External and foreign-currency debt #

This category group contains proxy information states of external debt ratios and foreign-currency debt security ratios. Ratios are typically calculated as a percentage of GDP. They are common indicators of the vulnerability of local financial conditions to currency depreciation and tightening international funding conditions.

Note : Vintages of all the below categories as scarce, as the publishing institutions do not provide them and as markets and aggregators do not pay much attention to revisions of these statistics. For some categories we procured vintages through web archives, which meant that only vintage subsets were available. In some cases older vintages were not available and pseudo-information states were estimated for convenience.

External debt #

General government external debt to GDP ratio #

Ticker : GGIEDGDP_NSA

Label : General government external debt: % of GDP.

Definition : General government external debt, % of GDP.

Notes :

  • External debt is defined as the outstanding amount of those actual current liabilities that require payments of principal and/or interest by the debtor at some point in the future and that are owed to nonresidents by residents of a country.

  • External debt is taken from the quarterly external debt statistics of the World Bank according to the IMF’s Special Data Dissemination Standard. Vintages have been procured through a web archive of the World Bank’s debt statistics.

  • A more precise definition of external debt is observable here from the IMF and here from the World Bank. More information on external debt is present in Appendix 1

All issuers external debt to GDP ratio #

Ticker : ALLIEDGDP_NSA

Label : All issuers external debt: % of GDP.

Definition : All issuers external debt: % of GDP.

Notes :

  • All issuers is taken as the sum of debt from all issuers, including general government, central government, deposit-taking corporations (excluding central banks), other sectors and intercompany lending. External debt is defined as the outstanding amount of those actual current liabilities that require payments of principal and/or interest by the debtor at some point in the future and that are owed to nonresidents by residents of an economy.

  • External debt is taken from the quarterly external debt statistics of the World Bank according to the IMF’s Special Data Dissemination Standard.

  • More information on external debt is present in Appendix 1

  • Warning : At present JPMaQS does not have pre-2024 vintages of this category, since the IMF and World Bank have not made these available. We still have added the series for convenience as pseudo-vintages that update on release dates. Also, markets typically do not pay close attention to revisions of these data.

Foreign-currency debt securities #

General government foreign-currency debt securities #

Ticker : GGFCDSGDP_NSA

Label : General government foreign-currency debt securities: % of GDP.

Definition : General government foreign-currency debt securities: % of GDP.

Notes :

  • These are government debt securities in foreign currency which have been issued across both domestic and international markets, as per table C4 here General government includes all level of government, but just the central or federal government. Government units are unique kinds of legal entities established by political processes that exercise legislative, judicial, or executive authority over other institutional units within a given area (2008 SNA, paragraph 4.117).

  • These statistics are released at annual frequency.

  • Warning : At present JPMaQS does not have pre-2024 vintages of this category, since the IMF and World Bank have not made these available. We still have added the series for convenience as pseudo-vintages that update on release dates. Also, markets typically do not pay close attention to revisions of these data.

  • More information on foreign debt is present in Appendix 2

Central government foreign-currency debt securities #

Ticker : CGFCDSGDP_NSA

Label : Central government foreign debt securities: % of GDP.

Definition : Central government foreign debt securities: % of GDP.

Notes :

  • These are government debt securities in foreign currency which have been issued in the domestic market.

  • The political authority of central government extends over the entire territory of the country. The central government has the authority to impose taxes on all resident and nonresident units engaged in economic activities within the country. It is responsible for providing collective services for the benefit of the community as a whole. Its political responsibilities include national defense, relations with other countries, and the maintenance of law and order. It also seeks to ensure the efficient operation of the social and economic system of the country.

  • These statistics are released at annual frequency.

  • Warning : At present JPMaQS does not have pre-2024 vintages of this category, since the IMF and World Bank have not made these available. We still have added the series for convenience as pseudo-vintages that update on release dates. Also, markets typically do not pay close attention to revisions of these data.

  • More information on foreign debt is present in Appendix 2

All issuers foreign-currency debt securities #

Ticker : ALLIFGDSGDP_NSA

Label : All issuers international foreign currency debt securities: % of GDP.

Definition : All issuers international foreign currency debt securities: % of GDP.

Notes :

  • All issuers include general government, financial institutions including the central bank, and non-financial corporations.

  • These statistics are released at quarterly frequency.

  • Vintages have been procured through a web archive of the BIS debt statistics.

  • More information on foreign debt is present in Appendix 2

General government foreign-currency debt securities (international market only) #

Ticker : GGIFCDSGDP_NSA

Label : General government international foreign debt securities: % of GDP.

Definition : General government international foreign currency debt securities: % of GDP.

Notes :

  • As per the BIS definition, the general government sector can be devided into central government, state government, local government and social security.

  • These statistics are released at quarterly frequency.

  • Vintages have been procured through a web archive of the BIS debt statistics.

  • More information on foreign debt is present in Appendix 2

Financials, foreign debt to GDP ratio #

Ticker : FINIFDSGDP_NSA

Label : Financials international foreign currency debt securities: % of GDP.

Definition : Financial institutions’ international foreign currency debt securities: % of GDP.

Notes :

  • Financials are defined as the sum of private banks, public banks and financial corporations.

  • According to the BIS, the financial corporation sector consists of all resident corporations principally engaged in providing financial services to other institutional units. The production of financial services takes the form of financial intermediation, financial risk management, liquidity transformation or auxiliary financial activities.

  • Financial corporations are: money-issuing institutions, central banks, other money issuing institutions, deposit-taking corporations except the central bank, money market funds.

  • These statistics are released at quarterly frequency.

  • Vintages have been procured through a web archive of the BIS debt statistics.

  • More information on foreign debt is present in Appendix 2

Imports #

Only the standard Python data science packages and the specialized macrosynergy package are needed.

import os
import numpy as np
import pandas as pd
from pandas import Timestamp
import matplotlib.pyplot as plt
import seaborn as sns

import warnings
from datetime import timedelta, date

import macrosynergy.management as msm
import macrosynergy.panel as msp
import macrosynergy.signal as mss
import macrosynergy.pnl as msn
from macrosynergy.download import JPMaQSDownload

import requests
from timeit import default_timer as timer

warnings.simplefilter("ignore")

The JPMaQS indicators we consider are downloaded using the J.P. Morgan Dataquery API interface within the macrosynergy package. This is done by specifying ticker strings , formed by appending an indicator category code <category> to a currency area code <cross_section> . These constitute the main part of a full quantamental indicator ticker, taking the form DB(JPMAQS,<cross_section>_<category>,<info>) , where <info> denotes the time series of information for the given cross-section and category.

The following types of information are available:

  • value giving the latest available values for the indicator

  • eop_lag referring to days elapsed since the end of the observation period

  • mop_lag referring to the number of days elapsed since the mean observation period

  • grade denoting a grade of the observation, giving a metric of real time information quality.

After instantiating the JPMaQSDownload class within the macrosynergy.download module, one can use the download(tickers, start_date, metrics) method to obtain the data. Here tickers is an array of ticker strings, start_date is the first release date to be considered and metrics denotes the types of information requested.

# Cross-sections of interest

cids_dmca = ['AUD', 'CAD', 'CHF', 'GBP', 'JPY', 'NOK', 'NZD', 'SEK', 'USD']
cids_dmeu = [
    "FRF",
    "DEM",
    "ITL",
    "ESP",
]  # DM euro area sovereigns
cids_latm = [
    "BRL",
    "CLP",
    "COP",
    "MXN",
    "PEN",
]  # Latam sovereigns
cids_emea = [
    "CZK",
    "HUF",
    "ILS",
    "PLN",
    "RON",
    "ZAR",
    "TRY",
]  # EMEA sovereigns
cids_emas = [
    "CNY",
    "IDR",
    "KRW",
    "MYR",
    "PHP",
    "THB",
]  # EM Asia sovereigns

cids_dm = cids_dmca + cids_dmeu
cids_em = cids_emea + cids_latm + cids_emas

cids = cids_dm + cids_em
fordebt = ['CGFCDSGDP_NSA', 'GGFCDSGDP_NSA', 'ALLIFCDSGDP_NSA', 'FINIFDSGDP_NSA', 'GGIFCDSGDP_NSA'] 
exdebt =['ALLIEDGDP_NSA', 'GGIEDGDP_NSA']
govs = ['GB02YYLD_NSA', 'GB0SYYLD_NSA', 'GB10YYLD_NSA']
xrets = ['CDS02YXR_NSA', 'CDS05YXR_NSA', 'CDS10YXR_NSA']
xvolrets = ['CDS02YXR_VT10', 'CDS05YXR_VT10', 'CDS10YXR_VT10']
rets = ['GB02YR_NSA', 'GB05YR_NSA', 'GB10YR_NSA']
swap_rets = ['DU02YXR_VT10', 'DU05YXR_VT10', 'DU10YXR_VT10']
rir = ['REER_NSA_P1M60ML1', 'REER_NSA_P1W4WL1']
fx_rets = ['FXXR_VT10', 'FXXRUSD_VT10']
fx_vol = ['FXXRUSDxEASD_NSA']
nfdi = ['NFDIGDPRATIO_NSA_12MMA']
        
main = fordebt + exdebt 
oths = govs + xrets + xvolrets + rets + rir + swap_rets + fx_rets + fx_vol + nfdi

xcats = main + oths
# Download series from J.P. Morgan DataQuery by tickers

start_date = "1996-01-01"
tickers = [cid + "_" + xcat for cid in cids for xcat in xcats]
print(f"Maximum number of tickers is {len(tickers)}")

# Retrieve credentials

oauth_id = os.getenv("DQ_CLIENT_ID")  # Replace with own client ID
oauth_secret = os.getenv("DQ_CLIENT_SECRET")  # Replace with own secret


print(oauth_id)
print(oauth_secret)
# Download from DataQuery

with JPMaQSDownload(client_id=oauth_id, client_secret=oauth_secret) as downloader:
    start = timer()
    df = downloader.download(
        tickers=tickers,
        start_date=start_date,
        metrics=["value", "eop_lag", "mop_lag", "grading"],
        suppress_warning=True,
        show_progress=True,
    )
    end = timer()

dfd = df.copy()

print("Download time from DQ: " + str(timedelta(seconds=end - start)))
Maximum number of tickers is 868
e5qY4ZXMUQOZ0tVK
vOZ5qwYU4sZ2s6Mfteydg9wsaym6Kzpq37zj9e4jybXhe1Vxsnc0nl5ort1bg1uf4enrkdpmtrvcQjk
Downloading data from JPMaQS.
Timestamp UTC:  2024-03-12 11:27:55
Connection successful!
Requesting data:  39%|███▊      | 67/174 [00:14<00:32,  3.26it/s]
Requesting data: 100%|██████████| 174/174 [00:41<00:00,  4.15it/s]
Downloading data: 100%|██████████| 174/174 [00:26<00:00,  6.62it/s]
Some expressions are missing from the downloaded data. Check logger output for complete list.
936 out of 3472 expressions are missing. To download the catalogue of all available expressions and filter the unavailable expressions, set `get_catalogue=True` in the call to `JPMaQSDownload.download()`.
Some dates are missing from the downloaded data. 
7359 out of 7359 dates are missing.
Download time from DQ: 0:01:17.343290

Availability #

cids_exp = sorted(list(cids))  # cids expected in category panels
msm.missing_in_df(dfd, xcats=main, cids=cids_exp)
Missing xcats across df:  []
Missing cids for ALLIEDGDP_NSA:  ['SEK', 'ILS', 'PHP', 'IDR', 'CHF', 'AUD', 'MYR', 'GBP', 'JPY', 'CNY', 'FRF', 'NOK', 'ITL', 'ESP']
Missing cids for ALLIFCDSGDP_NSA:  ['PHP']
Missing cids for CGFCDSGDP_NSA:  ['PHP', 'CHF', 'NZD', 'CNY', 'GBP', 'NOK']
Missing cids for FINIFDSGDP_NSA:  ['ILS', 'PHP', 'NZD', 'CZK', 'ESP']
Missing cids for GGFCDSGDP_NSA:  ['PHP', 'CHF', 'NZD', 'CNY', 'GBP', 'NOK']
Missing cids for GGIEDGDP_NSA:  ['CHF', 'PHP']
Missing cids for GGIFCDSGDP_NSA:  ['CHF', 'PHP']

Most debt ratios are available back to the late 1990s, albeit not all are based on true vintages. Moreover, there are “blank spots” of non-reported categories for many countries and “starts”, particularly for external debt ratios.

xcatx = main
cidx = cids_exp

dfx = msm.reduce_df(dfd, xcats=xcatx, cids=cidx)
dfs = msm.check_startyears(
    dfx,
)
msm.visual_paneldates(dfs, size=(20, 4))

print("Last updated:", date.today())
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/9f8822ccff1e06bd67322feb6a879021a0e3c06418673b3cb51250f1bc20bee4.png
Last updated: 2024-03-12
xcatx = main
cidx = cids_exp

plot = msm.check_availability(
    dfd, xcats=xcatx, cids=cidx, start_size=(20, 6), start_years=False
)
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/38205bb9742333adbc78452130b7017c202d06307759da146ac261f7dcc6e5bb.png

Vintage quality is generally poor, as the source generally kep no record of unrevised data and JPMaQS had to resort to web archives or make do with estimated vintages.

xcatx = main
cidx = cids_exp

plot = msp.heatmap_grades(
    dfd,
    xcats=xcatx,
    cids=cidx,
    size=(20, 6),
    title=f"Average vintage grades from {start_date} onwards",
)
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/6d692d0c568537cf4df1faa91a74723353e4c116c5e05d3269a03a8b8154c664.png

History #

External debt ratios #

External debt ratios are slow-moving semi-structural indicators. However, they can post strong medium-term trends that may be consequential for countries’ and governments’ vulnerabilities.

xcatx = ['ALLIEDGDP_NSA', 'GGIEDGDP_NSA'] 
cidx= cids

msp.view_timelines( 
    dfd,
    xcats=xcatx,
    cids=cidx,
    start="2000-01-01",
    title="External debt ratios, % of GDP",
    title_adj=1.01,
    title_fontsize=24,
    legend_fontsize=17,
    title_xadj=0.45,
    xcat_labels=["All issuers", "General government"],
    label_adj=0.0,
    ncol=4,
    same_y=False,
    height=3,
    aspect=2,
    all_xticks=True,
)
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/79c31e1585cad18314265dd0f284c60265be235db4a5acd1e36fd5409decc83a.png

Central and general government foreign-currency debt securities #

These are slow-moving semi-structural indicators that are typically updated annually. In most cases, the central government accounts for all outstanding general government debt securities. Some countries have no foreign-currency debt securities on record for prolonged periods of time.

xcatx = ['CGFCDSGDP_NSA', 'GGFCDSGDP_NSA']
cidx = cids

msp.view_timelines( 
    dfd,
    xcats=xcatx,
    cids=cidx,
    start="2000-01-01",
    title="Government foreign-currency debt securities ratios, % of GDP",
    title_adj=1.01,
    title_fontsize=24,
    legend_fontsize=17,
    title_xadj=0.45,
    xcat_labels=["Central government", "General government"],
    label_adj=0.0,
    ncol=4,
    same_y=False,
    height=3,
    aspect=2,
    all_xticks=True,
)
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/b7f3f30be11ce823c85112be56834d073aa301083c083d8db8c364ac80ef9000.png

Financial institutions’ foreign-currency debt securities #

Information states of foreign-currency debt security ratios of financial instutions have posted strong trends and occcasional drops and drops for some countries, reflecting mainly large new issuances or redemptions of foreign-currency debt securities.

xcatx = ['FINIFDSGDP_NSA']
cidx= cids

msp.view_timelines( 
    dfd,
    xcats=xcatx,
    cids=cidx,
    start="2008-01-01",
    title="Financials foreign currency debt securities",
    title_adj=1.01,
    title_fontsize=24,
    legend_fontsize=17,
    title_xadj=0.45,
    xcat_labels= ['FINIFDSGDP_NSA'],
    label_adj=0.0,
    ncol=4,
    same_y=False,
    height=3,
    aspect=2,
    all_xticks=True,
)
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/cd3c164f3b8e4ad7adccd5f937f43db55da7bd4b95adf05d2cf609e43666375f.png

All issuers’ foreign-currency debt securities #

The “all issuers” foreign-currency debt ratios have been very different as ratios to GDP across countries, often with strong medium-term trends.

xcatx = ['ALLIFCDSGDP_NSA']

cidx = cids_exp

msp.view_timelines( 
    dfd,
    xcats=xcatx, 
    cids=cidx,
    start="2000-01-01",
    title="All issuers foreign currency debt securities, % of GDP",
    title_adj=1.01,
    title_fontsize=28,
    legend_fontsize=17,
    title_xadj=0.45,
    xcat_labels= ['ALLIFCDSGDP_NSA'],
    label_adj=0.0,
    ncol=4,
    same_y=False,
    height=3,
    aspect=2,
    all_xticks=True,
)
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/cf12a241c1f18f531edb1c3e10e40c8d051d2da3184032c3d68ec9d9160d2033.png

Importance #

Relevant research #

“Foreign currency debt is widely believed to increase risks of financial crisis… Greater ratios of foreign currency debt to total debt are associated with increased risks of currency and debt crises, although the strength of the association depends crucially on the size of a country’s reserve base and its policy credibility.” Bordo, Meissner, and Stuckler

“The external value of the local currency is counter-cyclical so that foreign currency debt requires larger repayments than local currency debt in bad states of nature. The level of foreign currency denominated debts therefore affects the volatility of aggregate demand and by extension of the exchange rate. Exchange rate volatility is in turn an important determinant of the risk premium on local currency debt.” Korinek

“A traditional argument in favor of flexible exchange rates is that they insulate output better from real shocks, because the exchange rate can adjust and stabilize demand for domestic goods through expenditure switching. This argument is weakened in models with high foreign currency debt and low exchange rate pass-through to import prices…We find that flexible exchange rates…can even amplify the output response if foreign indebtedness is high.” Towbin and Weber

Empirical clues #

Debt increases and CDS returns #

Sovereign credit default swap (CDS) returns are from JPMaQS and calculated as return on “short protection” trades, which means that we will see positive returns when CDS spreads decrease and negative returns when CDS spreads increase, as detailed here

There is modest evidence of a negative relation between increase in the general government foreign-currency debt securities ratios and subsequent 5-year CDS returns. The panel regression test does find a signficant negative relationship, with probability of this being an accidental relation. Yet, the linear correlation coefficient is very small, reflecting that ratios and returns are very heterogeneous across countries.

cidx = cids
xcatx = ['GGIFCDSGDP_NSA', 'CDS05YXR_NSA']
sdate = "2000-01-01"
# GGIFCDSGDP
#ALLIFCDSGDP
#FINIFDSGDP_NSA

cr = msp.CategoryRelations(
    dfd,
    xcats=xcatx,
    cids=cidx,
    xcat1_chg="diff",
    freq="Q",
    start=sdate,
    lag=1,
    slip=1,
    years=None,
    xcat_aggs=["last", "sum"],
)

cr.reg_scatter(
    title="Changes in government foreign currency debt securities and subsequent CDS returns", 
    labels=False,
    coef_box="lower right",
    ylab="Next-quarter 5-year sovereign CDS return", 
    xlab="Quarterly change in government foreign currency debt securities, %-points of GDP",
    prob_est="map"
)
GGIFCDSGDP_NSA misses: ['CHF', 'PHP'].
CDS05YXR_NSA misses: ['CAD'].
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/b6189c3575442ccdfb039d1c1637d9d1d9c2bff0af80136655cb68f16aad4365.png

Debt-weighted currency appreciation and CDS returns #

Sovereigns with sizeable foreign-currency liabilities will find it easier to service this debt if the local currency appreciates in real (inflation-adjusted) terms. That is because government revenues are in local currency terms. Also, standard debt-to-GDP ratios decrease as result of appreciation. There is empirical evidence of a significant positive concurrent relation between foreign-currency debt-weighted real appreciation and CDS returns.

However, there has also been a significant predictive negative relation between debt-weighted real appreciation and subsequent CDS returns at various frequencies. This could arise from reduced risk premia and negative payback for previous capital inflows and excessive borrowing or increased risk premia and positive payback for previous outflows and debt reduction.

cidx=cids
calcs = [
    "GGIFCDSGDP_FX = REER_NSA_P1M60ML1 * GGIFCDSGDP_NSA / 100",
    "ALLIFCDSGDP_FX = REER_NSA_P1M60ML1 * ALLIFCDSGDP_NSA / 100",
]

dfa = msp.panel_calculator(dfd, calcs=calcs, cids=cidx)
dfd = msm.update_df(dfd,dfa)
cidx = cids
xcatx = ['GGIFCDSGDP_FX', 'CDS05YXR_NSA']
sdate = "2000-01-01"

cr = msp.CategoryRelations(
    dfd,
    xcats=xcatx,
    cids=cidx,
    freq="Q",
    start=sdate,
    lag=1,
    slip=1,
    years=None,
    xcat_aggs=["last", "sum"],
)

cr.reg_scatter(
    title="Foreign debt-weighted real appreciation and subsequent CDS returns (24 sovereigns, since 2000)", 
    labels=False,
    coef_box="lower right",
    ylab="5-year sovereign CDS (short protection) return, % next quarter", 
    xlab="Real appreciation (versus 5 year average) times government foreign-currency debt-to-GDP ratio, end of quarter",
    prob_est="map"
)
GGIFCDSGDP_FX misses: ['CHF', 'DEM', 'ESP', 'FRF', 'ITL', 'PHP'].
CDS05YXR_NSA misses: ['CAD'].
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/f54b2a997c5b08a689973536f81bdfb98428ba09bbdcd927c37102e043f582a0.png
cidx = cids
xcatx = ['GGIFCDSGDP_FX', 'CDS05YXR_NSA']
sdate = "2000-01-01"

cr = msp.CategoryRelations(
    dfd,
    xcats=xcatx,
    cids=cidx,
    freq="A",
    start=sdate,
    lag=1,
    slip=1,
    years=None,
    xcat_aggs=["last", "sum"],
)

cr.reg_scatter(
    title="Foreign debt-weighted real appreciation and subsequent CDS returns (24 sovereigns, since 2000)", 
    labels=True,
    coef_box="lower right",
    ylab="5-year sovereign CDS (short protection) return, % next year", 
    xlab="Real appreciation (versus 5 year average) times government foreign-currency debt-to-GDP ratio, end of year",
    prob_est="map"
)
GGIFCDSGDP_FX misses: ['CHF', 'DEM', 'ESP', 'FRF', 'ITL', 'PHP'].
CDS05YXR_NSA misses: ['CAD'].
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/b2a35636456e4410f8961ab19d2afce1474ba819ab19827876cf8a975e541b2a.png

Foreign debt-weighted FX volatility and subsequent CDS returns #

High local currency FX volatility implies uncertainty of foreign-currency debt sustainability. The impact of FX volatility should be the stronger, the larger the foreign-currency debt ratios. Generally, one would expect a negative relation between (a) the change of the product of foreign-currency debt ratios and FX volatility’s normalized deviation from mean and (b) subsequent sovereign CDS returns. This negative relation is supported by empirical evidence at a monthly or quarterly frequency and for simple and vol-targeted CDS returns.

cidx = cids

dfzn = msp.make_zn_scores(
    dfd,
    xcat="FXXRUSDxEASD_NSA",
    cids=cidx,
    sequential=True,
    min_obs=261 * 3,  # minimum requirement is 3 years of daily data
    neutral="mean",
    pan_weight=0,
    thresh=3,
    postfix="_ZN",
    est_freq="w",
)

dfd = msm.update_df(dfd, dfzn)
cidx = cids
calcs = [
    "GGIFCDSGDP_FXVOLN = FXXRUSDxEASD_NSA_ZN * GGIFCDSGDP_NSA",
]

dfa = msp.panel_calculator(dfd, calcs=calcs, cids=cidx)
dfd = msm.update_df(dfd, dfa)
cidx = cids
xcatx = ['GGIFCDSGDP_FXVOLN', 'CDS05YXR_VT10']
sdate = "2000-01-01"

cr = msp.CategoryRelations(
    dfd,
    xcats=xcatx,
    cids=cidx,
    xcat1_chg="diff",
    freq="Q",
    start=sdate,
    lag=1,
    slip=1,
    years=None,
    xcat_aggs=["last", "sum"],
)

cr.reg_scatter(
    title="Foreign debt-weighted FX volatility changes and subsequent CDS returns (23 sovereigns, since 2000)", 
    labels=False,
    coef_box="lower right",
    ylab="Next quarter 5-year vol-targeted CDS return", 
    xlab="Quarterly change in foreign-currency debt-weighted normalized FX volatility",
    prob_est="map"
)
GGIFCDSGDP_FXVOLN misses: ['CHF', 'DEM', 'ESP', 'FRF', 'ITL', 'PHP', 'USD'].
CDS05YXR_VT10 misses: ['CAD'].
https://macrosynergy.com/notebooks.build/themes/macroeconomic-balance-sheets/_images/f4c16aa57d0c74a8e769155e97d997b6ef85990d0b1cab0df8d6d9fc12e635a8.png

Appendices #

Appendix 1: External debt #

External debt is defined as debt with an original maturity of more than one year that is owed by residents of the reporting country to non-residents thereof. A a broader conceptual framework of external debt by the IMF can be found here here and a debtor reporting system manual is available from the World Bank is available here .

Generally, external debt figures come from the Quarterly External Debt Statistics from the World Bank archive. The World Bank publishes this data quarterly but allows for a republishing date, usually two weeks after the first publication, which may carry revisions. Moreover, each publication may contain revisions to historical data.

As per their website, this data brings together detailed external debt data of countries that subscribe to the IMF’s Special Data Dissemination Standard (SDDS) and a selected number of countries that participate in the IMF’s General Data Dissemination System (GDDS). This standard aims to bring together under common global rules data coming from different countries and computed in different ways. More information on the QEDS can be found here

Appendix 2: Foreign-currency debt securities #

Foreign debt securities track borrowing activity in debt capital markets.

Our statistics showcase the following: international foreign currency debt by all issuers, financials and general government. In addition, we also present general government and central government debt securities where the former are issued across both domestic and international markets and the latter across domestic markets. A more detailed framework of the different sources per market is observable in table C4 here

When we talk about international debt statistics, these are concerned with debt issued outside the local market of the country where the borrower resides and thus allow to isolate securities denominated in foreign currency. They include various instruments, such as treasury bills, commercial paper, negotiable certificates of deposit, bonds, debentures and asset-backed securities (including issues conventionally known as eurobonds and foreign bonds but excluding negotiable loans).

The source for these statistics is the International debt securities (IDS) database of the Bank of International Settlements. As per their definition, foreign debt is based on the notion that “if a resident has a current liability to a nonresident that requires payments of principal and/or interest in the future, this liability represents a claim on the resources of the economy of the resident, and so is external debt of that economy. Such an approach provides a comprehensive measure of foreign debt across the range of debt instruments regardless of how they may be structured. Th focus of the definition is on gross liabilities, i.e., excluding any assets.”

Following on that description, we find that foreign debt comprises “Debt securities issued in a market other than the local market of the country where the borrower resides, i.e. issued in any market by a non-resident. IDS comprise what are conventionally known as Eurobonds and foreign bonds. In the IDS statistics, debt securities are classified as international if at least of of the following characteristics differs from the country where the borrower resides: registration domain (ISIN), listing place or governing law.”

More specifically, we take this definition and add the foreign currency filter , so our definition of foreign debt will be even more specific, i.e. the debt being in foreign currency and not in one country’s own currency.

Regarding the location of debt securities issuance, the BIS states that ‘Information on the location of issuance of debt securities issued by residents and owned by nonresidents can also be of analytical value. For instance, such data provide an indication of the motivation of debtors and creditors-whether residents are attracting foreign investors by issuing securities in their markets; and of possible liquidity risk-securities issued in international markets may be harder to refinance in the event of an external shock to the economy’, as per the External debt statistics guide

The table from which we take general government foreign debt is table C3 here https://data.bis.org/topics/IDS/tables-and-dashboards/BIS,_SEC_C3,1.0?dimensions=ISSUER_RES%3ABR

Residence principle

The BIS collates foreign debt data according to two different methodologies, residence and nationality. Nationality refers to the ultimate obligor, as opposed to the immediate borrower on a residence basis and is linked to the consolidation of assets and liabilities for related entities (corporate group approach). Information on a nationality basis is useful to analyze potential support that might be available from the parent company and to understand links between borrowers in different countries and sectors. For example, the parent bank may guarantee the debt of a Cayman Islands subsidiary of a Brazilian bank. Consistent with the approach taken in international banking statistics, the BIS bases the nationality of an issuer on the residence of its controlling parent, regardless of any intermediate owners. The characterisation is based on the residence of holder approach.

We choose, when we can, the residence approach , as the nationality approach depends on the controlling parent, while the residence approach looks at the centre of interest. The classification of international issues by nationality, instead of residence, results in a reallocation of issuance from financial centers to major economies (i.e., where owners of issuers resident in financial centers reside. [source] https://www.bis.org/publ/othp23.pdf)