Token Valuation

Valuation Method

Let price(t),token(t),asset(t)\mathtt{price}(t), \mathtt{token}(t), \mathtt{asset}(t) be the token price, token supply, and asset under management (AUM), at time tt, respectively. Since all the management fee is used for buying back and burning. Using the discounted cash flow (DCF) model, the following relation holds.

price(t)token(t)=tϕasset(x)eλxdx\mathtt{price}(t) \cdot \mathtt{token}(t) = \int_t^\infty \phi \cdot \mathtt{asset}(x) \cdot e^{-\lambda x} dx

where ϕ\phi is the annual management fee rate and λ\lambda is the discount rate or rate of return on risky assets.

Following the staking-reward model and the buyback-and-burn mechanism, we break down the token supply into

token(t)=mint(t)burn(t)0\mathtt{token}(t) = \mathtt{mint}(t) - \mathtt{burn}(t) \ge 0

where mint(t),burn(t)\mathtt{mint}(t), \mathtt{burn}(t) are the total tokens minted and burned, respectively.

Assume that mint(t)\mathtt{mint}(t) is monotonically increasing and bounded over [M0,M]R+[M_0, M_\infty] \subseteq \mathcal{R}^+. That is, M0M_0 represents the initial token supply and MM_\infty the maximum token supply. The total tokens burned is given by

burn(t)=0tϕasset(x)price(t)dx\mathtt{burn}(t) = \int_0^t \phi \cdot \dfrac{\mathtt{asset}(x)}{\mathtt{price}(t)} dx

The equations above give

price(t){mint(t)burn(t)}=tϕasset(x)eλxdxprice(t){mint(t)0tϕasset(x)price(t)dx}=tϕasset(x)eλxdxprice(t)mint(t)0tϕasset(x)dx=tϕasset(x)eλxdx\begin{align*} \mathtt{price}(t) \cdot \Big \{ \mathtt{mint}(t) - \mathtt{burn}(t) \Big \} &= \int_t^\infty \phi \cdot \mathtt{asset}(x) \cdot e^{-\lambda x} dx \\ \mathtt{price}(t) \cdot \Big \{ \mathtt{mint}(t) - \int_0^t \phi \cdot \dfrac{\mathtt{asset}(x)}{\mathtt{price}(t)} dx \Big \} &= \int_t^\infty \phi \cdot \mathtt{asset}(x) \cdot e^{-\lambda x} dx \\ \mathtt{price}(t) \cdot \mathtt{mint}(t) - \int_0^t \phi \cdot \mathtt{asset}(x) dx &= \int_t^\infty \phi \cdot \mathtt{asset}(x) \cdot e^{-\lambda x} dx \end{align*}

​The generic model of the token price therefore is

price(t)=1mint(t){0tϕasset(x)dx+tϕasset(x)eλxdx}\mathtt{price}(t) = \frac{1}{\mathtt{mint}(t)} \left \{ \int_0^t \phi \cdot \mathtt{asset}(x) dx + \int_t^\infty \phi \cdot \mathtt{asset}(x) \cdot e^{-\lambda x} dx \right \}

​Expected Supply and Price Function

Assume the following parametric forms.

asset(t)=Aeαtmint(t)=M0eαt+M(1eαt)\begin{align*} \mathtt{asset}(t) &= A \cdot e^{\alpha t} \\ \mathtt{mint}(t) &= M_0 \cdot e^{-\alpha t} + M_\infty \cdot (1 - e^{-\alpha t}) \end{align*}

where α>0\alpha > 0 is the expected (log) growth rate in AUM. Note that the initial and asymptotic conditions already hold.

mint(0)=M0limtmint(t)=M\begin{align*} \mathtt{mint}(0) &= M_0 \\ \lim_{t \to \infty} \mathtt{mint}(t) &= M_\infty \end{align*}

To show that mint(t)\mathtt{mint}(t) is monotonically increasing at a diminishing growth rate.

ddtmint(t)=αM0eαt+αMeαt=α(M0+M)eαt0d2dt2mint(t)=α2M0eαtMα2eαt0=α2(M0M)eαt0\begin{align*} \dfrac{d}{dt} \mathtt{mint}(t) &= -\alpha \cdot M_0 \cdot e^{-\alpha t} + \alpha \cdot M_\infty \cdot e^{-\alpha t} \\ &= \alpha \cdot (-M_0 + M_\infty) \cdot e^{-\alpha t} \ge 0 \\ \dfrac{d^2}{dt^2} \mathtt{mint}(t) &= \alpha^2 \cdot M_0 \cdot e^{-\alpha t} - M_\infty \cdot \alpha^2 \cdot e^{-\alpha t} \le 0 \\ &= \alpha^2 \cdot (M_0 - M_\infty) \cdot e^{-\alpha t} \le 0 \end{align*}

The initial AUM is targeted at 30 million USD and is expected to grow at a rate of 61.80% annually. Hence, α=log(1+0.6180)0.4812\alpha = \log (1 + 0.6180) \approx 0.4812. The tokens have an initial supply of 30 million and will be gradually released to reach the maximum supply of 100 million. Hence, in a scale of 10610^6 (million), we have:

asset(t)=30e0.4812tmint(t)=30e0.4812t+100(1e0.4812t)\begin{align*} \mathtt{asset}(t) &= 30 \cdot e^{0.4812 t} \\ \mathtt{mint}(t) &= 30 \cdot e^{-0.4812 t} + 100 \cdot (1 - e^{-0.4812 t}) \end{align*}

Based on the the generic pricing equation and assuming a discount rate of 100.00% annually i.e. λ=log(1+1.0000)0.6931\lambda = \log (1 + 1.0000) \approx 0.6931, we have

price(t)=1mint(t){0t0.0230e0.4812xdx+t0.0230e0.2119xdx}=1mint(t){1.2469(e0.4812t1)+2.8311e0.2119t}=1.2469(e0.4812t1)+2.8311e0.2119t30e0.4812t+100(1e0.4812t) \begin{align*} \mathtt{price}(t) &= \dfrac{1}{\mathtt{mint}(t)} \left \{ \int_0^t 0.02 \cdot 30 \cdot e^{0.4812 x} dx + \int_t^\infty 0.02 \cdot 30 \cdot e^{-0.2119 x} dx \right \} \\ &= \dfrac{1}{\mathtt{mint}(t)} \left \{ 1.2469 \cdot (e^{0.4812 t} - 1) + 2.8311 \cdot e^{-0.2119 t} \right \} \\ &= \dfrac{ 1.2469 \cdot (e^{0.4812 t} - 1) + 2.8311 \cdot e^{-0.2119 t} }{ 30 \cdot e^{-0.4812 t} + 100 \cdot (1 - e^{-0.4812 t}) } \end{align*}

Visualizing the supply and price function

1. Expected supply over time

The token emission is scheduled based on all the assumptions above. This schedule represents only the emission plan yet does not take into account the burning mechanism.

The following plot shows the token supply function, designated by:

mint(t)=30e0.4812t+100(1e0.4812t)\mathtt{mint}(t) = 30 \cdot e^{-0.4812 t} + 100 \cdot (1 - e^{-0.4812 t})

2. Expected price over time with burning mechanism

The expected pricing is based on all the assumptions above and evaluated at a unit price-to-earning ratio (P/E). Note also that we assume that the tokens initially offered to Backers Sale and Avareum Lab are available without any promotion terms and conditions.

The following plot shows the token price function, designated by:

price(t)=1.2469(e0.4812t1)+2.8311e0.2119t30e0.4812t+100(1e0.4812t)\mathtt{price}(t) = \dfrac{ 1.2469 \cdot (e^{0.4812 t} - 1) + 2.8311 \cdot e^{-0.2119 t} }{ 30 \cdot e^{-0.4812 t} + 100 \cdot (1 - e^{-0.4812 t}) }

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