We are excited to announce a partnership between OpenBB and Nixtla, two leading open source companies. Together, we are committed to democratizing access to state-of-the-art machine learning (ML) algorithms that up until now has only been available to a few. We envision this to allow the next generation of quants to build faster but also take full control of their own ML pipelines.
OpenBB is a well-established player in the field of open-source financial analysis, offering access to a vast range of financial data and tooling for data analysis.. They have a proven track record of delivering high-quality solutions to organizations of all sizes. Nixtla is a time series research and deployment startup that offers a set of libraries intended to make available the widest set of forecasting capabilities in a consistent and easy-to-use manner. Nixtla emphasizes standardization, performance and scalability allowing organizations to solve real-world forecasting challenges, including financial forecasting, with ease.
With this partnership, we will be able to offer a comprehensive suite of tools and solutions that will empower financial analyst. By leveraging the expertise of OpenBB and Nixtla, we will be able to provide cutting-edge solutions for financial analysis, forecasting, and modeling. What unites us is our open source nature, where we allow the community to take full control of the data pipelines and algorithms in use. This is something that has been never been open at the scale of what we are doing today.
The collaboration between OpenBB and Nixtla has successfully integrated significant features, resulting in a seamless user experience for the forecasting modules of the OpenBB terminal. Nixtla included leading statistical models for time series forecasting such as AutoARIMA, AutoETS and AutoTheta as well as a wide variety of baseline models.
As we look to the future, we are focusing on several key areas to enhance our platform.
Deep Learning for Quant Finance
One key area of focus for the partnership is including deep learning into OpenBB’s core. Deep learning is a type of machine learning that utilizes artificial neural networks to analyze and interpret data. This powerful technique allows for quick and accurate processing of large amounts of data, making it a valuable tool for financial analysis. Additionally, deep learning has the ability to learn and adapt as more data is processed, leading to continually improve performance over time.
Multivariate time series and covariates
Another important area of collaboration multivariate forecasting, which involves using multiple variables to make predictions about future outcomes. This approach can be particularly useful in the financial industry, where many variables can impact the performance of assets or portfolios. By considering multiple variables simultaneously, users can make more accurate and reliable forecasts. We are also working on incorporating covariates into our models. Covariates are variables believed to be related to the outcome being predicted and including them in models can improve the accuracy and reliability of forecasts. In the context of financial analysis, covariates can include factors such as market conditions, macroeconomic indicators, or company-specific characteristics.
Risk forecasting
Risk forecasting is another important aspect of financial planning that we are targeting. It involves identifying and analyzing potential risks that could impact an investment or financial plan and determining the best course of action to mitigate or manage those risks. This allows users to make informed decisions and take proactive steps to protect their assets. We are incorporating a variety of tools and techniques for risk forecasting including statistical analysis, scenario planning, and risk modelling.
Hierarchical Forecasting
Finally, we are also exploring the area of hierarchical portfolio forecasting, which allows users to forecast the performance of multiple portfolios at once. This is particularly useful for asset managers and other financial professionals who manage multiple portfolios.
We are excited about the possibilities that this partnership brings and look forward to bringing the power of open-source quantitative finance to organizations around the world.
Stay tuned for more updates on this partnership and the solutions we will be offering in the near future!