Australia Super Investment Allocation History - APRA

Australia's superannuation strategic asset-allocation history from APRA, as clean per-row records - one investment option x quarter x asset sector/subsector, with benchmark allocation and currency-hedging ratio, and the fund and licensee names.

Search and current data

Question: What is Hostplus's strategic asset allocation for its Balanced option in the latest quarter?

{"funds": ["Hostplus"], "options": ["Balanced"], "fromDate": "2026-06-30", "maxRecords": 10}

Run on 30 Sep 2026 this returned 10 rows (10 × $0.05 = $0.50 on Apify's Free plan), for example:

Quarter	Option	Sector	Subsector	Benchmark %
20260630	Socially Responsible Investment (SRI) – Balanced Accumulation	Credit	Not Applicable	0
20260630	Socially Responsible Investment (SRI) – Balanced Accumulation	Fixed Income	Not Applicable	0.05
20260630	Socially Responsible Investment (SRI) – Balanced Accumulation	Equity	Not Applicable	0
20260630	Socially Responsible Investment (SRI) – Balanced Accumulation	Infrastructure	Not Applicable	0.09
20260630	Socially Responsible Investment (SRI) – Balanced Accumulation	Fixed Income	Not Applicable	0.05

Search options (all optional; a record must match every option you set, and several values in one option match any of them):

• Funds (name or ABN) (funds) — Fund (RSE) or trustee name words or the ABN, e.g. Hostplus, AustralianSuper, 68657495890.
• Investment options (name contains) (options) — e.g. Balanced, MySuper, Growth.
• Asset sectors (sectors) — e.g. Equity, Property, Infrastructure, Fixed Income, Cash.
• Quarter end from / to (fromDate, toDate) — e.g. 2025-06-30 or a year.
• Newest first (newestFirst) — reads the whole file and keeps the newest.

Always the newest file. APRA publishes these files every quarter under a new name. Until 30 Sep 2026 this actor read a fixed link to the March 2026 quarter file; it now reads APRA's publication page on every run and takes the newest file (the June 2026 quarter, published September 2026). If that page cannot be read, the run uses the last known file and says so in its status and receipt. Search options are tested on every row before the record limit. With no option set the actor returns the file's rows in order, as before.

What one record represents

The source is a single versioned CSV published by the Australian Prudential Regulation Authority (APRA) at www.apra.gov.au, downloaded directly (a keyless GET). Each record is one investment option x quarter x asset sector/subsector row: the option identifier and name, the period key, the fund (RSE) and licensee (RSL) names and RSE ABN, the consolidated and strategic sector/subsector classifications, the benchmark allocation percent and the currency-hedging ratio percent.

Sample output

Real rows from a live run of this actor (first 5 rows, selected columns).

One full record from the same run, exactly as delivered:

{
  "record_id": "83810127567-AZ49C1MySuper:20140630",
  "investment_option_identifier": "83810127567-AZ49C1MySuper",
  "time_key": "20140630",
  "investment_option_name": "Balanced Growth MySuper",
  "investment_option_type": "Multi Manager",
  "investment_option_category": "Multi Sector",
  "rse_name": "ANZ Australian Staff Superannuation Scheme",
  "rse_abn": "83810127567",
  "rsl_name": "ANZ Staff Superannuation (Australia) Pty. Limited",
  "public_offer_status": "Non-public offer",
  "consolidatedsectortype": "Fixed Income",
  "consolidatedlistingtype": "Not Applicable",
  "consolidateddomiciletype": "Australian Domicile",
  "consolidatedinternationaleconomytype": "Not Applicable",
  "investmentstrategicsectortype": "Fixed Income",
  "investmentstrategicsectorlistingtype": "Not Applicable",
  "investmentstrategicsectordomiciletype": "Australian Domicile",
  "investmentstrategicsectorinternationaleconomytype": "Not Applicable",
  "investmentstrategicsubsectortype": "Not Applicable",
  "investmentstrategicsubsectorlistingtype": "Not Applicable",
  "investmentstrategicsubsectordomiciletype": "Not Applicable",
  "investmentstrategicsubsectorinternationaleconomytype": "Not Applicable",
  "investmentbenchmarkallocationpercent": 0.09,
  "investmentcurrencyhedgingratiopercent": 0,
  "source": "Australian Prudential Regulation Authority (APRA)",
  "source_dataset": "APRA Historical Strategic Asset Allocation (SAA)",
  "licence": "Australian Prudential Regulation Authority (APRA). Published under Creative Commons Attribution 4.0 International (CC BY 4.0): free to copy, redistribute and adapt for any purpose, including commercially, with attribution to APRA and no suggestion of endorsement.",
  "attribution": "Source: APRA, licensed under CC BY 4.0",
  "caveat": "One record per investment option x quarter x asset sector/subsector from APRA's Historical Strategic Asset Allocation extract (426,917 rows): benchmark allocation percent and currency hedging ratio by strategic sector and subsector, with fund (RSE) and licensee names. Organisation-level only; no individual or contact column.",
  "observed_at": "2026-09-25T17:18:28Z"
}

Coverage and volume

Default changed on 30 Sep 2026: if you leave maxRecords out, a run now returns up to 10 records (it was 500). Set maxRecords yourself to get more — the maximum is unchanged.

The live file holds 426,917 rows (SHA-256 verified on the build). You raise Maximum records to pull the full set or lower it to sample; the Actor streams the CSV so memory stays flat regardless of how many records you request.

Person data

Every column is organisation- or product-level: fund (RSE), licensee and product identifiers and names, periods, and the numeric measures. The fund (RSE) and licensee (RSL) names are organisation names. The dataset carries no individual-person or contact column.

Licence

Australian Prudential Regulation Authority (APRA). Published under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence: you are free to copy, redistribute and adapt the material for any purpose, including commercially, provided you attribute APRA and do not suggest APRA endorses you. The attribution rides on every record.

Fields, scheduling and joins

Every field in the record is either a source-native identifier, a source-native attribute, or one of the six provenance fields (source, source_dataset, licence, attribution, caveat, observed_at) the fleet attaches to every record. Nothing is derived or inferred beyond the small, documented transforms noted above, and nothing is dropped silently - the person-handling section spells out exactly which fields are excluded and why. The grain is one record per the natural unit of the source, which keeps each row independently meaningful, keeps the key stable across runs so re-running is a cheap upsert rather than a re-import, and lets you aggregate up to whatever unit you need without unpicking a pre-joined table.

Because the source republishes on its own cadence, a scheduled run keeps a downstream table current: new and changed records upsert over the old ones on the stable key, and the observed_at stamp on every record tells you when each was last seen live. Set Maximum records low to sample the shape of the data cheaply, then raise it once the cell fits your use; the Actor streams its source, so memory stays flat regardless of how many records you request, and you are billed only for what is delivered. There is no subscription and no minimum - the per-record price and the record cap together mean the spend on any run is known in advance and matched exactly to the data you receive.

Reconciling counts honestly

Where the live count differs from any previously published figure, the live measure is the honest one and is what this listing quotes; sources re-issue and re-version their files over time, and a workbook's declared row dimension can include trailing empty rows. The run receipt always states what was actually delivered and charged and confirms the two agree, so every run is auditable against itself regardless of what any external index expected.

Integration notes

The output is a flat table of typed records, so it drops straight into whatever you already use: load the run's dataset over the API or an export, key on the record id, and upsert. A common pattern is a light scheduled run that pulls the newest slice into a staging table, then a merge on the stable key into the table your product reads, so you never re-pay for rows you already hold and your history grows cleanly over time. Because identifiers are preserved exactly as the source publishes them, joins across the fleet's cells - and onto your own systems - work without a mapping layer: the same organisation, product, option or facility id lines up on both sides. If you only need a slice, the record cap and any partition inputs bound the run precisely, so a targeted pull costs cents rather than the price of the whole set. Nothing about the record shape assumes a particular warehouse, language or tool; it is deliberately plain so the integration work is a load and a merge, not a cleaning project.

Sibling Actors

The fleet's ETF-holdings cell covers a different market and instrument (exchange-traded funds), not Australian superannuation; there is no row overlap. The two other APRA superannuation cells in this batch share this host and licence but are distinct datasets (allocation history, performance history, product/pathway structure).

Provenance and compliance

Every run reads the door host's robots.txt at runtime and records the result (URL, status, byte length and, where a policy is served, its SHA-256) in the run's RUN_RECEIPT. Where the host serves no robots policy (HTTP 404), the gate records that as a flag and proceeds on the licence, which grants re-use. The endpoint is keyless and the Actor reads only the public data door - never a per-record detail page, never a mirror, and it never bypasses a block.

Data quality and freshness

Numbers arrive as real numbers, booleans as real booleans, and every other value as a string or null, so the dataset loads without a cleaning pass. Each record is keyed on a stable source identifier, so it is safe to diff, deduplicate or upsert. Every run re-reads the live door, so the data is as fresh as the source publishes, and each record's observed_at stamp dates the snapshot. The receipt records how many rows were delivered and charged and confirms charge_equals_delivered.

Billing, delivery and joins

Pricing is per record: you are billed only for records the Actor actually delivers, and the charge is raised after each record is pushed (push-then-charge), so a failed or empty run costs nothing. The Maximum records cap bounds every run, so spend is known before you start - sample cheaply, then raise it. Every record is a flat, typed object keyed on a stable id, so it loads without a cleaning pass, diffs cleanly between runs, and upserts into a table you keep over time; re-running keeps that table current without re-paying for rows you already hold, and each receipt reconciles delivered against charged. Because the source's own identifiers are preserved verbatim, the dataset joins onto other sources keyed on the same identifier.

Who buys this, and how they use it

This cell is bought by teams that need the source's published set as a typed, keyed table they can hold and refresh rather than a page they scrape: market-intelligence and analytics teams sizing and tracking a market, data engineers wiring a clean upstream feed into a warehouse, and product teams building on a stable identifier. The grain and the key are chosen so the output is a building block, not a one-off export - you run it on a schedule, keep the delta, and join it to your other sources on the identifiers it preserves verbatim. The spend on any run is the per-record price times the records delivered, matched exactly to what you receive.