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Here are ten unsolved problems in algorithmic trading framed within a pure mathematics context:
1. **Optimal Execution Problem**: Finding a universally optimal strategy for executing large orders t…
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## Main Objectives
DeFi offers a wealth of trading opportunities, but monitoring positions and managing risks can be overwhelming, especially during market volatility. This project invites participant…
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Hi,
Thank you for your sharing, it is very good tutorial for us to learn how to predict stock price with LSTM method. I tested the SP500 data with lstm = 128 and epoch =500, but the result is not so…
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**Github username:** @Rassska
**Twitter username:** m_Rassska
**Submission hash (on-chain):** 0x95b8b57b0bd879a451debd8d4e1fe92743a8ff3f052cc44bab800a3355d7ee43
**Severity:** medium
**Description:**…
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The scoring rule in "Beat the house" is, by default, more expensive than previous alternatives. One way to mitigate this would be by:
- Giving enough expected reward for one or a few teams or indiv…
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The current my market view on Omen is not sufficient for keeping track of market cr…
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Research and develop a voting mechanism to choose what prediction to use in the overall framework
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### Prizes
First place team: 2000 DAI
Second place team: 1000 DAI
### Challenge
At Gnosis we have developed an open-source [conditional token framework](https://docs.gnosis.io/conditionaltok…
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Hi, Boris
I am amazing for your results for stock market modelling and prediction using advanced techniques such as GAN, LSTM, CNN.
Might you send me full code to reproduce your result on my sid…
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- Abstract (2-3 lines)
Predicting the behaviour of stock market is always an area of interest for researchers. With the advancement in techniques of machine learning and neural networks, it has sta…