refactor: rename project from Predix to NexQuant

Rename all source files, scripts, tests, documentation, and configuration
from Predix/predix to NexQuant/nexquant across the entire codebase.

rdagent/components/coder/factor_coder/auto_fixer.py

@@ -1,5 +1,5 @@
 """
-Predix Factor Auto-Fixer - Automatically patches common factor code issues.
+NexQuant Factor Auto-Fixer - Automatically patches common factor code issues.
 
 This module intercepts LLM-generated factor code and automatically fixes known problems:
 1. min_periods mismatch in rolling window calculations

rdagent/components/coder/kronos_adapter.py

@@ -1,5 +1,5 @@
 """
-Kronos Foundation Model Adapter for Predix.
+Kronos Foundation Model Adapter for NexQuant.
 
 Wraps the Kronos-mini OHLCV foundation model (4.1M params, AAAI 2026, MIT)
 for use as:
@@ -55,8 +55,8 @@ def _ensure_kronos() -> bool:
     return _KRONOS_AVAILABLE
 
 
-def _ohlcv_from_predix(df: pd.DataFrame) -> pd.DataFrame:
-    """Convert Predix HDF5 format ($open/$close/...) to Kronos format (open/close/...)."""
+def _ohlcv_from_nexquant(df: pd.DataFrame) -> pd.DataFrame:
+    """Convert NexQuant HDF5 format ($open/$close/...) to Kronos format (open/close/...)."""
     col_map = {"$open": "open", "$high": "high", "$low": "low", "$close": "close", "$volume": "volume"}
     renamed = df.rename(columns=col_map)
     cols = [c for c in ["open", "high", "low", "close", "volume"] if c in renamed.columns]
@@ -253,7 +253,7 @@ def build_kronos_factor(
 
     instrument = raw.index.get_level_values("instrument").unique()[0]
     df = raw.xs(instrument, level="instrument")
-    ohlcv = _ohlcv_from_predix(df)
+    ohlcv = _ohlcv_from_nexquant(df)
 
     adapter = KronosAdapter(device=device, max_context=min(context_bars, 512), model_size=model_size)
     adapter.load()
@@ -328,7 +328,7 @@ def evaluate_kronos_model(
     raw = pd.read_hdf(hdf5_path, key="data")
     instrument = raw.index.get_level_values("instrument").unique()[0]
     df = raw.xs(instrument, level="instrument")
-    ohlcv = _ohlcv_from_predix(df)
+    ohlcv = _ohlcv_from_nexquant(df)
 
     adapter = KronosAdapter(device=device, max_context=min(context_bars, 512), model_size=model_size)
     adapter.load()

rdagent/components/coder/rl/__init__.py

@@ -1,4 +1,4 @@
-"""RL Trading Agent components for Predix.
+"""RL Trading Agent components for NexQuant.
 
 This package provides reinforcement learning trading capabilities.
 Works with or without stable-baselines3 (graceful fallback).

rdagent/components/coder/rl/agent.py

@@ -2,7 +2,7 @@
 RL Trading Agent wrapper for Stable Baselines3.
 
 Provides an easy-to-use interface for training, evaluating, and deploying
-RL trading agents within the Predix framework.
+RL trading agents within the NexQuant framework.
 
 Supported algorithms:
 - PPO: Proximal Policy Optimization (most stable, recommended for production)

rdagent/components/coder/rl/env.py

@@ -5,7 +5,7 @@ Gym-compatible environment for training RL trading agents.
 Supports single-asset (EUR/USD) trading with technical indicators
 and portfolio state as observations.
 
-Inspired by common RL trading environment patterns, implemented from scratch for Predix.
+Inspired by common RL trading environment patterns, implemented from scratch for NexQuant.
 """
 
 import gymnasium as gym

rdagent/components/coder/rl/fallback.py

@@ -2,7 +2,7 @@
 Fallback RL implementation for users without stable-baselines3.
 
 Provides simple rule-based trading when RL library is not available.
-This ensures the Predix system works for all GitHub users, even
+This ensures the NexQuant system works for all GitHub users, even
 without the optional stable-baselines3 dependency.
 
 The fallback implements a momentum-based strategy as a placeholder