑥𝑒𝑑 𝑆𝑢𝑚 /𝑃𝑒𝑟𝑖𝑜𝑑 ) − ( 𝑃𝑒𝑟𝑖𝑜𝑑 + 1/ 𝑃𝑒𝑟𝑖𝑜𝑑 )

Where:

• Indexed Sum: The sum of the products of each normalized value and its rank.

• Period: The total number of periods (months). To reach a Gini coefficient of ~0.3, the specific parameters used were:

• Slope Factor: 25 • Backweight Factor: 3