Applied Cadence
Applied Cadence delivers cutting edge investment technology leveraging tertiary data to keep a pulse on the global markets. They provide actionable investment strategies and data covering equities and P2P lending, utilizing advanced analytics and data modeling to give investors and institutions an edge. Their services include sentiment strategies, structured market data, P2P loan analysis, and custom modeling, aimed at enhancing portfolio performance and asset diversification.
Industries
Nr. of Employees
small (1-50)
Applied Cadence
Minneapolis, Minnesota, United States, North America
Products
Modeled sentiment data feed
A cleaned, dimensionalized feed of sentiment features paired with price and volatility outcomes for tracked equities intended for use in quantitative models and strategy execution.
Distributed fixed-income loan scoring model
A loan-level scoring model that analyzes peer-to-peer loan data to identify loans with lower likelihood of default and target higher returns than aggregate platform averages.
Modeled sentiment data feed
A cleaned, dimensionalized feed of sentiment features paired with price and volatility outcomes for tracked equities intended for use in quantitative models and strategy execution.
Distributed fixed-income loan scoring model
A loan-level scoring model that analyzes peer-to-peer loan data to identify loans with lower likelihood of default and target higher returns than aggregate platform averages.
Services
Provide modeled sentiment data and pre-built long/short and volatility strategies that deliver trade signals for integration into quantitative portfolios.
Analyze peer-to-peer lending platform loan data with proprietary models to score and select loans aiming for higher risk-adjusted returns within a fixed-income allocation.
Tailored modeling engagements to adapt sentiment analytics or loan-scoring approaches to client-specific asset sets, risk tolerances, or portfolio constraints.
Provide modeled sentiment data and pre-built long/short and volatility strategies that deliver trade signals for integration into quantitative portfolios.
Analyze peer-to-peer lending platform loan data with proprietary models to score and select loans aiming for higher risk-adjusted returns within a fixed-income allocation.
Tailored modeling engagements to adapt sentiment analytics or loan-scoring approaches to client-specific asset sets, risk tolerances, or portfolio constraints.
Expertise Areas
- Sentiment-based trading strategies
- Quantitative model development
- P2P loan scoring and fixed-income portfolio modeling
- Market data engineering and feature engineering
Key Technologies
- Sentiment analysis
- Supervised machine learning models
- Time-series price and volatility modeling
- Data ingestion and ETL for heterogeneous sources