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Two mutual funds can disclose some of the same investments. A useful overlap workflow first checks whether the rows describe the same securities at the same reporting date and on the same percentage basis. Matching a company name alone can join different instruments and create a misleading result.
This guide extends a single-fund holdings table into a careful comparison built in your application. Fictional funds, securities and mappings provide a complete worked example. The calculation measures overlap observed in the supplied rows; it does not claim complete portfolios or a published holdings-comparison API.
The useful part, upfront.
- Align report_date, fund scope and percentage denominator before matching holdings.
- Canonical security and issuer mappings in this workflow belong to your application.
- Top-holdings lists can support observed overlap without establishing full-portfolio overlap.
Select a shared reporting period and a compatible holdings scope#
Discover the two funds through their canonical registry records, then identify a shared available FMR report_date. Fetch explicit-period complete reports with holdings and source expansions. Two independent latest requests can select different months, so latest is unsuitable as an implicit comparison rule.
Keep fund, plan and sub-fund scope consistent. A plan’s investments should not be merged with an umbrella fund’s disclosures without evidence that they describe the same portfolio. Retain holding_group, is_top_holding and the original rank to understand what the selected list represents.
The MUFAP template describes top-holdings disclosures and their percentage basis. A top list can be useful without being an exhaustive security inventory. Establish that scope before interpreting missing names, and avoid treating one fund’s longer disclosed list as evidence of greater diversification.
References: ILovePSX public API reference · MUFAP standardized Fund Manager Report template
Resolve securities before aggregating by issuer#
A holding row can contain issuer_name_raw, security_name_raw, symbol_raw, instrument_type_raw, maturity_date and other descriptive fields. The public holding model does not supply a canonical security_id or issuer_id. Any verified mapping used in this comparison must therefore be separately owned, documented and reviewed by your application.
Security-level matching asks whether two rows refer to the same instrument. Issuer-level matching asks whether instruments belong to the same issuing entity. Ordinary shares, a bond and another maturity from one issuer should not become one security merely because the issuer name matches. For example, two fictional bonds from Example Commercial Bank with different maturities remain separate securities, even if a reviewed issuer view later aggregates their exposure. Preserve both levels so the comparison question stays explicit.
Official PSX procedures distinguish security symbols and identification setup in the market infrastructure. Use authoritative identity evidence where applicable, together with the original disclosure. A fuzzy spelling match can propose a candidate for review; it should not silently certify a security identity.
References: ILovePSX public API reference · PSX joint procedures: government-security identification and setup
Keep API fields and application mappings separate#
The synthetic table uses application-owned keys beginning with mock:. They are deliberately fictional and not UUID fields returned by the holdings API. The raw holding names remain available so the mapping can be inspected rather than replacing the source text entirely.
The invented mapping says the two technology names refer to the same ordinary-share security, and the two fertilizer names refer to another. Their issuers also have separate invented keys. Example Commercial Bank and Example Cement Company have no shared security in the supplied rows.
For production, store mapping status, evidence, reviewer or deterministic matching rule, and its version. Do not put an unresolved candidate into the matched total. A future correction to identity should trigger a reproducible recomputation rather than silently changing a cached comparison.
| Raw fictional holding | Application security key | Application issuer key | Mock status |
|---|---|---|---|
| Example Technology Company | mock:technology-ordinary | mock:technology-issuer | Verified for this teaching example |
| Example Technology Ordinary Shares | mock:technology-ordinary | mock:technology-issuer | Verified for this teaching example |
| Example Fertilizer Company | mock:fertilizer-ordinary | mock:fertilizer-issuer | Verified for this teaching example |
| Example Commercial Bank | mock:bank-ordinary | mock:bank-issuer | Verified for this teaching example |
| Example Cement Company | mock:cement-ordinary | mock:cement-issuer | Verified for this teaching example |
Work with compatible weights without normalizing a partial list#
Both fictional funds report these selected top-three rows as percentages of total assets at 30 September 2026. Alpha’s supplied rows total 38%; Beta’s total 32%. The remaining portfolio is not specified. Each row’s percentage keeps the whole-fund denominator instead of being normalized to a top-list denominator.
For the technology security, the smaller disclosed weight is 10%. For the fertilizer security it is 12%. Adding those minima gives 22 percentage points of observed matched weight under this example’s definition. The bank and cement rows are unshared among the supplied records, not proven absent from the other complete portfolio.
Do not relabel 22 as the percentage of securities held in common, or divide it by 38 and present it as full-portfolio overlap. Count-based overlap, issuer exposure and matched portfolio weight are different measures. Name the calculation you actually performed.
| Mock security at 2026-09-30 | Alpha: % total assets | Beta: % total assets | Observed minimum |
|---|---|---|---|
| Example Technology ordinary shares | 18.000000 | 10.000000 | 10.000000 |
| Example Fertilizer ordinary shares | 12.000000 | 15.000000 | 12.000000 |
| Example Bank ordinary shares | 8.000000 | Not in supplied rows | Unresolved outside the observed intersection |
| Example Cement ordinary shares | Not in supplied rows | 7.000000 | Unresolved outside the observed intersection |
| Supplied row total | 38.000000 | 32.000000 | Matched sum: 22.000000 |
Check the worked overlap with exact decimal arithmetic#
The code receives already reviewed application mappings and explicitly compatible context. It rejects duplicate mapped keys rather than adding them blindly. That protects this small example from duplicate extraction rows or accidental mixing of two holding groups.
In a larger application, legitimate multiple positions might require deliberate aggregation by security. Establish which rows can be summed, their scope and evidence before doing so. The example intentionally keeps that decision outside the arithmetic function instead of hiding it behind an automatic name-based groupby.
from decimal import Decimal
context_a = ("2026-09-30", "percent_of_total_assets", "top-three illustrative shares")
context_b = context_a
alpha = [("mock:technology-ordinary", "18"), ("mock:fertilizer-ordinary", "12"), ("mock:bank-ordinary", "8")]
beta = [("mock:technology-ordinary", "10"), ("mock:fertilizer-ordinary", "15"), ("mock:cement-ordinary", "7")]
def reviewed_weights(rows):
values = {}
for security_key, weight_string in rows:
if security_key in values or weight_string is None:
raise ValueError("Duplicate or unavailable mapped weight")
weight = Decimal(weight_string)
if not weight.is_finite() or not Decimal(0) <= weight <= Decimal(100):
raise ValueError("Invalid illustrative weight")
values[security_key] = weight
return values
assert context_a == context_b
left, right = reviewed_weights(alpha), reviewed_weights(beta)
shared = left.keys() & right.keys()
observed = sum((min(left[key], right[key]) for key in shared), Decimal(0))
assert sum(left.values()) == Decimal(38)
assert sum(right.values()) == Decimal(32)
assert observed == Decimal(22)
print(f"Synthetic observed matched weight: {observed} percentage points")References: Python Decimal: exact decimal inputs and arithmetic
Keep unresolved names and unknown portfolio regions visible#
A missing name in a top list is not evidence of zero exposure. Report the observed intersection, the supplied-list totals and the unresolved mapping count separately. This tells readers how much of the disclosed input was actually usable without making up the remainder.
Changing the denominator also changes the question. percent_of_total_assets, percent_of_net_assets and percent_held should never flow into one total without a justified conversion. A value_amount or market_value can support another calculation only if the corresponding asset base and date are established.
Issuer exposure may be a useful additional view, but it needs its own definition and verified issuer grouping. Do not present it as security-level overlap. Likewise, a shared holding does not establish correlated returns or prove that two funds are interchangeable investments.
References: ILovePSX public API reference
Present a comparison with its evidence and limits#
Place the shared date and percentage basis above the table. Show raw holding labels, matched security labels and individual fund weights together. Include original ranks as context, but do not imply that the rank numbers themselves are comparable weight measures.
Preserve report IDs, source pages, returned versions and mapping versions in your export manifest. If a report or mapping is corrected, keep the earlier result traceable and regenerate the affected calculation. Your user can then understand whether a changed result reflects a new month, a source correction or a mapping fix.
For an AI answer, supply the observed matched weight, input scope, unknown remainder and unresolved identities in readable text. Link to the source evidence and explicitly label application calculations. That gives the assistant enough context to explain the comparison without inventing a full holdings inventory or a diversification verdict.
References: ILovePSX public API reference
Try a complete example.
Use these fictional records to prototype a full fund view: profile, reported returns, holdings, asset and sector allocations, credit quality, fees and ratings. Every name, identifier and number is invented. This is educational mock data, with no connection to a real fund, source document or agency opinion.
The JSON mirrors the public response structure. The complete FMR example includes all supported expansions; empty arrays and nulls demonstrate valid missing-data states. Your live integration must still request the sections it needs and check the returned coverage.
Inspect the complete FMR model
{
"success": true,
"data": {
"id": "00000000-0000-4000-8000-000000000101",
"report_ids": [
"00000000-0000-4000-8000-000000000101"
],
"fund": {
"id": "00000000-0000-4000-8000-000000000201",
"slug": "example-research-fund",
"name": "Example Research Fund",
"mufap_fund_id": null,
"amc": {
"id": "00000000-0000-4000-8000-000000000301",
"slug": "example-asset-management",
"name": "Example Asset Management"
}
},
"report_date": "2026-09-30",
"currency": "PKR",
"data_version": 1,
"identity": {
"fund_name_as_reported": "Example Research Fund",
"fund_short_name_as_reported": "ERF",
"parent_fund_name_as_reported": null,
"plan_name_as_reported": null,
"fund_type_as_reported": "Open-end",
"category_as_reported": "Illustrative mixed-asset category",
"risk_profile_as_reported": "Illustrative higher-risk profile",
"is_shariah_compliant": false,
"is_plan": false,
"is_pension_scheme": false,
"is_etf": false
},
"fund_size": {
"nav_per_unit": "100.500000",
"nav_date": "2026-09-30",
"offer_price": "100.500000",
"redemption_price": "100.500000",
"repurchase_price": "100.500000",
"market_price": null,
"net_assets_pkr": "1005000000.0000",
"fund_size_pkr": "1005000000.0000",
"fund_size_including_fof_pkr": "1005000000.0000",
"fund_size_excluding_fof_pkr": "1005000000.0000",
"amount_invested_by_fof_pkr": "0.0000",
"units_outstanding": "10000000.000000"
},
"profile": {
"launch_date": "2025-01-01",
"inception_date": "2025-01-01",
"maturity_date": null,
"benchmark": "Example composite benchmark",
"old_benchmark": null,
"new_benchmark": null,
"benchmark_effective_date": null,
"risk_of_principal_erosion": "Principal may fluctuate; synthetic disclosure.",
"pricing_mechanism": "Forward pricing — illustrative",
"dealing_days": "Monday to Friday — illustrative",
"dealing_time": "09:00 to 14:00 Pakistan time — illustrative",
"cutoff_time": "14:00 Pakistan time — illustrative",
"settlement_period": "T+2 — illustrative, not an actual dealing policy",
"minimum_initial_investment_pkr": "5000.0000",
"minimum_subsequent_investment_pkr": "1000.0000",
"minimum_redemption_pkr": "1000.0000",
"unit_classes": [
"Illustrative standard units"
],
"leverage": "None in this synthetic example"
},
"report_fragments": [
{
"id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"schema_version": "fmr_page_v3",
"data_version": 1,
"promoted_at": "2026-10-08T08:00:00Z",
"report_date": "2026-09-30",
"report_month": "September 2026",
"page_type": "FUND_REPORT",
"extraction_mode": "PROFILE_PERFORMANCE_PORTFOLIO",
"amc_name_raw": "Example Asset Management",
"fund_name_raw": "Example Research Fund",
"fund_short_name_raw": "ERF",
"parent_fund_name_raw": null,
"plan_name_raw": null,
"fund_type_raw": "Open-end",
"category_raw": "Illustrative mixed-asset category",
"risk_profile_raw": "Illustrative higher-risk profile",
"risk_of_principal_erosion_raw": "Principal may fluctuate; synthetic disclosure.",
"is_shariah_compliant": false,
"is_plan": false,
"is_pension_scheme": false,
"is_etf": false,
"launch_date": "2025-01-01",
"inception_date": "2025-01-01",
"maturity_date": null,
"benchmark_raw": "Example composite benchmark",
"old_benchmark_raw": null,
"new_benchmark_raw": null,
"benchmark_effective_date": null,
"par_value": "100.000000",
"listing_raw": null,
"leverage_raw": "None in this synthetic example",
"nav_per_unit": "100.500000",
"nav_date": "2026-09-30",
"offer_price": "100.500000",
"redemption_price": "100.500000",
"repurchase_price": "100.500000",
"market_price": null,
"net_assets": "1005000000.0000",
"fund_size": "1005000000.0000",
"fund_size_including_fof": "1005000000.0000",
"fund_size_excluding_fof": "1005000000.0000",
"amount_invested_by_fof": "0.0000",
"units_outstanding": "10000000.000000",
"currency": "PKR",
"pricing_mechanism_raw": "Forward pricing — illustrative",
"dealing_days_raw": "Monday to Friday — illustrative",
"dealing_time_raw": "09:00 to 14:00 Pakistan time — illustrative",
"cutoff_time_raw": "14:00 Pakistan time — illustrative",
"settlement_period_raw": "T+2 — illustrative, not an actual dealing policy",
"minimum_initial_investment": "5000.0000",
"minimum_subsequent_investment": "1000.0000",
"minimum_redemption": "1000.0000",
"unit_classes": [
"Illustrative standard units"
]
}
],
"sub_funds": [],
"reported_returns": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"period_label_raw": "1 year",
"period_key": "1Y",
"fund_return_percent": "12.00000000",
"benchmark_return_percent": "10.00000000",
"peer_return_percent": null,
"return_type": "ABSOLUTE",
"is_annualized": false,
"is_since_inception": false,
"calculation_basis_raw": "Synthetic cumulative return for the stated period"
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 2,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"period_label_raw": "Month to date",
"period_key": "MTD",
"fund_return_percent": "0.50000000",
"benchmark_return_percent": "0.40000000",
"peer_return_percent": null,
"return_type": "ABSOLUTE",
"is_annualized": false,
"is_since_inception": false,
"calculation_basis_raw": "Synthetic cumulative September return"
}
],
"allocations": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "ASSET_ALLOCATION",
"label_raw": "Equities",
"label_normalized": null,
"percent_of_total_assets": "60.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "603000000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 2,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "ASSET_ALLOCATION",
"label_raw": "Cash",
"label_normalized": null,
"percent_of_total_assets": "20.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "201000000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 3,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "ASSET_ALLOCATION",
"label_raw": "Government securities",
"label_normalized": null,
"percent_of_total_assets": "15.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "150750000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 4,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "ASSET_ALLOCATION",
"label_raw": "Other assets",
"label_normalized": null,
"percent_of_total_assets": "5.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "50250000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 5,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "SECTOR_ALLOCATION",
"label_raw": "Technology",
"label_normalized": null,
"percent_of_total_assets": "25.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "251250000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 6,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "SECTOR_ALLOCATION",
"label_raw": "Fertilizer",
"label_normalized": null,
"percent_of_total_assets": "20.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "201000000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 7,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "SECTOR_ALLOCATION",
"label_raw": "Banks",
"label_normalized": null,
"percent_of_total_assets": "15.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "150750000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 8,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "CREDIT_QUALITY",
"label_raw": "Government securities — illustrative bucket",
"label_normalized": null,
"percent_of_total_assets": "15.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": null,
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 9,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "CREDIT_QUALITY",
"label_raw": "Unrated / no rating assigned in this example",
"label_normalized": null,
"percent_of_total_assets": "85.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": null,
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
}
],
"holdings": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"holding_group": "TOP_HOLDINGS",
"rank": 1,
"name_raw": "Example Technology Company",
"holding_type": "EQUITY",
"asset_class": "Equities",
"issuer_name_raw": "Example Technology Company",
"security_name_raw": "Example Technology Company ordinary shares",
"symbol_raw": "EXTECH",
"sector_raw": "Technology",
"percent_of_total_assets": "18.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"percent_held": null,
"market_value": "180900000.0000",
"value_before_provisioning": null,
"provisioning_amount": null,
"value_after_provisioning": null,
"quantity": "1000000.000000",
"units": "shares",
"credit_rating": null,
"rating_agency": null,
"instrument_type_raw": "Ordinary shares",
"coupon_rate": null,
"yield_percent": null,
"ytm_percent": null,
"issue_date": null,
"maturity_date": null,
"listed_or_unlisted": "Listed — illustrative",
"secured_or_unsecured": null,
"is_shariah_compliant": null,
"is_top_holding": true,
"is_non_compliant": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 2,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"holding_group": "TOP_HOLDINGS",
"rank": 2,
"name_raw": "Example Fertilizer Company",
"holding_type": "EQUITY",
"asset_class": "Equities",
"issuer_name_raw": "Example Fertilizer Company",
"security_name_raw": "Example Fertilizer Company ordinary shares",
"symbol_raw": "EXFERT",
"sector_raw": "Fertilizer",
"percent_of_total_assets": "12.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"percent_held": null,
"market_value": "120600000.0000",
"value_before_provisioning": null,
"provisioning_amount": null,
"value_after_provisioning": null,
"quantity": "800000.000000",
"units": "shares",
"credit_rating": null,
"rating_agency": null,
"instrument_type_raw": "Ordinary shares",
"coupon_rate": null,
"yield_percent": null,
"ytm_percent": null,
"issue_date": null,
"maturity_date": null,
"listed_or_unlisted": "Listed — illustrative",
"secured_or_unsecured": null,
"is_shariah_compliant": null,
"is_top_holding": true,
"is_non_compliant": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 3,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"holding_group": "TOP_HOLDINGS",
"rank": 3,
"name_raw": "Example Banking Company",
"holding_type": "EQUITY",
"asset_class": "Equities",
"issuer_name_raw": "Example Banking Company",
"security_name_raw": "Example Banking Company ordinary shares",
"symbol_raw": "EXBANK",
"sector_raw": "Banks",
"percent_of_total_assets": "8.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"percent_held": null,
"market_value": "80400000.0000",
"value_before_provisioning": null,
"provisioning_amount": null,
"value_after_provisioning": null,
"quantity": "500000.000000",
"units": "shares",
"credit_rating": null,
"rating_agency": null,
"instrument_type_raw": "Ordinary shares",
"coupon_rate": null,
"yield_percent": null,
"ytm_percent": null,
"issue_date": null,
"maturity_date": null,
"listed_or_unlisted": "Listed — illustrative",
"secured_or_unsecured": null,
"is_shariah_compliant": null,
"is_top_holding": true,
"is_non_compliant": null
}
],
"metrics": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"metric_key": "NUMBER_OF_HOLDINGS",
"label_raw": "Illustrative number of equity holdings",
"value": "12.00000000",
"unit": "count",
"period": "September 2026",
"benchmark_value": null
}
],
"fees": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"fee_type": "TOTAL_EXPENSE_RATIO",
"label_raw": "Illustrative annualized total expense ratio",
"value_percent": "2.000000",
"value_amount": null,
"currency": "PKR",
"period": "September 2026 — annualized illustration",
"with_government_levies": true,
"government_levy_percent": null,
"secp_fee_percent": null,
"is_actual_charged": true,
"is_maximum_allowed": false
}
],
"ratings": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"rating_type": "ILLUSTRATIVE",
"rating_raw": "Illustrative rating — not an agency opinion",
"rating_agency": "Example agency (fictional)",
"rating_date": null,
"outlook_raw": null
}
],
"parties": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"role": "FUND_MANAGER",
"name_raw": "Example Research Team",
"designation_raw": "Illustrative fund-management team",
"organization_raw": "Example Asset Management"
}
],
"special_terms": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"term_type": "INVESTMENT_OBJECTIVE",
"label_raw": "Illustrative investment objective",
"value_raw": "A fictional mixed-asset portfolio used only to demonstrate the response model.",
"value_numeric": null,
"value_percent": null,
"value_amount": null,
"value_date": null,
"currency": "PKR"
}
],
"compliance": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"compliance_type": "ILLUSTRATIVE_DISCLOSURE",
"name_raw": "Synthetic compliance disclosure",
"limit_type_raw": null,
"regulatory_limit_percent": null,
"actual_exposure_percent": null,
"excess_percent": null,
"gross_assets_percent": null,
"net_assets_percent": null,
"status_raw": "Illustrative only — no regulatory assessment has been performed"
}
],
"notes": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"note_kind": "NOTE",
"section_type": "PORTFOLIO",
"note_type": "ILLUSTRATIVE",
"text": "All figures and entities are synthetic. The three reported top holdings are a partial list. Sector percentages use total assets. Credit-quality labels and rating text are not agency opinions."
}
],
"source": [
{
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"document": null,
"promoted_at": "2026-10-08T08:00:00Z",
"data_version": 1
}
],
"sections": {
"sub_funds": {
"status": "NOT_REPORTED",
"row_count": 0
},
"reported_returns": {
"status": "AVAILABLE",
"row_count": 2
},
"allocations": {
"status": "AVAILABLE",
"row_count": 9
},
"holdings": {
"status": "AVAILABLE",
"row_count": 3
},
"metrics": {
"status": "AVAILABLE",
"row_count": 1
},
"fees": {
"status": "AVAILABLE",
"row_count": 1
},
"ratings": {
"status": "AVAILABLE",
"row_count": 1
},
"parties": {
"status": "AVAILABLE",
"row_count": 1
},
"special_terms": {
"status": "AVAILABLE",
"row_count": 1
},
"compliance": {
"status": "AVAILABLE",
"row_count": 1
},
"notes": {
"status": "AVAILABLE",
"row_count": 1
},
"source": {
"status": "AVAILABLE",
"row_count": 1
}
},
"available_expansions": [
"allocations",
"compliance",
"fees",
"holdings",
"metrics",
"notes",
"parties",
"ratings",
"reported_returns",
"source",
"special_terms",
"sub_funds"
]
},
"meta": {
"request_id": "00000000000040008000000000000401",
"generated_at": "2026-10-08T08:00:00Z",
"data_as_of": "2026-09-30",
"data_freshness_days": 8
}
}Inspect the latest NAV model
{
"success": true,
"data": [
{
"fund_id": "00000000-0000-4000-8000-000000000201",
"fund_slug": "example-research-fund",
"fund_name": "Example Research Fund",
"mufap_fund_id": null,
"nav_date": "2026-09-30",
"nav": "100.500000",
"offer_price": "100.500000",
"repurchase_price": "100.500000",
"market_price": null,
"front_end_load_pct": "0.000000",
"back_end_load_pct": "0.000000",
"contingent_load_pct": null,
"nav_change_abs": null,
"nav_change_pct": null,
"currency": "PKR"
}
],
"meta": {
"request_id": "00000000000040008000000000000402",
"generated_at": "2026-10-08T08:00:00Z",
"data_as_of": "2026-09-30",
"data_freshness_days": 8
}
}Sources & further reading
Check the published contract for current fields and limits. Source documents describe reported facts; API availability still depends on promoted production coverage.
- ILovePSX public API reference
Operations and field mappings checked against the local public contract on 9 October 2026.
- MUFAP standardized Fund Manager Report template
Reporting context; check the applicable AMC report and its methodology for any real observation.
- PSX joint procedures: government-security identification and setup
An identification example from the official market infrastructure; not an identity lookup supplied by the Funds API.
- Python Decimal: exact decimal inputs and arithmetic
Put the guide to work.
Start with the documented contract, keep your key server-side, and make dates and missing data visible in your product.
Inspect holdings with reporting context