Introduction

Ramstack implements math modules and algorithms on-chain to simulate token pair price and predict option price.

Demo information

• Frontend Application
• Video demo
• Deployed Ramstack on RandomNet
• Math formulas

For more detailed information on product features, you can refer to our project description on TaiKai.

Key ideas

Our project employs the main idea of developing an on-chain algorithm using Monte Carlo simulation and implementing distributed computation using smart contracts to simulate the token price.

Architecture

• We use Aptos_std and Aptos_framework as the foundation to develop Ramstack. The most important modules are fixed_point64 and math_fixed64.

• To generate random numbers following probability distributions, we utilize the Aptos randomness API to generate uniform distribution numbers initially. Subsequently, math formulas such as Box-Muller and inverse CDF are applied to transform these numbers.

• For frontend development, we employ Aptos-labs/ts-sdk, Next.js, Redux Toolkit, Rechart, and Ant Design.

Ramstack modules

• PI: Approximate the value of π using the Bailey-Borwein-Plouffe and Leibniz formulas.

• Cosine and Sine: Approximate Cos(x) and Sin(x) using the Maclaurin series formula, where x is in radians.

• Fixed Point64 with Sign: Enhance the original fixed_point64 module in the aptos_std package to support both positive and negative numbers.

• Math Fixed64 with Sign: Enhance the original math_fixed64 module in the aptos_std package to allow operations such as multiplication, division, natural logarithm, mean, standard variation, minimum, maximum, and square root using fixed_point64_with_sign. This enables operations on both negative and positive numbers.

• Box-Muller: Transform random numbers of uniform distribution (generated from Randomness) to normal distribution using the Box-Muller method.

• Chi-square Transform: Transform random numbers of uniform distribution to Chi-square distribution. (uniform -> normal -> Chi-square)

• Laplacian Transform: Transform random numbers of uniform distribution to Laplacian distribution using the inverse CDF.

• Exponential Transform: Transform random numbers of uniform distribution to Exponential distribution using the inverse CDF.

• Prob_distribution: Include view functions to generate random numbers based on inputs and specific distributions.

• Price_simulation: Include view functions to generate price paths based on inputs and the Monte Carlo algorithm.

Installation

To build & test smart contract:

• Go to smart contract folder, e.g. cd contracts/ramstack
• To compile: aptos move compile
• To test: aptos move test
• To deploy: aptos move publish --expiration-secs 6000000

To run Ramstack frontend application:

• cd frontend
• npm i
• npm run dev for the dev mode
• npm run build & npm run start for the production mode.