SSM-Audit Q&A Series – Currency (Question 8)

Reserves looked fine, yet the currency slid on risk-off

Question
Officially our reserves looked stable and our debt ratios were within comfort. Then a global risk-off day hit and our currency weakened quickly; forward points spiked and local yields jumped. We were “buffered” on paper—so why did it still break this fast?

Answer ✅
Buffers protect when they are calmly usable, not just large. If the composition of reserves leans on hot money, if rollover walls are near, or if intervention is lumpy, the headline can look fine while usability is fragile. SSM-Audit adds a stability band beside the FX signals you already track, so you see whether the defense is steady or brittle—before stress arrives.

What the bands would have shown 📊
• Portfolio flow share drifting from A+ to A0 / A- (more short-horizon, faster reversals)
• Short-term external debt rollover weakening to A- as maturities bunch near-term
• FX intervention smoothness sliding (A+ -> A0): same monthly total, but spikier intraday use
• Forward cover stability degrading (A0 -> A-): gaps in hedge depth when demand surges
• Onshore–offshore basis band tilting to A- / A– (stress in cross-market liquidity)
• Import-cover days steady, but hot-money share inside reserves increasing (composition shift)

What to do now 🛠️

  1. Band composition, not just level: net FDI vs portfolio flows, retail vs institutional, tenor of liabilities.
  2. Term out near walls: stagger maturities; pre-arrange contingent lines to cut rollover risk.
  3. Smooth intervention: smaller, more frequent operations; pre-signal auction windows to reduce intraday air pockets.
  4. Deepen forward markets: encourage market-making in longer tenors; align prudential limits with stability goals.
  5. Communicate cadence, not just totals: publish simple band views so markets see steadiness, not just size.

How SSM-Audit helps (practicalities) 🌟

  • No additional infrastructure: runs beside your existing FX, flow, and debt dashboards.
  • Numbers unchanged: reported metrics remain intact; stability is a read-only overlay.
  • Easy to use: spreadsheet/BI friendly; one lightweight weekly and event-week view.
  • Universal language: A++ / A+ / A0 / A- / A– aligns treasury, markets, and policy teams fast.

CLI 💻 — try our mini Calculator to identify the drift
(Mini CLI Download Page)
Feed your CSV and see bands and drift at a glance (numbers unchanged).

# Composition stability of reserves (hot-money share proxy)
ssm_audit_mini_calc fx.csv --kpi "Reserves Composition Stability" \
  --out bands_reserves_comp.csv --plot_kpi "Reserves Composition Stability" --build_id fx

# Short-term external debt rollover pressure
ssm_audit_mini_calc fx.csv --kpi "Short-Term Rollover Ratio" \
  --out bands_rollover.csv --plot_kpi "Short-Term Rollover Ratio" --build_id fx

# Portfolio flow volatility (weekly)
ssm_audit_mini_calc fx.csv --kpi "Portfolio Flow Volatility" \
  --out bands_flows.csv --plot_kpi "Portfolio Flow Volatility" --build_id fx

# FX intervention smoothness (intraday variance)
ssm_audit_mini_calc fx.csv --kpi "Intervention Smoothness" \
  --out bands_intervention.csv --plot_kpi "Intervention Smoothness" --build_id fx

# Onshore–offshore basis stability
ssm_audit_mini_calc fx.csv --kpi "Onshore-Offshore Basis" \
  --out bands_basis.csv --plot_kpi "Onshore-Offshore Basis" --build_id fx

Outputs you will get:

  • CSVs with stability bands for each timestamp (e.g., bands_rollover.csv).
  • Drift charts per KPI (--plot_kpi) showing early composition and cadence stress.
  • Optional alerts if you enable thresholds in your setup.

Technical notes

Representation: x = (m, a) with a in (-1, +1)
Collapse parity: phi((m,a)) = m
Order-invariant pooling:
  U = sum(w_i * atanh(a_i))
  W = sum(w_i)
  a_out = tanh( U / max(W, eps_w) )

Typical bands (example):
  A++: a >= 0.75
  A+:  0.50 - 0.75
  A0:  0.25 - 0.50
  A-:  0.10 - 0.25
  A--: a < 0.10

Navigation
Back: SSM-Audit Q&A Series – Markets (Question 7)
Next: SSM-Audit Q&A Series – Public Sector (Question 9)

Page disclaimer
Illustrative scenario for research and education. Observation-only; do not use for critical decisions without independent validation.