Coding a hybrid model for economics project to predict stock volatility
Budget: $250 – $750 USD
Project Title: Coding a hybrid model for economics project to predict stock
We are working on a project to improve and develop a hybrid stock prediction model. Some code can be found on GitHub, and please review the attached publications for more information. Our objective is to create a model using Econometrics, especially GARCH family models and Neural network models, namely LSTM and GRU. This hybrid model will be applied to stock index datasets, running each sample separately for each index. We additionally aim to design an appealing architecture for the entire data, and the accuracy should surpass each econometrics and neural network model. Please feel free to contact me for further details.
Overview:
I am looking for a skilled developer to code a hybrid model for an economics project that focuses on predicting stock. The project requires expertise in Python programming language, experience with stock data analysis, and proficiency in machine learning modeling techniques.
Requirements:
- Proficient in Python programming language
- Strong knowledge of stock data analysis
- Experience with machine learning modeling techniques
- Familiarity with economics and financial concepts
- Ability to code a hybrid model for stock prediction
Skills and Experience:
- Strong programming skills in Python
- Experience working with stock data and databases
- Knowledge of machine learning algorithms and modeling techniques
- Understanding of economics and financial concepts
- Ability to develop a hybrid model for stock prediction using Python
If you have the relevant skills and experience, please submit your proposal with examples of similar projects you have completed. This is an exciting opportunity to contribute to an economics project and develop a hybrid model for stock prediction.
We are working on a project to improve and develop a hybrid stock prediction model. Some code can be found on GitHub, and please review the attached publications for more information. Our objective is to create a model using Econometrics, especially GARCH family models and Neural network models, namely LSTM and GRU. This hybrid model will be applied to stock index datasets, running each sample separately for each index. We additionally aim to design an appealing architecture for the entire data, and the accuracy should surpass each econometrics and neural network model. Please feel free to contact me for further details.
Overview:
I am looking for a skilled developer to code a hybrid model for an economics project that focuses on predicting stock. The project requires expertise in Python programming language, experience with stock data analysis, and proficiency in machine learning modeling techniques.
Requirements:
- Proficient in Python programming language
- Strong knowledge of stock data analysis
- Experience with machine learning modeling techniques
- Familiarity with economics and financial concepts
- Ability to code a hybrid model for stock prediction
Skills and Experience:
- Strong programming skills in Python
- Experience working with stock data and databases
- Knowledge of machine learning algorithms and modeling techniques
- Understanding of economics and financial concepts
- Ability to develop a hybrid model for stock prediction using Python
If you have the relevant skills and experience, please submit your proposal with examples of similar projects you have completed. This is an exciting opportunity to contribute to an economics project and develop a hybrid model for stock prediction.