Authors:
(1) Zhenbang Feng, Department of Electrical and Computer Engineering, Viterbi College of Engineering, South University, California Los Angeles, California, USA ([email protected]);
(2) Hardik Mohanti, Department of Electrical and Computer Engineering, Viterbi College of Engineering, South University, California Los Angeles, California, USA ([email protected]);
(3) Bhaskar Krishnamachari, Department of Electrical and Computer Engineering, Viterbi College of Engineering, South University, California Los Angeles, California, USA ([email protected]).
Editor’s note: This article is part of a wider study. You read part 5 of 5. Read the rest below.
Links table
Seventh. Risk factors for stable derivatives
Stability derivatives are the stability against the fluctuations of cryptocurrencies in Defi. Although these stable fungi are designed to keep PEG with traditional currencies or goods, they face different risk factors that can shake their value.
A. Blockchain inherent
The stability and operation of applications or decentralized protocols depends largely on the basis provided by the basic Blockchain. If Blockchain faces issues such as poor performance, delayed transactions, or security violations, this affects all applications based on them. Practical example is the closure of the mirror protocol, which arose from Oracle issues on Terra Blockchain. The challenges faced by Blockchain can ripple into Defi protocols, decrease user confidence and reduce system stability.
for. Oracle
Oracles plays an important role in connecting Blockchain systems to real world data. They are responsible for providing accurate price data and ensuring an appropriate guarantee within the system. However, it is not exempt from risks. Events such as inaccuracy, unexpected regime behavior, or targeted attacks can provide wrong data. This wrong information can extinguish unjustified liquidation or other harmful system procedures.
Jim insects smart nodes or breakthroughs
Smart contracts are essential for DEFI protocol. Like other programs, they are also vulnerable to weakness. The actors are constantly looking for these security gaps in the code of the smart contract to exploit them. In the worst cases, the infrastructure attack can lead to a complete loss of decentralized assets held as a guarantee.
D. Central infrastructure failure
Although the central Defi principles are decentralized, some aspects still depend on central systems, especially in the early stages. Defi platforms sometimes tend to the central systems or institutions of operations, management and governance. Any malfunction or regulatory issues of these central parts can pose a major threat to the protocol. Problems can range from arrival barriers in specific countries, failure in the user front facades, or legal complications for the supervision institution, which can all affect the operation and expansion of the protocol.
E. Debt ceiling
Looking at the single side Dai, the roof of the debt determines the maximum amount of the Dai that can be devised for a specific guarantee, usually ETH. The creation of this limit is a strategic management plan to restrict the Dai’s offer in Defi Market. However, the complex dynamics of the Defi market can convert this into a potential risk factor for a stable derivative. When the amount of Dai -created for the individual warranty reaches the roof of the debt, the system prohibits any other generation of Dai. As a result, users are forced to get Dai exclusively from the open market. These restrictions can put up ascending on the Dai’s price, which leads to some bonding the intended amount. This position emphasizes the risk of a stable derivative price that exceeds the appointed link.
Eighth. Conclusions
We Iman teacher presented Dai Stablecoin modeling to capture the market’s feelings effectively in terms of evaluating and stability. We constructed a sporty depicting the quantitative stability mechanism for DAI in response to ETH price fluctuations. In addition, we conducted a widespread analysis of the risks of stable derivatives, studying the effect of factors such as Oracle reliability, debt ceiling, and smart nodes’ points on their stability and operation. For future research, we plan to improve the model to reduce the relationship between Dai and ETH prices and expand the model to integrate multi -equipped Dai in order to provide deeper visions of its stability and risk factors in a more diverse economic environment.
Reference
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