GoldPesa Option precio 

GPO

GoldPesa invests 50% of all fees in a brokerage account managed by the PAWN, a proprietary and highly intelligent trading algorithm. Profits generated by the PAWN are used to buy back and then burn GPX tokens from the market, which rewards token holders by creating demand and reducing supply at the same time. This model effectively creates earnings on an asset class (gold) that generally does not have any earnings. Based on traditional finance, by creating earnings, we can expect the market to trade GPX at some multiple of the earnings and therefore will result in GPX being traded at a premium depending on the performance of the Pawn, our proprietary and highly intelligent trading algorithm.

It's important to note that GPX token holder's gold remains unencumbered at all times as we risk our own fees/capital for the benefit of token holders, resulting in tokens which have the characteristics of a DeFi gold-backed structured product. As GPX begins to trade at a premium, the intrinsic value of the GoldPesa Option token (GPO) will also increase naturally as it is correlated to the premium of GPX.

GoldPesa is the brainchild of developer and computer engineer Shamik Raja who has extensive experience in digital signal processing, programming, commodities and quantitative science.

Between 2001 and 2006, Raja earned a degree in Electrical & Computer Engineering from the University of British Columbia in Canada. Over the years Raja has focused on research involving the application of principals in digital signal processing to create an automated commodity-buying system that uses algorithmic calculations to navigate complex international commodity and currency markets.

GoldPesa is an amalgamation of Raja’s 8 years experience in the precious metals sector combined with over 20 years experience in quantitative science and engineering.

GPO can be purchased on the GoldPesa decentralised exchange power by Uniswap (https://app.goldpesa.com/).

GoldPesa has coded an advanced dynamic liquidity protocol, using Uniswap V3. The code places liquidity in concentrated ranges which rebalance automatically based on machine learning models, resulting in steady growth, price protection and lower slippage.