In recent years, the Transformer architecture has experienced extensive adoption in the fields of Natural Language Processing (NLP) and Natural Language Understanding (NLU). Google AI Research’s introduction of Bidirectional Encoder Representations from Transformers (BERT) in 2018 set remarkable new standards in NLP. Since then, BERT has paved the way for even more advanced and improved models.

We discussed the BERT model in our previous article. Here we would like to list alternatives for all of the readers that are considering running a project using some large language model (as we do 😀 ), would like to avoid ChatGPT, and would like to see all of the alternatives in one place. So, presented here is a compilation of the most notable alternatives to the widely recognized language model BERT, specifically designed for Natural Language Understanding (NLU) projects.

The emergence of high-frequency trading has led to improvements in numerous algorithmic trading strategies. Consequently, there is a growing demand for quantitative analysis and optimization techniques to develop these strategies. We present a paper by Aydoğan et al. (2022), which discusses the derivation of the optimal prices for HFT to execute the limit buy and sell orders where a stochastic volatility model generates the mid prices of the assets in the market.

Six new strategies have been added. Four new related research papers have been included into existing strategy reviews and one short free blog post has been published during last few weeks. Plus, six trading strategies have been backtested in QuantConnect in the previous two weeks.

Beta-adjusted returns equity factors are considerably more stable, indicating that factor construction methodologies may be improved beyond dollar and size neutrality. Low-beta effect at the level of factors confirms the existence of seasonal and momentum effects in the cross-section of factor returns. Altogether, these insights deepen the understanding of factor behavior and can aid the development of more robust factor-based investment strategies.

Hello all,

What have we accomplished in the last month?

– Extensions of 5 Quantpedia Pro reports
– 12 new Quantpedia Premium strategies have been added to our database
– 12 new related research papers have been included in existing Premium strategies during the last month
– Additionally, we have produced 7 new backtests written in QuantConnect code
– And finally, 4 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month

Six new strategies have been added. Five new related research papers have been included into existing strategy reviews and two short free blog posts has been published during last few weeks. Plus, three trading strategies have been backtested in QuantConnect in the previous two weeks.