Sector Definition and Scope

A finance sector average real yield of 2.844 looks solid at first glance. The surprise is how unevenly that purchasing-power cushion is distributed once the sector is broken apart by country and security type. At one end, Bank Rakyat Indonesia posts a real yield of 11.103. At the other, Axis Bank sits at -2.789. That spread captures the core question behind real yield analysis: not just how much income a security distributes, but how much remains after local inflation erodes it.

In this sector study, Finance Pulse Research treats finance as a broad income universe that includes both listed financial stocks and real-estate vehicles classified within the finance segment of the database. The role of this sector in Asian income markets is large and varied. Banks often anchor dividend screens because they generate recurring cash distributions, while REITs extend the sector into property-linked income streams with separate valuation and payout dynamics. Readers looking for the calculation framework can review the research methodology.

The current scope covers 121 instruments across Asian markets. Of those, 45 are stocks and 76 are REITs. The stock dataset spans 10 countries: Indonesia, Thailand, China, Hong Kong, Malaysia, Singapore, South Korea, Japan, India, and Vietnam. That breadth matters because nominal yield and inflation do not move together. A 5% headline yield in one market can preserve more purchasing power than a 7% yield elsewhere. The sector therefore works as a cross-border test case for Asian dividend stocks, Asian REITs, and dividend screener workflows that distinguish nominal income from inflation-adjusted income.

Aggregate Metrics Overview

The broad finance universe combines scale with a middling inflation-adjusted payoff. Data shows 121 total instruments in the sector, but the average yields cited for the stock universe point to a more nuanced picture than a simple headline ranking would suggest.

Metric Value
Total instruments 121
Stocks 45
REIT count 76
Average nominal yield 4.76
Average real yield 2.844

Those aggregate figures reveal three things immediately. First, the sector is REIT-heavy, with 76 REITs versus 45 stocks. Second, the average nominal yield of 4.76 converts into an average real yield of 2.844, meaning inflation absorbs a noticeable share of headline income. Third, the distribution is wide. In the stock subset, nominal yields run from 0.08 to 13.27, while real yields range from -2.789 to 11.103. That is not a narrow, stable band. It is a sector where local inflation and payout policy produce sharply different outcomes.

A deeper look at the stock distribution reinforces that point. The median nominal yield is 4.31, below the 4.76 mean, while the 75th percentile reaches 5.89 and the 25th percentile falls to 2.83. On the real-yield side, the median stands at 3.166, the 75th percentile at 4.199, and the 25th percentile at 0.487. In practical analytical terms, that means a significant portion of the universe preserves purchasing power only modestly, while a smaller upper tier drives the stronger average. The standard deviation is 2.995 for nominal yield and 3.515 for real yield, which underscores dispersion rather than uniformity.

Beyond the headline numbers, comparison across sectors places finance in the middle of the field rather than at the top. The dedicated REIT sector in the comparison set shows an average nominal yield of 5.961076923076923 and an average real yield of 3.7326153846153844. Energy posts 4.839375 nominal and 3.12425 real. Consumer records 4.363846153846154 nominal and 2.169923076923077 real, while Utilities comes in at 4.12 nominal and 2.1350625 real. IT Services shows 5.182 nominal and 2.0372 real. On that basis, finance outruns Consumer, Utilities, and IT Services on average real yield, but trails both REIT and Energy.

That relative position matters for sector framing. Finance is not the strongest aggregate inflation buffer in the comparison table, yet it still contains some of the highest individual real-yield outcomes in the full set. Analysis indicates this is a selection-driven sector: averages look respectable, but the range between high- and low-purchasing-power names is unusually large. Readers using dividend safety or REIT valuation frameworks would therefore read the sector less as a uniform basket and more as a split market where country inflation, payout culture, and vehicle structure shape outcomes very differently.

Top Performers Table and Analysis

The top end of the sector is dominated by banks, not property trusts. That alone is notable in a finance universe containing 76 REITs. Ranked by nominal yield, the leading names all come from the stock side of the dataset, and they are concentrated in just four markets.

Ticker Name Country Nominal Yield Real Yield
BBRI.JK Bank Rakyat Indonesia Indonesia 13.27 11.103
KTB.BK Krung Thai Bank Thailand 11.12 9.623
601166.SS Industrial Bank China 9.06 8.823
BBL.BK Bangkok Bank Thailand 10.22 8.735
BMRI.JK Bank Mandiri Indonesia 10.62 8.504
600036.SS China Merchants Bank (A) China 7.87 7.635
SCB.BK Siam Commercial Bank Thailand 8.61 7.147
BBNI.JK Bank Negara Indonesia Indonesia 8.91 6.827
3968.HK China Merchants Bank Hong Kong 7.02 5.2
600016.SS China Minsheng Banking China 5.35 5.121

Several patterns stand out.

First, Indonesia and Thailand lead the top tier in raw yield intensity. Indonesia places Bank Rakyat Indonesia, Bank Mandiri, and Bank Negara Indonesia in the top 10. Thailand places Krung Thai Bank, Bangkok Bank, and Siam Commercial Bank. Those six entries alone account for most of the highest nominal-yield cluster. Their real yields remain elevated because local inflation is not high enough to erase the advantage. Indonesia’s inflation input for these names is 1.95, while Thailand’s is 1.366. The result is a large conversion from nominal yield into retained purchasing power.

Second, China appears in both A-share and Hong Kong listings, but the inflation context creates a different dynamic. Mainland Chinese entries benefit from a country inflation rate of 0.218 in the dataset. That low reading allows even moderate nominal yields to translate into relatively strong real yields. Industrial Bank at 9.06 nominal and 8.823 real illustrates that effect clearly. China Merchants Bank (A) at 7.87 nominal and 7.635 real shows the same pattern. China Minsheng Banking, despite a lower nominal yield of 5.35, still records a real yield of 5.121 because inflation drag remains limited.

A different pattern emerges when Hong Kong is layered into the same banking names. China Merchants Bank listed in Hong Kong shows a nominal yield of 7.02 and a real yield of 5.2. That remains high on an absolute basis, yet it sits below the mainland-listed leaders because Hong Kong inflation in the dataset is 1.73 rather than 0.218. The difference is not about the bank brand alone; it reflects how local inflation shapes the purchasing-power result.

Third, the ranking reveals that top performers are not simply those with the highest dividends. They are the names where strong distributions coincide with a manageable inflation backdrop. This is precisely the distinction highlighted in Finance Pulse Research’s real yield framework. A nominal payout can look compelling in isolation, but the data reveals which names actually preserve income value after inflation.

Zooming into the individual entries, the standout outlier is Bank Rakyat Indonesia at 13.27 nominal and 11.103 real. That combination places it well above the sector’s average nominal yield of 4.76 and average real yield of 2.844. At the same time, Krung Thai Bank at 11.12 nominal and 9.623 real confirms that the upper tail is not a one-name anomaly. Bangkok Bank at 10.22 nominal and 8.735 real, together with Bank Mandiri at 10.62 nominal and 8.504 real, forms a second cluster just below the leader.

The top 10 also highlight how little representation comes from markets such as Japan, India, South Korea, Vietnam, Singapore, or Malaysia. That absence is informative in itself. It suggests the strongest purchasing-power outcomes in finance are currently concentrated in specific banking systems rather than dispersed across the region. Readers comparing top-yield screens with country flow data or dividend aristocrats would likely note that the current winners are driven by payout magnitude and inflation arithmetic, not by broad regional balance.

Country Distribution Within Sector

The finance stock universe spans 10 countries, but the distribution is not even. China supplies the largest count, while several other markets appear only as small clusters.

Country Count
Indonesia 4
Thailand 4
China 8
Hong Kong 6
Malaysia 5
Singapore 3
South Korea 4
Japan 3
India 5
Vietnam 3

China leads with 8 stocks, followed by Hong Kong with 6. Malaysia and India each contribute 5, while Indonesia, Thailand, and South Korea each contribute 4. Singapore, Japan, and Vietnam each contribute 3. That mix reflects how finance screens in Asia often lean toward bank-heavy markets with broad listed coverage, especially in Greater China.

The picture changes at the country level when that distribution is compared with real-yield outcomes. China’s larger representation gives it more ways to populate the middle and upper ranges, while Hong Kong’s 6 names extend that Greater China footprint further. Indonesia and Thailand, despite only 4 names each, punch above their weight in the top-yield rankings. By contrast, India and Vietnam appear in the lower real-yield end of the stock dataset, where inflation exceeds nominal payouts for multiple names. Japan’s three entries are also compressed by inflation, producing one negative real yield and two near-zero results rather than a strong positive cluster.

That structure explains why country count alone does not determine purchasing-power ranking. A market can dominate representation without dominating the top of the real-yield table, and a smaller market can supply a disproportionate share of the leaders. For cross-border comparison, this is one of the clearer reminders that real yield screens need local inflation context, not just dividend frequency or headline payout size.

REITs in This Sector

The finance sector includes 76 REITs, which means property-linked income vehicles represent the majority of the tracked universe. Their analysis requires extra care because headline yield alone does not describe valuation or payout resilience. In this dataset, NAV premium/discount measures how far market price sits above or below reported net asset value, with negative values indicating a discount and positive values indicating a premium. Distribution Safety Score is a 0-100 measure where higher indicates stronger payout coverage; the values shown here are 0 or 25. Aristocrat status flags trusts with a continuous distribution record recognized by the database’s ruleset. Readers can review the broader framework in REIT methodology and NAV discount analysis.

Ticker Name Country Yield NAV Discount Safety Aristocrat?
GVREIT.BK Golden Ventures REIT Thailand 10.57 -33.67 0 No
ALLY.BK Ally Global Property Fund Thailand 9.65 -53.36 25 No
LHHOTEL.BK LH Hotel REIT Thailand 9.54 0.63 25 No
CRPU.SI Sasseur REIT Singapore 9.16 -16.67 0 No
CPNREIT.BK CPN Retail Growth REIT Thailand 8.87 5.41 0 No
5120.KL Amanahraya REIT Malaysia 8.83 -73.32 25 No
5123.KL Hektar REIT Malaysia 8.72 -38.37 0 No
5212.KL Pavilion REIT Malaysia 8.01 32.24 25 Yes
0435.HK Sunlight REIT Hong Kong 7.78 -67.16 0 No
0808.HK Prosperity REIT Hong Kong 7.77 -63.26 0 No
0405.HK Yuexiu REIT Hong Kong 7.73 -75.94 0 No
5180.KL CapitaLand Malaysia Trust Malaysia 7.62 -34.1 25 Yes
M1GU.SI Sabana Industrial REIT Singapore 7.55 -7.97 25 No
A17U.SI CapitaLand Ascendas REIT Singapore 7.47 11.8 25 No
A7RU.SI ARA Hospitality Trust Singapore 7.36 305.3 0 No
WHART.BK WHA Premium Growth REIT Thailand 7.16 2.38 0 No
AIMIRT.BK AIM Industrial Growth REIT Thailand 7.13 -6.99 0 No
UD1U.SI IREIT Global Singapore 6.92 -53.1 0 No
HMN.SI CapitaLand Ascott Trust Singapore 6.78 -23.37 25 No
0778.HK Fortune REIT Hong Kong 6.74 -59.49 0 No
0823.HK Link REIT Hong Kong 6.61 -34.66 25 No
FTREIT.BK Frasers Property Thailand REIT Thailand 6.59 5.29 25 Yes
C38U.SI CapitaLand Integrated Commercial Trust Singapore 6.57 10.23 25 No
3309.T Sekisui House REIT Japan 6.55 26.87 25 No
IMPACT.BK Impact Growth REIT Thailand 6.5 3.96 25 Yes
P40U.SI Starhill Global REIT Singapore 6.49 -23.34 25 No
8958.T Global One Real Estate Investment Japan 6.47 20.63 0 No
ME8U.SI Mapletree Industrial Trust Singapore 6.45 15 0 No
O5RU.SI AIMS APAC REIT Singapore 6.43 23.47 0 No
Q5T.SI Cromwell European REIT Singapore 6.38 -34.66 0 Yes
TS0U.SI OUE REIT Singapore 6.19 -35.71 0 No
N2IU.SI Mapletree Pan Asia Commercial Trust Singapore 6.18 -27.55 0 No
5130.KL Axis REIT Malaysia 6.08 -10.32 0 No
5116.KL Al-'Aqar Healthcare REIT Malaysia 6.05 -0.8 0 No
5109.KL Sunway REIT Malaysia 6.04 -40.07 0 No
J85.SI CDL Hospitality Trusts Singapore 6 -42.87 0 No
BUOU.SI Frasers Logistics & Commercial Trust Singapore 5.96 -10.86 0 No
M44U.SI Mapletree Logistics Trust Singapore 5.9 -3.71 0 No
K71U.SI Keppel REIT Singapore 5.83 -30.25 25 No
5227.KL IGB Commercial REIT Malaysia 5.35 104.93 25 Yes
2778.HK Champion REIT Hong Kong 5.18 -62.04 0 No
T82U.SI Suntec REIT Singapore 5.16 -27.49 0 No
8953.T Japan Retail Fund Investment Japan 5.15 -30.62 0 Yes
8972.T KDX Realty Investment Japan 5.14 -69.75 0 No
8964.T Frontier Real Estate Investment Japan 5.1 32.99 0 No
5106.KL IGB REIT Malaysia 5 18.86 25 No
3281.T GLP J-REIT Japan 4.97 43.76 0 No
8960.T United Urban Investment Japan 4.96 49.41 0 No
3295.T Hulic REIT Japan 4.95 19.2 0 No
8954.T ORIX JREIT Japan 4.92 -21.84 0 No
8961.T MORI TRUST Sogo REIT Japan 4.86 -38.11 25 No
C2PU.SI Parkway Life REIT Singapore 4.41 58.17 25 No
AJBU.SI Keppel DC REIT Singapore 4.39 37.59 25 No
8955.T Japan Prime Realty Investment Japan 4.31 -63.15 25 No
3283.T Nippon Prologis REIT Japan 4.3 50.5 0 No
5111.KL AmanahRaya-JMF Asset Malaysia 4.28 -85.19 25 No
8952.T Japan Real Estate Investment Japan 4.25 -68.09 0 Yes
8984.T Daiwa House REIT Investment Japan 4.14 -43.99 0 No
OXMU.SI Manulife US REIT Singapore 4.07 -66.1 25 No
3269.T Advance Residence (REIT) Japan 3.96 -3.46 0 Yes
8951.T Nippon Building Fund (REIT) Japan 3.75 -65.87 0 No
F34.SI Wilmar International Singapore 3.71 -15.73 25 No
1881.HK Regal REIT Hong Kong 2.29 -90.12 25 No
5127.KL KLCC Property & REITs Malaysia 1.95 -68.82 0 No
DIF.BK Digital Telecommunications Infra Fund Thailand data not available data not available 0 No
1275.HK Spring REIT Hong Kong data not available data not available 0 No
Q1P.SI Lendlease Global Commercial REIT Singapore data not available data not available 0 No
ACV.SI Far East Hospitality Trust Singapore data not available data not available 0 No
SK6U.SI Prime US REIT Singapore data not available data not available 0 No
RF7U.SI Dasin Retail Trust Singapore data not available data not available 0 No
5235.KL AmFIRST REIT Malaysia data not available data not available 0 No
CWBU.SI CapitaLand China Trust Singapore data not available data not available 0 No
RW0U.SI Mapletree North Asia Commercial Trust Singapore data not available data not available 0 No
A68U.SI Frasers Centrepoint Trust Singapore data not available data not available 0 No
J91U.SI ESR-LOGOS REIT Singapore data not available data not available 0 No
BTSGIF.BK BTS Rail Mass Transit Growth Thailand data not available data not available 0 No

Stepping back to the aggregate level, REITs bring both breadth and complexity. Thailand, Singapore, Malaysia, Hong Kong, and Japan all contribute sizable trust lineups, but the internal structure differs. Thailand shows several of the highest current yields in the table, led by Golden Ventures REIT at 10.57, Ally Global Property Fund at 9.65, and LH Hotel REIT at 9.54. Singapore contributes the deepest cluster around the 6 to 7 range, spanning industrial, retail, office, hospitality, logistics, healthcare, and data center formats. Japan’s entries skew toward mid-single-digit yields with a mix of NAV premiums and discounts.

Cross-referencing with safety metrics reveals a sharp split between high yield and payout support. Many of the highest-yield trusts carry a Distribution Safety Score of 0, while a smaller subset shows 25. That difference does not by itself settle the quality question, but it does signal that current yield alone is an incomplete read. The same applies to aristocrat status. Pavilion REIT, CapitaLand Malaysia Trust, Frasers Property Thailand REIT, Impact Growth REIT, Cromwell European REIT, IGB Commercial REIT, Japan Retail Fund Investment, Japan Real Estate Investment, and Advance Residence (REIT) are marked as aristocrats, yet their current yields span a wide range rather than clustering at the top.

That pattern breaks down when anomaly flags enter the picture. Several trusts carry explicit NAV anomalies, including Ally Global Property Fund at -53.36, Amanahraya REIT at -73.32, Sunlight REIT at -67.16, Prosperity REIT at -63.26, Yuexiu REIT at -75.94, ARA Hospitality Trust at 305.3, IREIT Global at -53.1, IGB Commercial REIT at 104.93, KDX Realty Investment at -69.75, Parkway Life REIT at 58.17, Nippon Prologis REIT at 50.5, AmanahRaya-JMF Asset at -85.19, Japan Real Estate Investment at -68.09, Manulife US REIT at -66.1, Regal REIT at -90.12, and KLCC Property & REITs at -68.82. The dataset explicitly notes that these extremes may reflect stale NAV data, illiquid markets, or structural factors. They therefore require caution rather than face-value interpretation.

The growth anomalies tell a similar story. Yuexiu REIT shows 5-year distribution growth of -30.389, Impact Growth REIT shows 36.287, Manulife US REIT shows -47.974, and Regal REIT shows -48.665. The dataset flags these as potentially influenced by one-time events or base effects. In other words, the most dramatic readings are exactly the ones that need contextual handling.

Finally, several REITs have missing current yield, NAV discount, or growth fields. Digital Telecommunications Infra Fund, Spring REIT, Lendlease Global Commercial REIT, Far East Hospitality Trust, Prime US REIT, Dasin Retail Trust, AmFIRST REIT, CapitaLand China Trust, Mapletree North Asia Commercial Trust, Frasers Centrepoint Trust, ESR-LOGOS REIT, and BTS Rail Mass Transit Growth are not yet covered for those specific fields in the current snapshot. That absence is analytically relevant because it limits direct trust-to-trust comparison inside a sector already defined by wide dispersion.

Data Sources and Methodology

This analysis uses Finance Pulse Research database snapshots dated 2026-05-06 for both real-yield and REIT fields, with fetched_at also recorded as 2026-05-06. Real yield is calculated as nominal yield adjusted for country inflation in the local market context. That approach matters in cross-border finance screens because a lower headline dividend can preserve more purchasing power than a higher nominal payout in a market with faster inflation. The detailed calculation framework is outlined in the methodology page and the dedicated real yield explainer.

The stock universe in the distribution tables contains 45 finance names, while the broader sector scope includes 121 instruments once REITs are added. REIT data includes current yield, 5-year average yield, NAV premium/discount, Distribution Safety Score, aristocrat flag, years of continuous distributions, and 5-year distribution growth when available. Missing fields are labeled as data not available rather than inferred.

Known gaps and caveats are visible in the raw dataset itself. Multiple trusts carry anomaly annotations for extreme NAV discounts, extreme NAV premiums, or extreme 5-year distribution growth figures. The dataset states these may reflect stale NAV data, illiquid markets, or structural factors. Those values are therefore presented as flagged observations, not normalized comparables. Additional background on dividend safety and REIT discounts to NAV can help frame those extremes.

Readers exploring the finance sector from adjacent angles can compare this study with the broader Asian dividend stocks database, the REIT coverage hub, and country-level foreign flows work. For screening use cases, the dividend screener and dividend aristocrats pages add continuity and payout-history context. Together, those tools help separate high nominal income from income that retains purchasing power.

This analysis is based on publicly available market data and derived metrics calculated by Finance Pulse Research. Finance Pulse Research is a data analytics publisher. Content is for informational and educational purposes only. Nothing herein constitutes investment advice, a recommendation to buy or sell any security, or an offer of any kind. Data as of 2026-05-06.