Methodology Reference · Macro Dashboards

Korea Financial Conditions Index

A weekly read on how loose or tight Korean financial conditions are — built from seven market series, reported as two complementary indices. Lower always means looser.

◄ looser (easing) neutraltighter (stress) ►

Two indices, one engine

Both indices use the same seven components, the same signs, and the same category weights. They differ in one thing only: whether each series is standardized against a fixed historical base or a rolling window.

FCI — LEVEL

Goldman-style, anchored at 100

Weighted sum of component levels, standardized on a frozen 2010s base and anchored so the base-period average = 100. Preserves secular drift.

▸ "How loose/tight vs ~20 years of history?"

FCI — MOMENTUM

Rolling 52-week z-score

Identical construction, but moments come from a trailing 52-week window. Detrended, centred near zero.

▸ "Have conditions tightened vs the last year?"

Read them together. A typical week might say "the level is historically loose, but momentum is flat" — easy conditions in absolute terms, not moving much at the margin.

Components & weights

Seven series in five categories. The sign encodes a growth-impulse convention: +1 means a higher value tightens conditions (raises the index); −1 means a higher value loosens them (lowers it).

Series	Category	Cat wt	Sub wt	Sign	Higher value →
REER (BIS broad)	FX	0.25	1.00	+1	stronger won → tighter
KOSPI trend gap (200d)	Equity	0.25	0.50	−1	above trend → looser
KOSPI realised vol (21d)	Equity	0.25	0.50	+1	higher vol → tighter
Spread AA − KTB 3Y	Credit	0.20	0.50	+1	wider → tighter
Quality spread BBB − AA	Credit	0.20	0.50	+1	wider → tighter
KTB 10Y yield	Rates	0.20	1.00	+1	higher → tighter
Resid. property YoY	Housing	0.10	1.00	−1	faster → looser

Category weights sum to 1.00; sub-weights sum to 1.00 within each category.

How it's built

1 · Sign & standardize

Each raw series is signed and standardized to zero mean, unit variance:

x_i,t = sign_i × ( X_i,t − μ_i ) / σ_i

The moments (μ, σ) are the only switch between the two indices — a frozen 2010–2019 base for the Level, a trailing 52-week window for Momentum.

2 · Category composites

Multi-series categories (Equity, Credit) are combined by sub-weight, then re-standardized to unit variance — without this step, averaging correlated sub-series shrinks the category's variance and silently under-weights it.

equity = standardize( 0.5·x_gap + 0.5·x_vol )
credit = standardize( 0.5·x_aa_ktb + 0.5·x_bbb_aa )

3 · Weight & aggregate

C_t = 0.25·FX + 0.25·Equity + 0.20·Credit + 0.20·Rates + 0.10·Housing

4 · Anchor

Level     :  FCI = 100 + (1 / SD_base(C)) × C_t
Momentum  :  FCI = C_t          (rolling moments)

This anchoring is our own scaling choice: because the deviation is divided by the composite's 2010s-base standard deviation, one index point equals one base-period SD by construction — so 97 is ~3 SD looser than the 2010s average and 103 ~3 SD tighter. It is the same SD scale the commentary uses when it cites, e.g., "−1.1 SD". Note this is not how Goldman scales its headline index (see §06). Master frequency is weekly (Friday); daily series are sampled last-obs, monthly series forward-filled with no interpolation.

Sign conventions growth-impulse

Signs follow the logic that asset-price strength is stimulative — the same framing Goldman uses. This is a deliberate choice; it makes the index a read on the growth impulse from conditions, not a froth/stress gauge.

Weak won → looser. A weaker trade-weighted won supports an export economy, so it eases conditions. (Strong won → tighter.)
Equities above trend → looser via the wealth effect and cheaper equity capital.
Equity volatility → tighter. Elevated vol signals stress — and deliberately offsets the trend gap (see §6).
Wider credit / quality spreads → tighter (costlier credit).
Higher 10Y yield → tighter (higher cost of capital).
Faster house-price growth → looser via collateral and wealth.

Flip note. Inverting the equity-gap and property signs turns this into a stress/overheating index instead — a different question that no longer tracks Goldman. Keep equity and housing signs consistent.

Reading the dashboard

FCI — Level (top): the headline. Green below 100 = looser than the 2010s norm, red above = tighter.
Category contribution (directly beneath): decomposes the current Level into its five category contributions — green easing, red tightening. This explains the chart above it.
FCI — Momentum: the rolling z-score. The shaded grey band marks the trailing 52-week window the current z is measured over.
Component tiles: each raw series over its last 52 weeks, with a signed z-badge (green easing / red tightening). The KOSPI tile shows its 52-week price gain.

Relationship to Goldman's FCI

The Level index is built on the methodology Goldman set out in Our New G10 Financial Conditions Indices (Goldman Sachs Global Economics, 2017): a weighted average of a short rate, a long-term yield, a credit spread, an equity-price variable and a trade-weighted exchange rate, with weights reflecting each variable's estimated effect on GDP growth over a one-year horizon.

This index departs from Goldman in one deliberate way: it adds a KOSPI realised-volatility overlay that Goldman's construction lacks. When an equity melt-up also spikes volatility, the Equity category nets toward neutral here rather than registering as pure easing. That is why this Level can read meaningfully less loose than the published GSKRFCI during a vol-heavy rally — the divergence localises to the equity channel by design.

Weights here are share-based and standardized, not Goldman's proprietary GDP-impact coefficients. The shapes co-move; the absolute levels are not expected to match tick-for-tick.

On units. Our Level expresses deviations in 2010s-base standard deviations (1 point = 1 SD; see §03). Goldman's headline index is instead scaled to growth impact — a one-point move corresponds to roughly one percentage point of year-ahead GDP growth — so its "points" are not standard deviations. Standardized, SD-based presentations of the GS FCI do exist (the BIS, for example, publishes it as 100 = long-run average with each unit a one-SD move), and our scale matches that convention rather than the paper's native growth-impact units.

Data & refresh

The authoritative history is a Bloomberg export. For the weekly run, the tail is extended to the latest date from free sources, level-matched onto the Bloomberg series:

KOSPI — Yahoo Finance ^KS11
REER — FRED RBKRBIS (BIS broad)
KTB 3Y/10Y, AA, BBB, CPI — Bank of Korea ECOS
Residential property — carried forward from Bloomberg (slow, monthly); base-year rebasings are chain-linked out automatically.

Published weekly, Friday morning (SGT), to Discord with an auto-generated commentary.

Caveats

Look-ahead in the Level. A frozen base avoids revision, but a full-sample base would use future data — use an expanding window if it ever feeds trading logic.
Nominal-rate drift. The 10Y enters in nominal terms, so the rates channel carries some inflation premium.
Thin BBB market. The quality spread can be distorted by a few illiquid names; a ~600bp reading is large — sanity-check it.
Property is lagged & monthly — don't over-read week-to-week housing moves.
Structural breaks (GFC, COVID, the 2025–26 melt-up) distort any fixed base and short rolling window; inspect component z-scores around these dates.

References

Goldman Sachs Global Economics. Our New G10 Financial Conditions Indices, Global Economics Analyst, 20 April 2017. gspublishing.com

Bank for International Settlements. Effective exchange rate indices (REER, broad) and residential property price statistics.

Bank of Korea. Economic Statistics System (ECOS) — market interest rates and consumer price index.