diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/analytics/black.py | 22 | ||||
| -rw-r--r-- | python/analytics/option.py | 3 | ||||
| -rw-r--r-- | python/collateral_calc.py | 8 |
3 files changed, 23 insertions, 10 deletions
diff --git a/python/analytics/black.py b/python/analytics/black.py index ba9d8e96..94f91efb 100644 --- a/python/analytics/black.py +++ b/python/analytics/black.py @@ -3,13 +3,16 @@ from numba import jit, float64, boolean from scipy.stats import norm import math + def d1(F, K, sigma, T): return (log(F / K) + sigma**2 * T / 2) / (sigma * math.sqrt(T)) + def d2(F, K, sigma, T): return d1(F, K, sigma, T) - sigma * math.sqrt(T) -@jit(cache=True,nopython=True) + +@jit(cache=True, nopython=True) def d12(F, K, sigma, T): sigmaT = sigma * sqrt(T) d1 = log(F / K) / sigmaT @@ -18,27 +21,32 @@ def d12(F, K, sigma, T): d2 -= 0.5 * sigmaT return d1, d2 -@jit(float64(float64),cache=True,nopython=True) + +@jit(float64(float64), cache=True, nopython=True) def cnd_erf(d): + """ 2 * Phi where Phi is the cdf of a Normal """ RSQRT2 = 0.7071067811865475 return 1 + erf(RSQRT2 * d) -@jit(float64(float64,float64,float64,float64,boolean),cache=True,nopython=True) + +@jit(float64(float64, float64, float64, float64, boolean), cache=True, nopython=True) def black(F, K, T, sigma, payer=True): d1, d2 = d12(F, K, sigma, T) if payer: return 0.5 * (F * cnd_erf(d1) - K * cnd_erf(d2)) else: - return 0.5 * (K * cnd_erf(-d2) - F * cnd_erf(-d1)) + return 0.5 * (K * cnd_erf(-d2) - F * cnd_erf(-d1)) + -@jit(float64(float64,float64,float64,float64),cache=True,nopython=True) +@jit(float64(float64, float64, float64, float64), cache=True, nopython=True) def Nx(F, K, sigma, T): - return cnd_erf((log(F/K) - sigma**2 * T /2) / (sigma * sqrt(T))) /2 + return cnd_erf((log(F/K) - sigma**2 * T / 2) / (sigma * sqrt(T))) / 2 + def bachelier(F, K, T, sigma): """ Bachelier formula for normal dynamics need to multiply by discount factor """ - d1 = (F - K) / ( sigma * sqrt(T)) + d1 = (F - K) / (sigma * sqrt(T)) return (0.5 * (F - K) * cnd_erf(d1) + sigma * sqrt(T) * norm.pdf(d1)) diff --git a/python/analytics/option.py b/python/analytics/option.py index fbb84caf..5924fc56 100644 --- a/python/analytics/option.py +++ b/python/analytics/option.py @@ -86,7 +86,8 @@ class BlackSwaption(ForwardIndex): if rec is None: return ValueError("trade_id doesn't exist") if index is None: - index = CreditIndex(redcode=rec.security_id, maturity=rec.maturity, value_date=rec.trade_date) + index = CreditIndex(redcode=rec.security_id, maturity=rec.maturity, + value_date=rec.trade_date) index.ref = rec.index_ref instance = cls(index, rec.expiration_date, rec.strike, rec.option_type.lower(), direction="Long" if rec.buysell else "Short") diff --git a/python/collateral_calc.py b/python/collateral_calc.py index af2e49c3..9bed262d 100644 --- a/python/collateral_calc.py +++ b/python/collateral_calc.py @@ -96,6 +96,7 @@ def download_ms_emails(count=20): with open(DATA_DIR / fname, "wb") as fh: fh.write(attach.content) + def download_gs_emails(count=20): emails = get_msgs(path=["NYops", "Margin calls"], subject_filter="Regulatory VM Margin", @@ -180,15 +181,17 @@ def ms_collateral(d): r.append(["M_CSH_CASH", -collat - acc, "USD"]) return pd.DataFrame.from_records(r, columns=['Strategy', 'Amount', 'Currency']) + def load_gs_file(d, pattern): try: - fname = next( (DAILY_DIR / "GS_reports"). - glob(f"{pattern}*{d.strftime('%d_%b_%Y')}*")) + fname = next((DAILY_DIR / "GS_reports"). + glob(f"{pattern}*{d.strftime('%d_%b_%Y')}*")) except StopIteration: raise FileNotFoundError(f"GS {pattern} file not found for date {d}") df = pd.read_excel(fname, skiprows=9, skipfooter=77) return df + def gs_collateral(d): df = load_gs_file(d, "Collateral_Detail") collateral = float(df.Quantity) @@ -207,6 +210,7 @@ def gs_collateral(d): 'Currency': "USD"}, ignore_index=True) return df + def send_email(account, df_ms, df_sg, df_gs): pd.set_option('display.float_format', '{:.2f}'.format) content = HTMLBody('<html><body>' |