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| -rw-r--r-- | python/exploration/vcube.py | 49 |
1 files changed, 49 insertions, 0 deletions
diff --git a/python/exploration/vcube.py b/python/exploration/vcube.py new file mode 100644 index 00000000..d6d7d95f --- /dev/null +++ b/python/exploration/vcube.py @@ -0,0 +1,49 @@ +import datetime +from bbg_helpers import init_bbg_session, retrieve_data, BBG_IP +from analytics.utils import tenor_t +import pandas as pd + +spreads = [-200, -100, -50, -25, 25, 50, 100, 200] +spread_letter = {200: 'D', 100: 'C', 75: 'G', 50: 'B', 25: 'A'} + + +def ticker(expiry, tenor, spread, vol_type, source): + if spread < 0: + spread_mapping = "R" + spread_letter[abs(spread)] + else: + spread_mapping = "P" + spread_letter[abs(spread)] + if vol_type == "V": + return f"US{spread_mapping}{expiry:0>2}{tenor:0>2} {source} Curncy" + elif vol_type == "N": + return f"USS{spread_mapping}{expiry}{tenor:0>2} {source} Curncy" + +# Normal vol +# sources GFIS, CMPN +expiry = ["C", "F", 1, 2, 3, 4, 5, 7, 10, 20, 30] +tenor = [1, 2, 5, 10, 20, 30] +tickers = [] +for s in spreads: + for e in expiry: + for t in tenor: + tickers.append(ticker(e, t, s, "V", "GFIS")) + +with init_bbg_session(BBG_IP) as session: + data = retrieve_data(session, tickers, ['PX_LAST'], + start_date=datetime.date(2018, 1, 1)) + +df = pd.concat(data, axis=1) +df.columns = df.columns.droplevel(1) +col = df.columns.to_series().str.extract("US([RP])([DCGBA])(\d[0-9ACF])(\d{2})") +pos_dict = {v: k for k, v in spread_letter.items()} +neg_dict = {v: -k for k, v in spread_letter.items()} +col.loc[col[0] == 'P', 1] = col.loc[col[0] == 'P', 1].map(pos_dict) +col.loc[col[0] == 'R', 1] = col.loc[col[0] == 'R', 1].map(neg_dict) + +def to_tenor(s): + d = {'A': '1m', 'C': '3m', 'F': '6m'} + return d.get(s, s + 'yr') + +col[2] = col[2].str.lstrip("0").map(to_tenor).astype(tenor_t) +col[3] = col[3].str.lstrip("0").map(to_tenor).astype(tenor_t) +df.columns = pd.MultiIndex.from_arrays([col[1], col[2], col[3]], + names=['spread', 'expiry', 'tenor']) |