Pantera Research: Crypto Users Lack Patience, Instant Gratification Outweighs Future Gains

Pantera Capital

24-06-20 08:00

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Original title: Crypto Users Are Comparatively Impatient

Original author: PAUL VERADITTAKIT, Pantera Capital

Original translation: TechFlow

Do cryptocurrency users need intervention?

· A study by Pantera Research Lab found that cryptocurrency users exhibited high present bias and low discount factor, indicating a strong preference for instant gratification.

· The quasi-hyperbolic discounting model, characterized by parameters such as present bias (ꞵ) and discount factor (), helps understand the tendency of individuals to prefer immediate returns over future gains, a behavior that is particularly evident in the volatile and speculative cryptocurrency market.

· This research can be used to optimize token distribution, such as airdrops used to reward early users, decentralized governance, and market new products.

Introduction

A classic example in Silicon Valley startup stories is Paypal’s decision to pay users $10 to use its product. The logic behind this is that if you can pay people to join, eventually the network value will be high enough that new people will join for free and you can stop paying. This does seem to work, as PayPal was able to stop paying and continue to grow, bootstrapping the network effect.

In the cryptocurrency space, we have adopted and extended this approach by not only paying people to join through airdrops, but also generally requiring them to use our product for a period of time.

Quasi-Hyperbolic Discount Model

Airdrops have become a multifaceted tool for rewarding early users, decentralizing protocol governance, and promoting new products. In particular, developing the distribution criteria has become an art when it comes to determining who should receive the rewards and the value of their efforts. In this context, the amount and timing of token distributions (usually through mechanisms such as vesting periods or gradual release) play an important role. These decisions should be based on systematic analysis rather than relying on guesswork, emotion, or precedent. Using a more quantitative framework can ensure fairness and alignment with long-term goal strategies.

The quasi-hyperbolic discount model provides a mathematical framework for exploring the choices individuals make when weighing rewards across different points in time. Its application is particularly relevant in areas where impulsivity and time inconsistency significantly influence decision making, such as financial decision making and health-related behavior.

The model is driven by two specific parameters: current preference (ꞵ) and discount factor ( ).

Current Preference (ꞵ):

This parameter measures an individual's tendency to prioritize immediate rewards over distant rewards. Its values range between 0 and 1, where 1 indicates no current preference, reflecting a balanced, time-consistent evaluation of future rewards. Values closer to 0 indicate stronger current preference, indicating a high preference for immediate rewards.

For example, given the choice between taking $50 today or $100 a year from now, someone with a high current preference (close to 0) would prefer to take the $50 immediately rather than wait for the larger sum.

Discount Factor ( ):

This parameter describes the rate at which the value of a future reward decreases as the time to its realization increases, taking into account its perceived value that naturally decreases with delay. The discount factor is more accurately quantified over longer, multi-year intervals. The factor exhibits considerable variability when evaluating two options over short periods of time (less than a year) because immediate circumstances may disproportionately influence perceptions.

For the general population, research suggests that the discount factor is typically around 0.9. However, in groups with a stronger propensity to gamble, this value is often significantly lower. Research suggests that habitual gamblers have an average discount factor of just under 0.8, while problem gamblers have a discount factor closer to 0.5.

Using the above terminology, we can express the utility U of receiving reward x at time t by the following formula:

U(t) = tU(x) U(t) = tU(x)

This model captures how the value of rewards changes over time: immediate rewards are valued at full utility, while future rewards are adjusted for current preferences and exponential decay.

Experiment

Last year, Pantera Research Lab conducted a study to quantify the behavioral tendencies of cryptocurrency users. We surveyed participants with two simple questions designed to measure their preference for immediate payments versus future value.

This approach helped us identify representative ꞵ and values. Our study found that a representative sample of cryptocurrency users exhibited a current preference slightly above 0.4 and a significantly lower discount factor.

The study revealed that cryptocurrency users have an above-average current preference and a low discount factor, indicating a tendency to be impatient and prefer immediate gratification over future gains.

This can be attributed to several interrelated factors in the cryptocurrency environment:

· Cyclical market behavior:Crypto markets are known for their volatility and cyclicality, with tokens often experiencing rapid swings in value. This cyclicality impacts user behavior, as many are accustomed to navigating these cycles rather than adopting long-term investment strategies more common in traditional finance. Frequent ups and downs can cause users to discount future value more steeply, fearing that a potential decline could wipe out profits.

· Stigma of tokens:The survey specifically asked about tokens and their perceived future value, which may highlight the deep-seated stigma associated with token trading. The stigma of token valuations, which is associated with cyclicality and speculation, reinforces caution about long-term investments. Additionally, if the survey had measured fiat currency or other forms of rewards, the results might have been more consistent with the global average, suggesting that the nature of the rewards may significantly influence the observed discounting behavior.

· Speculative Nature of Cryptocurrency Applications:Today’s cryptocurrency ecosystem is deeply rooted in speculation and trading, and these characteristics are particularly prevalent in its most successful applications. This tendency suggests that current users overwhelmingly prefer speculative platforms, a preference reflected in the survey results, which show a strong preference for immediate financial gains.

While the findings may differ from typical human behavioral norms, they reflect the characteristics and tendencies of the current cryptocurrency user base. This distinction is particularly important for projects designing airdrops and token distributions, as understanding these unique behaviors can enable more strategic planning and reward system structures.

For example, Drift, a perpetual contract DEX on Solana, recently launched its native token DRIFT. The Drift team included a time delay mechanism in its token distribution strategy, offering double rewards to users who wait 6 hours after the token is released to claim the airdrop. The time delay is intended to alleviate the congestion usually caused by bots in the early stages of an airdrop and help stabilize token performance by reducing the surge of initial sellers.

In fact, only 7.5k or 15% (at the time of writing) of potential recipients did not wait 6 hours to claim the doubled reward. Based on our findings, Drift can be delayed for several months and statistically should meet the needs of most end users.