Wetradetogether’s Bold Vision for AI-Powered Market Analysis
Alfredo Baraldi, chief information officer of fintech startup Wetradetogether Corporation, believes the $7.5tn global trading analytics market is ripe for disruption. His company’s answer: a sophisticated AI system that models not just market data, but the entire socio-economic ecosystem driving price movements.
“Every investment decision will soon be benchmarked against digital twins of the global economy,” Baraldi says from the company’s New York offices. “Traditional technical analysis is becoming obsolete.”
The timing appears favorable. Nvidia’s latest GPU offerings have slashed computational costs by 90%, making previously prohibitive calculations accessible to retail traders. What once required a $20,000 A100 GPU can now be achieved with hardware costing between $1,000 and $2,000.
Beyond Traditional Analytics
Wetradetogether’s platform, dubbed ChronoTwin, represents a radical departure from conventional trading tools. While competitors focus on optimizing algorithms around historical price patterns and social media sentiment, Baraldi’s team is building what they call a “digital twin of the socio-economic ecosystem.”
The approach draws on three academic disciplines rarely associated with quantitative trading: behavioral economics, economic sociology, and economic anthropology.
“In 2010, during my early algorithmic trading days, I realized we were only scratching the surface,” Baraldi explains. “Ninety-nine percent of what influences markets manifests in social dynamics, geopolitical tensions, and cultural shifts long before prices move.”
The platform synchronizes real-time behavioral, sociological, and anthropological data with asset prices across equities, bonds, commodities, and safe-haven assets. Rather than seeking causal relationships, ChronoTwin takes a purely descriptive approach, mapping societal changes to market movements.
Democratizing Institutional Tools
Wetradetogether’s ambition extends beyond technical innovation. The company aims to democratize access to advanced financial analysis tools previously available only to major investment firms.
“Retail traders deserve the same interpretive capabilities for understanding both financial data and systemic environments,” Baraldi argues. “The computational power that was exclusive to Wall Street giants is now within reach.”
The company is preparing a $50m funding round to accelerate development, adopting training approaches similar to those pioneered by DeepSeek to manage computational costs.
The Mechanics of Social Prediction
ChronoTwin’s “Deep Social Learning” methodology ingests petabytes of behavioral data: transaction records, financial discussions on social platforms, demographic shifts, geopolitical events, and cultural changes. The AI learns to identify social patterns that precede market movements.
Consider the oil market during the pandemic. While traditional models focused on supply-demand dynamics and OPEC decisions, ChronoTwin tracked work-from-home patterns, evolving consumer habits, environmental sentiment shifts, and mobility discussions across social media.
“It’s like teaching a child not just to recognize words, but to understand the emotions, cultural context, and social implications behind them,” Baraldi explains. “Our AI doesn’t just see Tesla’s price rising—it understands the generational shift in sustainable mobility attitudes, amplified by specific influencers, within a context of growing post-pandemic environmental awareness.”
Risk Management Concerns
The approach raises several risk management questions. Algorithmic bias presents a primary concern—AI trained on historical behaviors could perpetuate economic discrimination. There’s also the risk of self-fulfilling prophecies if too many traders adopt similar systems, potentially destabilizing markets.
Privacy considerations loom large. Analyzing human behavior at scale requires careful navigation of data protection regulations and ethical boundaries.
“We must ensure our analysis respects privacy without manipulating behaviors,” Baraldi acknowledges.
Market Implications
If successful, ChronoTwin could fundamentally alter how markets operate. The platform promises to transform trading from a numbers game into a sophisticated analysis of human behavior and social dynamics.
The implications extend beyond returns. Baraldi envisions portfolios optimized not just for financial performance but for social, environmental, and cultural impact—a vision aligned with the growing ESG investment trend, which reached $35tn globally in 2023.
Looking Ahead
Wetradetogether’s DGX system, a desktop version of their predictive analytics platform, demonstrates the practical application of their vision. Despite appearing like standard hardware, it runs a digitized replica of global behavioral economics, correlating millions of social, cultural, and anthropological data points with market movements in real-time.
“In ten years, investing based solely on balance sheets and charts will seem primitive,” Baraldi predicts. “The question isn’t ‘Which stock will rise?’ but ‘What social changes are creating new economic opportunities?'”
For market participants, the message is clear: tomorrow’s successful traders must think like economic anthropologists, reading social and cultural signals that precede market movements.
“My generation learned to use computers for trading,” Baraldi concludes. “Today’s generation must ask: ‘How can I use artificial intelligence to better understand society and, consequently, the markets?'”
Wetradetogether Corporation is currently in late-stage development of ChronoTwin. The commercial launch is anticipated in the future, coinciding with the completion of its $50 million Series B funding round, for which the closing dates are still being finalized.
