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.

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

Hello all,

What have we accomplished in the last month?

– A new Quantpedia Prime subscription + new Quantpedia Premium features
– 11 new Quantpedia Premium strategies have been added to our database
– 11 new related research papers have been included in existing Premium strategies during the last month
– Additionally, we have produced 8 new backtests written in QuantConnect code
– And finally, 5+2 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month

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

Hello all,

What have we accomplished in the last month?

– An extension of the Strategy Grading Quantpedia Pro report
– 10 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 8 new backtests written in QuantConnect code
– And finally, 4+1 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month

At the end of 2018, researchers at Google AI Language made a significant breakthrough in the Deep Learning community. The new technique for Natural Language Processing (NLP) called BERT (Bidirectional Encoder Representations from Transformers) was open-sourced. An incredible performance of the BERT algorithm is very impressive. BERT is probably going to be around for a long time. Therefore, it is useful to go through the basics of this remarkable part of the Deep Learning algorithm family.