Introduction: Quantifying Tokenomics to predict the future

Opening prices and post-TGE pops allow projects to unilaterally determine their valuation at the immediate onset of the Secondary markets. Unfortunately, many projects abuse these Mechanisms in an attempt to inflate their valuations. For example, some projects facilitate post-TGE pops that imply egregious fully diluted valuations relative to more established competitors in an attempt to generate hype and attract the attention of speculative investors with the allure of future returns. This approach often serves to the long-term detriment of a blockchain project as its token price trends steadily downwards following TGE — eroding community sentiment and deterring network participation on the token’s path to $0.

Strategic adjustments to your Tokenomics can help you avoid such pitfalls and put your token in a better position to succeed following TGE. This section will serve as a comprehensive guide to optimizing your TGE token pricing and overall Tokenomics to encourage desirable post-TGE token performance. You’ll find that assigning fair value for your project’s TGE, designating distribution and emissions schedules, and building demand drivers are all interconnected exercises that should be balanced to optimize token price performance. Encouraging sustainable token price performance is critical given its potential to drive increased protocol usage.

At this point in the Tokenomics Design Framework, a few things should be clear to you:

1. You only get one shot at facilitating a token generation event (“TGE”).
2. A successful TGE can catalyze growth for your protocol while an unsuccessful TGE may be interpreted as deteriorating or “broken” fundamentals.
3. Token price is the number one performance indicator used by prospective network participants and speculators to determine underlying protocol value.
4. Token price appreciation can be directed almost unilaterally by a project by (1) setting an opening price, and (2) facilitating a post-TGE pop.
5. Once a post-TGE pop occurs, organic buyers and sellers enter the Secondary market.
6. When organic buyers and sellers begin to trade, a token’s price becomes entirely dependent on their appetite to transact.
7. The willingness of buyers and sellers to transact is largely influenced by the perception of an asset as overvalued or undervalued, which is a function of Supply & Demand.
   1. Supply comes from Token Distributions & Emissions Schedules and Demand is dictated by Token Demand Drivers.
   2. These are the main inputs in Price Discovery, which will occur continuously after the initial post-TGE pop.
8. If supply outpaces demand, the token price will likely depreciate. On the other hand, if demand is greater than supply, then token price may increase.
9. Long-term, positive, sustainable token price performance can drive increased protocol usage by supporting the monetary value of token incentives offered to network participants.

In sum, token price matters. Accordingly, strategic decisions regarding your token’s supply & demand should be influenced based on its future projected performance. But how do we estimate supply & demand in the secondary market to simulate continuous price discovery and predict the future?

We do this by calculating the US dollar value of “patient” and “impatient” buyers & sellers on a daily basis to determine a “start of day” and “end of day” price. The resulting token price from the initial simulation influences the appetite of each side to transact in the next day’s simulation; therefore, price becomes both an output as well as a dynamic variable in the model. The quantitative model is fully responsive and can simulate post-TGE performance for any period following your project’s TGE – for example, we can simulate token performance for the first one-week post-TGE, or up to 100 years post-TGE.

The model accomplishes this by first converting supply from Token Distributions & Emissions Schedules and demand from your project’s Demand Drivers (utility, demand mechanisms, and speculation) into US Dollar terms.

Next, we subtract the supply from the demand to determine the net buying or selling pressure from impatient traders. Positive figures indicate more buyers than sellers while negative figures indicate more sellers than buyers.

We then simulate market impact by taking the resulting net buy/sell pressure and trading it against a dynamic liquidity pool that represents patient buyers and sellers. The resulting “slippage” induced by the simulated trade is then multiplied by a “starting price” to determine an “end-of-day price.” The resulting “end-of-day price” is then used to determine the US dollar value of supply & demand for the next day’s price discovery simulation.

Given that a token’s opening price and the extent of its post-TGE pop are largely user-determined, we can utilize these values to determine a starting price for the model, then simulate price discovery for a token’s first day of trading, then roll this price output to the continuous model to dynamically generate projected prices every day thereafter. By multiplying token price by your project’s Circulating Token Supply and Maximum Token Supply, we can predict key performance indicators such as Market Capitalization (“MC”), and Fully Diluted Valuation (“FDV”) which also become variables and influence liquidity. Based on these predictions, we can adjust and iterate various aspects of your Tokenomics to promote more desirable post-TGE performance.

Helpful Prompts

• Understand the Impact of Opening Prices and Post-TGE Pops: Recognize how these factors can unilaterally determine your project's valuation at the onset of the Secondary markets. Be aware that inflated valuations can lead to a downward trend in token price post-TGE.
• Consider the Role of Supply and Demand: Understand that once organic buyers and sellers begin trading a token, its price is determined by supply and demand in the Secondary market. If the supply entering the market is too great due to high token prices from a post-TGE pop, no reasonable amount of demand can overcome it, leading to price depreciation.
• Leverage Quantitative Models: Use quantitative models to simulate daily price discovery based on your project’s unique Tokenomics. This can help you predict future token price performance and make strategic decisions regarding your token’s supply and demand.
• Iterate Your Tokenomics Based on Predictions: Use the predictions from your quantitative model to adjust and iterate various aspects of your Tokenomics to promote more desirable post-TGE performance. This includes factors like token price, circulating token supply, and maximum token supply.