Search Results for "economic"

...This makes them extremely useful for predicting stock prices. Predicting stock prices is a complex task, as it is influenced by various factors such as market trends, political events, and economic indicators. The fluctuations in stock prices are driven by the forces of supply and demand, which can be unpredictable at times. To identify patterns and trends in stock prices, deep learning techniques can be used for machine learning. Long short-term memory (LSTM) is a type of recurrent neural network (RNN) that is specifically designed for sequence modeling and prediction.

...Built on Bayesian causal inference principles, Meridian enables organizations to evaluate how different marketing channels influence key performance indicators (KPIs) such as revenue or conversions while accounting for external factors like seasonality or economic trends. The framework provides a robust foundation for constructing in-house MMM pipelines capable of handling both national and geo-level data, with built-in support for calibration using experimental data or prior knowledge. Meridian uses the No-U-Turn Sampler (NUTS) for Markov Chain Monte Carlo (MCMC) sampling to produce statistically rigorous results, and it includes GPU acceleration to significantly reduce computation time.

...Its goal is to provide a unified framework for the whole market (stock, futures, bonds, foreign exchange, digital currency, macroeconomics, etc.) for research, backtesting, forecasting, and trading. Its applicable objects include quantitative traders, teachers, and students majoring in finance, people interested in economic data, programmers, and people who like freedom and the spirit of exploration. You could write the Strategy using an event-driven or time walkway and view and analyze the performance in a uniform way.

eBarter froms trades from commitments. It measures economic values without the need of a common value standard; distributes fairly the gain produced between participants and gives the preference to trades where participants have the weakest requirements.