guardrailed-llm-agent — Step 8: The Walk-Forward Loop: Keeping It Honest (snippet 2)

step_8_the_walk_forward_loop_keeping_it__2.py

    # One continuous agent position series across the whole OOS window
    agent_parts   = []
    params_by_day = {}
    for idx, policy, guard in month_blocks:
        seg = feat_all.loc[idx]
        agent_parts.append(build_agent_positions(
            seg, policy,
            state_lag = state_lag_full.loc[idx],   # cross-month continuity
            vol_lag   = vol_lag_full.loc[idx],
        ))
        for t in idx: params_by_day[t] = guard

    agent_pos = pd.concat(agent_parts)

    # Agent-only equity
    eq_agent = equity_from_positions(feat_oos, agent_pos)

    # Guardrailed equity (continuous guardrail state: no monthly reset)
    guard_pos = apply_guardrails_oos(
        feat_oos, agent_pos, params_by_day, vol_lag_oos
    )
    eq_guard  = equity_from_positions(feat_oos, guard_pos)

    # Buy-and-hold benchmark over identical window
    eq_bh = np.exp(feat_oos['ret'].fillna(0.0).cumsum())

    return eq_agent/eq_agent.iloc[0], eq_guard/eq_guard.iloc[0], eq_bh/eq_bh.iloc[0]