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Weights

Computes the weights to be allocated for a portfolio

This is the simplest and most fundamental block. It takes a time-series of unlimited instruments as an input and outputs weights for each path. The weights under no constraints, should sum up to 1 in order to reflect a fully invested portfolio.

note

This endpoint is experimental so please take note that the processing performance hasn't been fine tuned yet, i.e. do expect up to 30 seconds to get a response from the engine. The computation are however production ready.

Method#

POST /v1/optimiser/weights

Parameters#

ticker(s) symbol(s) REQUIRED - one or many symbols. For example the following symbols are valid: AAPL,HOG,KO

info

The list of tickers supported by the PathLit engine are advertised at /v1/timeseries/info

Response attributes#

info

Want to learn more about the attributes? a deep dive is available at this location, under the quant section

AttributeHigh level explanation
l1r.l2d.l3ewpAssets aggregated by daily log-returns, allocated using an equally-weighted strategy
l1r.l2d.l3gmvpAssets aggregated by daily log-returns allocated using a global minimum-variance strategy
l1r.l2d.l3hrpAssets aggregated by daily log-returns allocated using a hierarchical risk-parity strategy
l1r.l2d.l3ivpAssets aggregated by daily log-returns allocated using an inverse-volatility strategy
l1r.l2d.l3mdcpAssets aggregated by daily log-returns allocated using an maximum-decorrelation strategy
l1r.l2d.l3mdpAssets aggregated by daily log-returns allocated using an maximum-diversified strategy
l1r.l2d.l3rppAssets aggregated by daily log-returns allocated using an risk-parity strategy
l1r.l2m.l3ewpAssets aggregated by monthly log-returns, allocated using an equally-weighted strategy
l1r.l2m.l3gmvpAssets aggregated by monthly log-returns allocated using a global minimum-variance strategy
l1r.l2m.l3hrpAssets aggregated by monthly log-returns allocated using a hierarchical risk-parity strategy
l1r.l2m.l3ivpAssets aggregated by monthly log-returns allocated using an inverse-volatility strategy
l1r.l2m.l3mdcpAssets aggregated by monthly log-returns allocated using an maximum-decorrelation strategy
l1r.l2m.l3mdpAssets aggregated by monthly log-returns allocated using an maximum-diversified strategy
l1r.l2m.l3rppAssets aggregated by monthly log-returns allocated using an risk-parity strategy
l1r.l2w.l3ewpAssets aggregated by monthly log-returns, allocated using an equally-weighted strategy
l1r.l2w.l3gmvpAssets aggregated by weekly log-returns allocated using a global minimum-variance strategy
l1r.l2w.l3hrpAssets aggregated by weekly log-returns allocated using a hierarchical risk-parity strategy
l1r.l2w.l3ivpAssets aggregated by weekly log-returns allocated using an inverse-volatility strategy
l1r.l2w.l3mdcpAssets aggregated by weekly log-returns allocated using an maximum-decorrelation strategy
l1r.l2w.l3mdpAssets aggregated by weekly log-returns allocated using an maximum-diversified strategy
l1r.l2w.l3rppAssets aggregated by weekly log-returns allocated using an risk-parity strategy

Note#

n/a

Example#

curl--request POST 'https://engine.pathlit.io/v1/optimiser/weights' \--header 'x-api-key: xxxxxxxxxxxxxxxxxxxxx' \--header 'Content-Type: application/json' \--data-raw '{    "tickers": [        "AAPL",        "HOG",        "KO"    ]}'