working cva computation using quantlib

python/cvatesting/driver.py

@@ -0,0 +1,83 @@
+
+import numpy as np
+import Quantlib as ql
+
+from hullwhite import (build_calibrated_hw,simulate_hw_state,swap_npv_from_state)
+from instruments import (make_vanilla_swap,make_swaption_helpers)
+
+today = ql.Date(15, 1, 2025)
+ql.Settings.instance().evaluationDate = today
+calendar = ql.TARGET()
+day_count = ql.Actual365Fixed()
+
+
+def expected_exposure(
+    swap,
+    hw,
+    curve_handle,
+    today,
+    time_grid,
+    x_paths
+):
+    ee = np.zeros(len(time_grid))
+
+    for j, t in enumerate(time_grid):
+        values = []
+
+        for i in range(len(x_paths)):
+            v = swap_npv_from_state(
+                swap, hw, curve_handle, t, x_paths[i, j], today
+            )
+            values.append(max(v, 0.0))
+
+        ee[j] = np.mean(values)
+
+    return ee
+
+def main():
+    # Time grid
+    time_grid = np.linspace(0, 10, 121)
+
+    flat_rate = 0.02
+    curve = ql.FlatForward(today, flat_rate, day_count)
+    curve_handle = ql.YieldTermStructureHandle(curve)
+
+    #creat and calibrate HW
+    a_init = 0.05
+    sigma_init = 0.01
+    hw = ql.HullWhite(curve_handle, a_init, sigma_init)
+
+    index = ql.Euribor6M(curve_handle)
+    helpers=make_swaption_helpers(curve_handle,index,hw)
+    optimizer = ql.LevenbergMarquardt()
+    end_criteria = ql.EndCriteria(1000, 500, 1e-8, 1e-8, 1e-8)
+    hw.calibrate(helpers, optimizer, end_criteria)
+
+    a, sigma = hw.params()
+    print(f"Calibrated a     = {a:.4f}")
+    print(f"Calibrated sigma = {sigma:.4f}")
+
+
+
+    # Simulate model
+    x_paths = simulate_hw_state(
+        hw, curve_handle, time_grid, n_paths=10000
+    )
+
+    # Swap
+    swap = make_receiver_swap(
+        today, curve_handle, maturity_years=10, fixed_rate=0.025
+    )
+
+    # Exposure
+    ee = expected_exposure(
+        swap, hw, curve_handle, today, time_grid, x_paths
+    )
+
+
+
+    return 0
+
+
+if __name__ =='__main__':
+    main()