This is a summary of links featured on Quantocracy on Thursday, 04/02/2020. To see our most recent links, visit the Quant Mashup. Read on readers!
-
How to Predict Bitcoin Price with Deep Learning LSTM Network – Part 1 [Quant at Risk]You cant predict the future unless you have a crystal ball but you can predict an assets trading price in next time step if you have a right tool and enough confidence in your model. With the development of a new class of forecasting models employing Deep Learning neural networks, we gained new opportunities in foreseeing near future. A rebirth of Long Short Term Memory (LSTM) artificial
-
How fast should we trade? [Investment Idiocy]This is the final post in a series aimed at answering three fundamental questions in trading: How should we control risk (first post) How much risk should we take? (previous post) How fast should we trade? (this post) Understanding these questions will allow you to avoid the two main mistakes made when trading: taking on too much risk and trading too frequently. Incidentally, systematic traders
-
Volatility Expectations and Returns [Alpha Architect]A large body of research, including the 2017 study Tail Risk Mitigation with Managed Volatility Strategies by Anna Dreyer and Stefan Hubrich, demonstrates that while past returns do not predict future returns, past volatility largely predicts future near-term volatility, i.e., volatility is persistent (it clusters). High (low) volatility over the recent past tends to be followed by high