Fintech-Collaboration / vixx-token-dapp

A token is created to invest in long term volatility, which is very profitable in market crisis, but also in bull markets through algorithmic trading using an Adaboost machine learning model and VIXM.

VIXCOIN

VIXCOIN is the 1st DeFi/CeFI company that provides a solution to invest long-term in volatility!
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Installation
3. Usage
• Demo
4. Token Valuation
5. License
6. Contact
7. Acknowledgments

About The Project

VIXCOIN is a defi/cefi solutions company that has created a way to invest long-term in volatility using a digital token which is VIXCOIN Our first product utilizes VIXM as the financial investment vehicle but there are plans to expand to others.

How it works: Users can purchase a token on our website that acts like security on a long-term volatility instrument. Using our algorithmic trading strategy when there are buy and sell signals, we take our users cash and invest it in VIXM. Our company provides both a product (VIXCOIN) and a service which is the trading strategy.

• The VIXCOIN token is ERC20 (fungible) and was created utilizing the Etherum blockchain
• The token links digital assets with traditional investments.
• Offers a way to diversify an investors' portfolio during market downturns.
• Opens up investment opportunities to global investors since it was traditional only available to those in the US.
• Token does not rely on supply and demand. It derives value from the performance of our algorithmic trading strategy.

DISCLAIMER: Our product is only deployed to a testnet and our user interface can only be launched locally. Investment in our product is not an option yet.

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Built With

The dApp was built utilizing at least python 3.7 for the back end data analysis and machine learning for the algorithmic trading strategy.

Python Packages

• Pandas
• Numpy
• Datetime
• yfinance
• Sci-kit learn
• Hvplot
• Matplotlib

Smart Contracts

• Solidity
• REMIX IDE
• Chainlink

User Interface

• Django
• JSON

Wallet Integration

• Metamask

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Getting Started

To get a local copy up and running follow these steps below. Alternatively, you can jump straight to the demo section and test out the wesbite portion.

Installation

1. Clone the repo

   git clone https://github.com/Fintech-Collaboration/vixx-token-dapp.git

2. Install python packages listed in the Built With section.
3. To test out the algorithmic trading strategy file, first go to your terminal.
4. In your terminal, navigate to the location where the cloned repo resides.
5. Locate vixm_adaboost_model.ipynb and launch the file in jupyter notebook for data visualizations.
6. Alternatively, if you would like to rerun the model, you may import the file into Google Colab.
7. Website functions are covered in the Demo portion.

Usage

There are multiple components to our dApp:

1. ML/AL trading strategy
2. smart contract
3. web3.py
4. Django UI

Please refer to installation section for how to run the trading strategy. For the UI, please see the next section below.

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Demo

1. To launch the user interface, make sure that you have installed Django for python.
2. In the terminal, navigate to the vixx-trader file from the cloned repo.
3. Start the Django app, enter the info below:

  python manage.py startapp <vixx_trader>

4. If launched, properly, you should see the image below

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Token Valuation

The price of the VixCoin token is linked to the performance of the investment strategy. Here is a comparison of the performance of the VIXCOIN token and the SP500 out-of-sample.
As you can see: If you would have invested $1 in Oct 2019, by the end of 2021 the value of your coin would be $2.50, which is a 150% return, above the 60% of the S&P500.

In our smart contract, we utilize the following formula in order to set the price of the token. TP_t = TP_y * (1+rs) Where s is the signal predicted for the day r is the daily VIXM return token_price_today = token price yesterday(1+vixm_return_yesterday*signal_hat_yesterday)

In order to get VIXM data, we utilize Chainlink to call price feeds into the contract.

NOTE: Current contract that is connected to Django does not utilize the formula above. It is a work in progress.

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License

Distributed under the MIT License. https://github.com/git/git-scm.com/blob/main/MIT-LICENSE.txt)

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Contact

Jason Garcia -(https://www.linkedin.com/in/24-jason-j-garcia/)

Project Link: https://github.com/jasonjgarcia24

Prateek Sharma - (https://www.linkedin.com/in/prateek-sharma-21a081180/)

Project Link: https://github.com/puru444

Paola Carvajal- (https://www.linkedin.com/in/paolacarvajal/)

Project Link: https://github.com/paocarvajal1912

Srini Goda - (https://www.linkedin.com/in/srini-goda-2305644/)

Project Link: https://github.com/your_username/repo_name

Jasmine Tengsico - (https://www.linkedin.com/in/jasmine-tengsico-5030b0167/)

Project Link: https://github.com/jtengsico

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Acknowledgments

Credit to creator of readme template.

• README Template

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