Data layer
Behavioral and market-structure indicators quantify greed-fear dynamics across the yearly cycle.
Methodology
High-level model framework
Model layer
ML and pattern-recognition methods condense broad signal space into candidate turning-point windows.
Advisory layer
Portfolio managers receive clear risk-date outputs and structured hedge overlay guidance.
Turning Point Dates for Capital Protection (TP Dates CP) is a risk-management overlay designed for long-only, long-term institutional investors. The system uses machine learning, pattern recognition, and behavioural-finance metrics to distil roughly 250 trading days per year into a small set of ex-ante candidate dates on which the probability of a major market correction is elevated. These turning-point windows are identified ahead of time, are registered and non-revisable (±1 day), and are mapped to corresponding time-based price thresholds that act as support/resistance levels.
The methodology is rooted in the observation that investor greed and fear generate recurring, synchronised cyclical patterns that can be projected forward. Over more than two decades of back-testing, the approach has highlighted high-risk periods surrounding the COVID crash of 2020, the 2022 bear market, and the 2025 volatility episodes, while also providing opportunistic entry signals. The resulting overlay strategy is implemented with minimal intervention— typically via liquid futures and options—without liquidating core holdings or incurring major transaction costs.