Nexus Price Predictor

Inspired by the economic vulnerabilities explored in Isaac Asimov and Robert Silverberg's 'Nightfall', where a planet's economy is dictated by a singular celestial event leading to price chaos, and the pervasive, often exploitative, consumer culture depicted in Ridley Scott's 'Blade Runner', this project, 'Nexus Price Predictor', aims to develop a machine learning model that forecasts e-commerce price changes. The core idea is to scrape historical pricing data for specific niche products (e.g., rare collectibles, specialized electronics components) from various online marketplaces. This data will be used to train a time-series forecasting model (like ARIMA or LSTM). The 'Nightfall' aspect influences the focus on predicting volatility and potential price spikes or drops due to external or cyclical factors (e.g., seasonal demand, new product releases from competitors). The 'Blade Runner' inspiration subtly guides the niche product selection towards items often associated with a futuristic, yet possibly marginalized, consumer base or those used in specialized, high-tech industries. The low-cost implementation is achieved through open-source Python libraries (like `BeautifulSoup` for scraping, `pandas` for data manipulation, and `scikit-learn` or `TensorFlow/PyTorch` for modeling) and potentially free tiers of cloud services for hosting. High earning potential arises from offering this predictive service to collectors, small businesses, and arbitrage traders who can leverage accurate price predictions for profit, by either buying low or selling high before significant market shifts occur. The niche aspect ensures a focused and manageable dataset, making individual implementation feasible.