Systems Study / Trading Infrastructure / 2026

Chronara

Algorithmic Trading Engine

Work in Progress

Chronara is a modular trading engine built for strategy research, risk-constrained backtesting, and staged paper execution. The project focuses on a shared execution path across research and live-style workflows, separating signal generation, position sizing, and stateful trade management into clear system components.

Shared Execution Core

Research and live-style modes feeding one decision core

Shared Execution Pipeline

Signal flow from enriched inputs to stateful position management

Execution Logic

_compute_exit_fill

Gap-aware exit logic distinguishes between overnight gaps and intrabar touches, producing more realistic fill behavior than naive stop-loss simulation.

core/portfolio/position_manager.py416-458

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    def _compute_exit_fill(self, pos: Dict[str, Any], bar: Dict[str, Any]) -> Tuple[Optional[float], Optional[str]]:
        """
        If OPEN gaps through level → fill at OPEN (worst side).
        Else if intrabar touch → fill at the level.
        Stop has precedence over TP.
        """
        side = pos["side"]
        stop = pos.get("stop_loss")
        tp = pos.get("take_profit")
        o = float(bar["open"])
        h = float(bar["high"])
        l = float(bar["low"])
        if side == "long":
            if stop is not None and not pd.isna(stop):
                stop = float(stop)
                if o <= stop:

Sizing Logic

_affordable_size

Position sizing accounts for opening costs before execution, preventing avoidable over-allocation at the cash boundary.

core/portfolio/position_manager.py463-471

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    def _affordable_size(self, entry_price: float, requested_size: float) -> float:
        """Cash-only affordability (includes opening fee) with a small tolerance."""
        if entry_price <= 0.0 or requested_size <= 0.0:
            return 0.0
        denom = entry_price * (1.0 + self.fee_rate)
        if denom <= 0.0:
            return 0.0
        size_cap = self.cash / denom
        return min(requested_size, max(0.0, size_cap) * (1.0 - max(self._eps_abs, self._eps_rel)))

Next Project

Flowtal