South Korea Foreign Investor Net Buying Intensity

The Korea investor-sentiment suite is a monthly, top-down Baker-Wurgler sentiment composite (KRSENT) reported alongside two companion intensity transforms, the margin-loan intensity (KRMARGIN) and the foreign net-buying intensity (KRFFLOW). KRSENT is the reduced-form, top-down gauge of Baker and Wurgler (2007), the first principal component of a panel of standardized Korean investor-demand proxies rather than a bottom-up model of any single behavior. It is published as a descriptive positioning gauge and not as a forecast.

The composite is the first principal component of the selected standardized proxies.

where $s_{j,t}$ is the business-cycle-cleaned, standardized, timing-selected proxy $j$, $w_j$ its final loading, and $N = 4$. The frozen Korean panel holds turnover, the margin-loan intensity, individual net-buying intensity, and customer-deposit growth, all investor-demand or investor-behavior measures oriented so that higher readings are more bullish (Baker and Wurgler 2006; Byun and Kim 2013).

What the Korean panel cannot contain is disclosed rather than papered over. The cleanest general proxy of Baker and Wurgler, the closed-end fund discount, is dropped permanently because Korea has no institutional closed-end equity-fund market whose discount could carry the retail-sentiment signal it carries in the United States (Lee, Shleifer, and Thaler 1991). The dividend premium and the two initial-public-offering proxies are dropped at the free-data rung, since neither the payer-nonpayer valuation panel nor the issuance ingredients are retrievable from open sources without fabrication (Baker and Wurgler 2007; Chung, Kim, and Park 2017). To hold the panel at its four-proxy floor, customer-deposit growth substitutes for the initial-public-offering count, a substitution warranted by the candidate list of Baker and Wurgler and by the Korean adaptation of Byun and Kim (2013), and the resulting panel therefore carries no firm-supply-response member and is driven entirely by investor demand and investor behavior (Stambaugh, Yu, and Yuan 2012; De Long et al. 1990).

The two companions are single-line intensity transforms with no estimation. KRMARGIN is the month-end margin-loan balance as a percent of market capitalization, a leverage-sentiment reading (Byun and Kim 2013), and KRFFLOW is the monthly foreign net-purchase flow scaled by the prior month-end capitalization, the cross-border-flow reading of the foreign-investor literature (Choe, Kho, and Stulz 1999; Richards 2005; Froot, O'Connell, and Seasholes 2001). All three series describe Korean retail and cross-border positioning rather than issuing any predictive signal (Yang 2017; Ryu, Ryu, and Yang 2020).

KRSENT follows the two-stage principal-component construction of Baker and Wurgler (2006), with the loadings, the orthogonalization, and the standardization all refit on the full pinned sample at every run.

(1) Business-cycle orthogonalization. Each raw proxy is regressed on a three-regressor Korean control set and replaced by its residual, the cleaner proxy independent of the major business-cycle effects (Baker and Wurgler 2006).

The controls are industrial-production growth, retail-sales growth standing in for the three consumption categories of Baker and Wurgler, and a reference-cycle recession indicator, the three-block mapping of the five-regressor Journal of Finance control list, with employment added only if an omitted-control probe triggers (Baker and Wurgler 2007).

(2) Standardization. Each cleaned proxy is standardized to zero mean and unit variance over the pinned sample.

(3) First-stage index. The first principal component is taken over the standardized proxies and their twelve-month lags, the one-year Baker-Wurgler lag carried to monthly data (Baker and Wurgler 2007).

(4) Lead-or-lag selection. For each proxy the contemporaneous column or its twelve-month lag is retained, whichever has the higher absolute correlation with the first-stage index, the orientation-invariant reading of the Baker-Wurgler timing rule.

(5) Final index, sign, and scale. The published index is the first principal component of the selected columns, its sign flipped so the loading vector matches the maximum number of a-priori bullish signs, with ties broken toward positive turnover and then positive margin intensity, and it is rescaled to unit variance (Baker and Wurgler 2006).

The panel retains no firm-supply-response proxy once the closed-end fund discount and the initial-public-offering proxies are dropped, so the composite is built entirely from investor-demand and investor-behavior measures (Lee, Shleifer, and Thaler 1991; Chung, Kim, and Park 2017). An uncleaned companion built from the raw proxies is published alongside the orthogonalized headline, the two being near-identical, in the manner in which Baker and Wurgler report both (Baker and Wurgler 2006). The construction is a principal-component composite rather than the return-predictive partial-least-squares sentiment index of Huang et al. (2015), which is not built here for want of an obtainable implementation and is noted only as the missing robustness companion (Bouteska, Sharif, and Abedin 2024), and its measurement lineage runs through Greenwood and Shleifer (2014) and Stambaugh, Yu, and Yuan (2012).

(6) The two companion transforms. KRMARGIN is a pure ratio with no estimation, the month-end margin-loan balance $M_t$ over the same-date month-end market capitalization.

Its numerator is a market-wide margin balance covering both the KOSPI and KOSDAQ boards while the only available capitalization is the KOSPI board alone, so the level is inflated relative to a true market-wide intensity while its dynamics remain valid, and this scope mismatch is disclosed rather than repaired by fabricating a board split (Byun and Kim 2013). KRFFLOW is likewise a pure ratio, the calendar-month sum of daily KOSPI-leg foreign net purchases $F_{[t]}$ over the prior month-end capitalization, the per-market scaling of Richards (2005).

The prior-period denominator avoids the mechanical simultaneity of scaling a flow by the capitalization the flow itself moved, and the numerator is the KOSPI leg only, with the KOSDAQ foreign-flow leg excluded and the exclusion disclosed, the scope-consistent per-market fraction of the foreign-flow literature (Choe, Kho, and Stulz 1999; Froot, O'Connell, and Seasholes 2001).

Investor sentiment matters for asset prices because a class of traders acts on beliefs unmoored from fundamentals, and the risk their mispricing imposes deters the arbitrage that would correct it. In the noise-trader account of De Long et al. (1990), correlated sentiment is itself a priced risk, and Shleifer and Vishny (1997) show why rational arbitrageurs, running other people's money under short horizons, cannot fully lean against it. Baker and Wurgler (2006) build the composite this suite adapts, and the sentiment-anomaly literature documents that a broad range of cross-sectional return anomalies concentrate in high-sentiment states (Stambaugh, Yu, and Yuan 2012; Greenwood and Shleifer 2014).

KRSENT reads this literature descriptively for Korea, a market whose retail investors trade with a directness that makes a demand-side sentiment gauge legible. The Korean sentiment literature has repeatedly tied retail trading, turnover, and margin leverage to speculative episodes (Byun and Kim 2013; Yang 2017; Ryu, Ryu, and Yang 2020; Yang and Ryu 2021). The composite tracks that chronology. It rises to its sample maximum of +4.0616 standard deviations in January 2022, at the crest of the 동학개미 retail surge that carried unprecedented household participation into the market through 2020 and 2021, and it sits at its sample minimum of −0.31 in March 2020, at the pandemic-shock low from which that surge began (Choe, Kho, and Stulz 1999).

KRSENT is not a restatement of consumer confidence. Its correlation with the Bank of Korea consumer-sentiment survey is −0.078, so it measures a different object, namely the positioning revealed in the trades of investors rather than the mood reported in a household survey (Baker and Wurgler 2007). The honest use of the series is as a description of where Korean retail and cross-border positioning sit relative to their own history, and no return-predictive reading is asserted for it here, a scope the statistical testing sets out in full (Lee, Shleifer, and Thaler 1991; Park 2024).

For a markets desk the suite is a positioning and monitoring panel, not a trading signal. KRSENT summarizes how stretched Korean retail demand is relative to its own history, and the two companions decompose the reading. KRMARGIN reads the leverage channel, the margin-loan balance investors have borrowed against their positions, which the Korean evidence links to the speculative phase of the cycle (Byun and Kim 2013). KRFFLOW reads the cross-border channel, foreign net buying scaled to market size, whose persistence and contemporaneous relation to returns the foreign-flow literature has mapped in detail (Choe, Kho, and Stulz 1999; Richards 2005; Froot, O'Connell, and Seasholes 2001).

The framing the gauge licenses is historical accompaniment, not prediction. Elevated sentiment has accompanied the episodes the composite dates, and a reading near the top of its range flags positioning the market has reached before, which is surveillance information rather than a contrarian entry signal. The limits-to-arbitrage tradition is the reason for that caution, since sentiment can stay stretched and grow more stretched for long stretches, so leaning against it is itself risky (Shleifer and Vishny 1997; De Long et al. 1990; Greenwood and Shleifer 2014), and no return-predictive reading is claimed for the composite here (Stambaugh, Yu, and Yuan 2012).

The series are best read together and against the other gauges of this platform. A high KRSENT driven mainly by KRMARGIN is a leverage-led advance, while one driven by KRFFLOW is a foreign-flow-led advance, and the two have different unwinds (Baker and Wurgler 2006; Byun and Kim 2013). Because the composite is a full-sample construction whose history revises, cross-period level comparisons are approximate, and the companions, being raw ratios, are the more stable cross-period reads (Baker and Wurgler 2007; Yang and Ryu 2021).

KRFFLOW is a monthly foreign net-purchase flow intensity, the calendar-month sum of daily KOSPI-leg foreign net purchases over the prior month-end KOSPI capitalization, a pure transform with no estimation. It is a sign-varying, theoretically mean-reverting flow object, so the unit-root triplet is run on the level, and its stationarity is a genuine empirical claim rather than a construction artifact, since the numerator is a raw transaction-flow sum and the denominator a predetermined capitalization reading, with no stationarity-manufacturing filter between them (Hamilton 2018). Being an unbounded, sign-varying intensity, it also gives the regulated-process mechanism nothing to regulate against, so the bounded-support exclusion does not apply (Cavaliere 2005).

Over 282 months from 2003-02 to 2026-07 the level is cleanly integrated of order zero. The augmented Dickey-Fuller and Phillips-Perron tests both reject a unit root at p = 0.000, and the KPSS test does not reject stationarity at p > 0.10, so the three procedures agree and a clean I(0) verdict is assigned (Said and Dickey 1984; Phillips and Perron 1988; Kwiatkowski et al. 1992). The first-order autocorrelation of the level is 0.48688 with an implied half-life of about 0.96 months, a descriptive persistence summary consistent with a fast-mean-reverting flow. The flow is serially dependent within its stationary support, the Ljung and Box (1978) portmanteau on the level rejecting white noise at lags 12 and 24, Q = 174.488 and Q = 182.956 at p = 0.000 and p = 0.000, and the automatic portmanteau of Escanciano and Lobato (2009) likewise rejecting at 88.886 with p = 0.000, the mandated companion because monthly flow intensities are conditionally heteroskedastic across the flight episodes where the plain portmanteau over-rejects.

The mean is stable in level. The Bai and Perron (1998) procedure, by the Bai and Perron (2003) algorithm, finds no break in the mean of the level (Perron 1989), while the Andrews (1993) sup-Wald statistic of 9.621 exceeds its five-percent critical value of 8.68 and rejects parameter constancy at a single unknown date, and reported honestly the single-break test flags a candidate the information-criterion partition does not retain, so no break date is assigned. The series is a monthly flow intensity with no posited seasonal quantity, so the seasonal-unit-root and seasonal-stationarity tests are not applicable and are not run (Hylleberg et al. 1990; Canova and Hansen 1995; Ghysels and Osborn 2001).

The published intensity is the KOSPI leg only, over the prior month-end KOSPI capitalization, the scope-consistent per-market fraction, and the KOSDAQ foreign-flow leg is excluded and the exclusion disclosed, since the anchor scales the flow of each market by the own capitalization of that market and the free KOSDAQ capitalization needed for a clean KOSDAQ fraction is absent (Richards 2005). The prior-period denominator is the convention of the anchor for avoiding the mechanical simultaneity of scaling a flow by the capitalization it moved.