Six new strategies have been added.
Eleven new related research papers have been included into existing strategy reviews and three short free blog posts have been published during last few weeks.
Plus, five trading strategies have been backtested in QuantConnect in the previous two weeks.
Indisputably, we are witnesses of an ETF mega boom. From passive to active ETFs, their numbers seem to be ever-increasing. Since these exchange-traded funds can be excellent (accessible, transparent, liquid) instruments, it is a great necessity to examine their possible usage in active and systematic trading or investing. Therefore, the short research critically assesses the possibility of using ETFs in the Skewness Trading Strategy.
Five new strategies have been added.
Ten new related research papers have been included into existing strategy reviews and two short free blog posts have been published during last few weeks.
Plus, five trading strategies have been backtested in QuantConnect in the previous two weeks.
Eight new strategies have been added.
Ten new related research papers have been included into existing strategy reviews and three short free blog posts have been published during last few weeks.
Plus, five trading strategies have been backtested in QuantConnect in the previous two weeks.
NFTs are taking the cryptocurrency trading world by storm. NFTs stand for the non-fungible tokens which have emerged as another possible usage of blockchain technology. NFT can be used to record/verify/track the ownership of a unique – hence the non-fungible asset. Commonly, NFTs are connected with art (visual art, music, etc.), but there are also several decentralized finance or gaming-related projects.
Same as for the other blockchain-related projects, the critics are easy to find, so a research paper with hard data concerning the NFTs can be of great importance. The research paper by Mazur (2021) studies the NFT startups traded in the crypto markets. Therefore, the paper does not analyze the individual NFTs (such as some piece of art), but rather the whole projects and their tokens traded on the Binance crypto exchange.
It is indisputable that the data are changing financial markets – computing power has increased, allowing to rise the trends of ML/AI and big data (number of possible predictors or granularity) or HFT strategies. Indeed, not all the datasets are worth the time of academics, investors or traders, but we are always keen to analyze the novel and unique datasets. Of course, if we believe that the analysis is worthy of sharing, we are happy to do so. This post offers a shorter version of our newest research about Synthetic lending rates and subsequent market return. We hope that you find it enriching; enjoy the reading!
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