Financial Flows: Strategy Overview

Kpler’s Financial Flows framework is built to help market participants understand how systematic trading activity influences price behavior across global futures markets. Rather than predicting discretionary outcomes, the goal is to identify and replicate repeatable, rules-based trading behavior of large systematic managers, whose rule-driven position entry and liquidation can create persistent and observable effects on price action, volatility, and market activity.

Financial Flows applies a common set of flat price strategy frameworks to every futures contract it analyzes. These strategies are designed to reflect the primary ways systematic participants tend to engage with markets across different conditions and time horizons.

Below, we outline the baseline characteristics of the core strategies applied consistently across markets to model systematic flows:

All models are built using a unified research and implementation framework. Strategies are derived exclusively from intrinsic, price-based market data to ensure portability and consistency across markets and regimes.

At a high level, the development process follows five core stages:

This framework ensures that each strategy expresses a clear behavioral thesis while maintaining disciplined risk control and execution consistency.

Trend strategies are designed to capture persistent directional price movement. These strategies are built to identify and remain aligned with sustained trends that develop as markets transition across regimes and systematic participation reinforces directional behavior.

Market Behavior Targeted

Representative Strategy Characteristics

Trend strategies typically exhibit medium- to long-duration holding periods, with a payoff profile characterized by smaller, more frequent losses and larger average wins. Entries are designed to engage once directional persistence is established, while exits are structured to allow trends to fully develop rather than respond to short-term countertrend movement.

Mean reversion strategies are designed to take advantage of price movement beyond defined reference levels where markets exhibit a higher probability of retracement. These strategies are constructed to provide diversification to trend and value behavior while maintaining clearly defined risk during periods of directional movement.

Market Behavior Targeted

Representative Strategy Characteristics

Mean reversion strategies generally operate over short- to medium-term horizons. Trades are entered quickly following price extension and exited dynamically as markets retrace. Win/loss profiles reflect defined downside risk with asymmetric upside during successful reversion episodes.

Value strategies are designed to capture longer-horizon price normalization by identifying markets trading away from established reference levels. These strategies operate over extended holding periods and are less sensitive to short-term price fluctuations.

Market Behavior Targeted

Value strategies emphasize patience and risk calibration, allowing positions to withstand interim volatility while maintaining exposure to the broader normalization process.

Portfolio Role and Integration

Individually, each flat price strategy targets a distinct and complementary source of systematic market behavior. When combined, trend, mean reversion, and value strategies provide diversified exposure across time horizons, volatility regimes, and positioning environments.

This multi-layered structure allows Financial Flows to:

Together, these base flat price models form the foundation for Financial Flows’ broader systematic replication and market intelligence framework.