Written by: Jeffrey Chen

Decentralized Finance (DeFi) is a term that has been used to describe financial services that are performed in decentralized blockchain markets and networks. These services often mimic traditional finance services such as lending, borrowing, and trading. However, its design allows it to be more accessible, transparent, and open than traditional finance. It also provides financial options for countries that do not have strong enough central governments to implement and enforce central financial institutions, thus, a key advantage for DeFi is its ability for widespread use. As long as one has an internet connection, by using DeFi, they will be able to have access to various financial services. In terms of transparency, because transactions are recorded on a blockchain, they can be easily audited and verified by anyone. This means that there is less risk of fraud or corruption- a significant problem found in traditional finance.

Despite the advantages, there are some setbacks that prevent DeFi from replacing traditional finance. With technology improving everyday, so are the methods used to both hack and launder money. The unregulated nature of DeFi combined with a lack of cybersecurity lead to smart contract vulnerabilities, hacks, exploits, and fraud. When dealing with important financial assets, these security vulnerabilities can often ruin and cripple portfolios.

There are various overlaps between traditional finance and DeFi- one of which being arbitrage trading bots. In traditional finance, arbitrage trading is a well established strategy that has been used by traders to make enormous profits. The underlying strategy is the exploitation of tiny differences in price between identical or similar assets in two or more markets. These arbitrage traders often buy assets in one market and sell it in another market at the same time to make profits. In DeFi, the concept is the same but instead applied to decentralized markets. However, unlike arbitrage trading in traditional markets, DeFi arbitrage trading is still relatively new with many opportunities to optimize strategies and make more profits.

The underlying strategy for arbitrage trading bots is largely the same in traditional and decentralized markets. There are often two parts associated with these bots: predictiveness and latency/bandwidth. In terms of predictiveness, both machine learning and AI strategies are employed to predict when certain commodities or assets will fall or rise. This allows for traders to be the first ones to capitalize on discrepancies in assets. Afterall, once traders buy a certain asset at a given price, the discrepancies are likely to correct itself. Models such as [write about the different models like neural network models]. The other component is the latency/bandwidth capabilities of a firm. The lower the latency and higher the bandwidth allow for companies to submit trades to the markets the fastest. Similar to the reasoning above, the faster a firm is able to submit a trade request, the more likely they are to capitalize on the discrepancies of a priced asset. For that reason, the barrier to entry for arbitrage trading requires expensive hardware. Big arbitrage trading firms often dominate certain markets simply because their hardware is better than everyone else’s and that they are able to submit trades faster to the market.