openapi-directory/api/portfoliooptimizer.io.json

Building & bundling https://github.com/APIs-guru/openapi-directory for easy use from JS

{"openapi":"3.0.1","servers":[{"url":"https://api.portfoliooptimizer.io/v1"},{"url":"https://eu-west-1.api.portfoliooptimizer.io/v1"}],"info":{"contact":{"email":"contact@portfoliooptimizer.io","name":"Support","url":"https://portfoliooptimizer.io/"},"description":"Portfolio Optimizer is a [Web API](https://en.wikipedia.org/wiki/Web_API) to analyze and optimize investment portfolios (collection of financial assets such as stocks, bonds, ETFs, crypto-currencies) using modern portfolio theory algorithms (mean-variance, VaR, etc.).\n\n# API General Information\n\n  Portfolio Optimizer is based on [REST](https://en.wikipedia.org/wiki/Representational_state_transfer) for easy integration, uses [JSON](https://en.wikipedia.org/wiki/JSON) for the exchange of data and uses a standard [HTTP verb](https://en.wikipedia.org/wiki/Hypertext_Transfer_Protocol#Request_methods) (`POST`) to represent the action(s).\n\nPortfolio Optimizer is also as secured as a Web API could be: \n* [256-bit HTTPS Encryption](https://en.wikipedia.org/wiki/HTTPS)\n* No usage of cookies\n* No usage of personal data  \n\n## API Headers \nThe following HTTP header(s) are required when calling Portfolio Optimizer endpoints:\n* `Content-type: application/json`  \n  This header specifies that the data provided in input to the endpoint is in JSON format\n\nThe following HTTP header(s) are optional when calling Portfolio Optimizer endpoints:\n* `Content-Encoding: gzip`  \n  This header indicates that the data provided in input to the endpoint is compressed with gzip.\n* `X-API-Key: <private API key>`  \n  This header enables [authenticated users](#auth) to provide their private [API key](#overview--api-key) in order to [benefit from higher API limits](#overview--api-limits)\n\n## API Key\nPortfolio Optimizer is free to use, but not free to run.\n\nIn order to obtain an API key and benefit from [higher API limits](#overview--api-limits), a *small* participation to Portfolio Optimizer running costs is required.\n\nThis participation takes the form of coffee(s), with one coffee = one month of usage.\n\n<p><a href=\"https://www.buymeacoffee.com/portfolioopt\"><img alt='Buy a Coffee at buymeacoffee.com' src=\"https://img.buymeacoffee.com/button-api/?text=Buymeacoffee.com&emoji=&slug=portfolioopt&button_colour=000000&font_colour=ffffff&font_family=Cookie&outline_colour=ffffff&coffee_colour=FFDD00\"></a></p>\n\n\n> **Notes:** \n> * Please make sure not to expose your API key publicly!\n\n## API Limits \n\nPortfolio Optimizer comes with *fairly reasonable* API limits.\n\nFor anonymous users:  \n* The API requests are restricted to a subset of all the available endpoints and/or endpoints features  \n* The API requests are limited to 1 request per second for all the anonymous users combined, with concurrent requests rejected \n* The API requests are limited to 1 second of execution time\n* The API requests are limited to 20 assets, 250 portfolios, 500 series data points and 5 factors\n\nFor authenticated users with an [API key](#overview--api-key):  \n* The API requests have access to all the available endpoints and endpoints features\n* The API requests are limited to 10000 requests per 24 hour per API key, with concurrent requests queued\n* The API requests are limited to 2.5 seconds of execution time\n* The API requests are limited to 100 assets, 1250 portfolios, 2500 series data points and 25 factors\n\n> **Notes:** \n> * It is possible to further relax the API limits, or to disable the API limits alltogether; please [contact the support](https://portfoliooptimizer.io/contact/) for more details.\n> * Information on the API rate limits are provided in response messages HTTP headers `x-ratelimit-*`:  \n>   * `x-ratelimit-limit-second`, the limit on the number of API requests per second\n>   * `x-ratelimit-remaining-second`, the number of remaining API requests in the current second    \n>   * `x-ratelimit-limit-minute`, the limit on the number of API requests per minute\n>   * ...\n\n## API Regions\nPortfolio Optimizer servers are located in Western Europe.\n\n> **Notes:** \n> * It is possible to deploy Portfolio Optimizer in other geographical regions, for example to improve the API latency; please [contact the support](https://portfoliooptimizer.io/contact/) for more details. \n\n## API Response Codes       \n\nStandard [HTTP response codes](https://en.wikipedia.org/wiki/List_of_HTTP_status_codes) are used by Portfolio Optimizer to provide details on the status of API requests.\n\n| HTTP Code | Description | Notes |\n| --------- | ----------- | ----- |\n| 200 | Request successfully processed | - |\n| 400 | Request failed to be processed because of incorrect content | The response message body contains information on the incorrect content |\n| 401 | Request failed to be processed because of invalid API key | - |\n| 404 | Request failed to be processed because of non existing endpoint | The requested endpoint might exist, but needs to be accessed with another HTTP method (e.g., `POST` instead of `GET`) |\n| 429 | Request failed to be processed because of API limits violated | The response message HTTP headers `x-ratelimit-*` contain information on the [API limits](#overview--api-limits) |\n| 500 | Request failed to be processed because of an internal error | Something went wrong on Portfolio Optimizer side, do not hesitate to [report the issue](#overview--support) |\n| 502 | Request failed to be processed because of a temporary connectivity error | Something went wrong on Portfolio Optimizer side, please check the [API status](#overview--api-status) and do not hesitate to [report the issue](#overview--support) |\n\n## API Status  \n\nPortfolio Optimizer is monitored 24/7 by [UptimeRobot](https://stats.uptimerobot.com/wgW71SL1AW).\n\n# Support\n\nFor any issue or question about Portfolio Optimizer, please do not hesitate to [contact the support](https://portfoliooptimizer.io/contact/).\n","license":{"name":"Apache 2.0","url":"http://www.apache.org/licenses/LICENSE-2.0.html"},"termsOfService":"https://portfoliooptimizer.io/terms-of-service","title":"Portfolio Optimizer","version":"1.0.9","x-apisguru-categories":["financial"],"x-logo":{"url":"https://portfoliooptimizer.io/assets/images/88x88.png"},"x-origin":[{"format":"openapi","url":"https://docs.portfoliooptimizer.io/openapi/portfoliooptimizer.yaml","version":"3.0"}],"x-providerName":"portfoliooptimizer.io"},"externalDocs":{"description":"External documentation","url":"https://docs.portfoliooptimizer.io/"},"security":[{"ApiKeyAuth":[]}],"paths":{"/assets/analysis/absorption-ratio":{"post":{"description":"Compute the absorption ratio associated to a universe of assets.\n\nReferences\n* [Mark Kritzman, Yuanzhen Li, Sebastien Page and Roberto Rigobon, Principal Components as a Measure of Systemic Risk, The Journal of Portfolio Management Summer 2011, 37 (4) 112-126](https://jpm.pm-research.com/content/37/4/112)\n","requestBody":{"content":{"application/json":{"examples":{"Example":{"description":"Compute the absorption ratio of 2 assets","value":{"assets":2,"assetsCovarianceMatrix":[[9,1],[1,1]]}}},"schema":{"properties":{"assets":{"description":"The number of assets","minimum":1,"type":"integer"},"assetsCovarianceMatrix":{"description":"assetsCovarianceMatrix[i][j] is the covariance between the asset i and the asset j","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"},"assetsCovarianceMatrixEigenvectors":{"properties":{"eigenvectorsRetained":{"description":"The number of eigenvectors to retain in the numerator of the absorption ratio, which must be lower than the number of assets; 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Kritzman, Y. Li, Skulls, Financial Turbulence, and Risk Management,Financial Analysts Journal, Volume 66, Number 5, Pages 30-41, Year 2010](https://www.tandfonline.com/doi/abs/10.2469/faj.v66.n5.3)\n* [Kinlaw, W., Turkington, D. Correlation surprise. J Asset Manag 14, 385–399 (2013)](https://link.springer.com/article/10.1057/jam.2013.27)\n","requestBody":{"content":{"application/json":{"examples":{"Example (1 asset)":{"description":"Compute the turbulence index of 1 asset","value":{"assets":1,"assetsAverageReturns":[0.5],"assetsCovarianceMatrix":[[1]],"assetsReturns":[1]}},"Example (2 assets)":{"description":"Compute the turbulence index of 2 assets","value":{"assets":2,"assetsAverageReturns":[1,1],"assetsCovarianceMatrix":[[9,1],[1,1]],"assetsReturns":[1,0]}}},"schema":{"properties":{"assets":{"description":"The number of assets","minimum":1,"type":"integer"},"assetsAverageReturns":{"description":"assetsAverageReturns[i] is the average return of asset i over an historical reference period","items":{"type":"number"},"minItems":1,"type":"array"},"assetsCovarianceMatrix":{"description":"assetsCovarianceMatrix[i][j] is the covariance between the asset i and the asset j over an historical reference period","items":{"items":{"type":"number"},"minItems":1,"type":"array"},"minItems":1,"type":"array"},"assetsReturns":{"description":"assetsReturns[i] is the return of asset i over a period different from the historical reference period","items":{"type":"number"},"minItems":1,"type":"array"}},"required":["assets","assetsCovarianceMatrix","assetsAverageReturns","assetsReturns"],"type":"object"}}},"required":true},"responses":{"200":{"content":{"application/json":{"examples":{"Example":{"description":"Computed turbulence index","value":{"assetsTurbulenceIndex":0.5624999999999999}}},"schema":{"properties":{"assetsTurbulenceIndex":{"description":"the turbulence index of the universe of assets","type":"number"}},"required":["assetsTurbulenceIndex"],"type":"object"}}},"description":"OK"}},"summary":"Turbulence Index","tags":["Assets / Analysis"],"x-codegen-request-body-name":"body"}},"/assets/correlation/matrix":{"post":{"description":"Compute the Pearson asset correlation matrix from either:  \n* The asset returns\n* The asset covariance matrix\n\nReferences\n* [Wikipedia, Correlation and Dependence](https://en.wikipedia.org/wiki/Correlation_and_dependence#Correlation_matrices)\n","requestBody":{"content":{"application/json":{"examples":{"From covariance matrix":{"description":"Computes the correlation matrix of 2 assets based on their covariance matrix","value":{"assets":2,"assetsCovarianceMatrix":[[0.01,-0.0025],[-0.0025,0.0025]]}},"From returns":{"description":"Computes the correlation matrix of 2 assets based on 4 returns per asset","value":{"assets":[{"assetReturns":[0.01,0,0.02,-0.03]},{"assetReturns":[0.01,0,0.02,-0.03]}]}}},"schema":{"oneOf":[{"properties":{"assets":{"items":{"properties":{"assetReturns":{"description":"assetReturns[t] is the return of the asset at the time t; 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Rev. Lett. 83, 1467](https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.83.1467)\n","requestBody":{"content":{"application/json":{"examples":{"Example":{"description":"Denoise an asset correlation matrix of 3 assets","value":{"assets":3,"assetsCorrelationMatrix":[[1,0.5,0.9],[0.5,1,0.7],[0.9,0.7,1]],"assetsCorrelationMatrixAspectRatio":0.5}}},"schema":{"properties":{"assets":{"minimum":2,"type":"integer"},"assetsCorrelationMatrix":{"description":"assetsCorrelationMatrix[i][j] is the correlation between the asset i and the asset j","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"},"assetsCorrelationMatrixAspectRatio":{"description":"The aspect ratio of the asset correlation matrix, defined as the number of assets divided by the number of asset returns per asset used to compute the asset correlation matrix","exclusiveMinimum":true,"minimum":0,"type":"number"},"denoisingMethod":{"default":"eigenvaluesClipping","description":"The method used to denoise the asset correlation matrix","enum":["eigenvaluesClipping"],"type":"string"}},"required":["assets","assetsCorrelationMatrix","assetsCorrelationMatrixAspectRatio"],"type":"object"}}},"required":true},"responses":{"200":{"content":{"application/json":{"examples":{"Example":{"description":"Denoised correlation matrix","value":{"assetsCorrelationMatrix":[[1,0.6838346015086407,0.7246659534718176],[0.6838346015086407,1,0.6978824315038066],[0.7246659534718176,0.6978824315038066,1]]}},"Example of failing denoising method":{"description":"No denoised correlation matrix","value":{"assetsCorrelationMatrix":null}}},"schema":{"properties":{"assetsCorrelationMatrix":{"description":"assetsCorrelationMatrix[i][j] is the correlation between the asset i and the asset j; assetsCorrelationMatrix is possibly null in case the denoising method did not manage to denoise the provided asset correlation matrix","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"}},"required":["assetsCorrelationMatrix"],"type":"object"}}},"description":"OK"}},"summary":"Denoised Correlation Matrix","tags":["Assets / Correlation Matrix"],"x-codegen-request-body-name":"body"}},"/assets/correlation/matrix/distance":{"post":{"description":"Compute the distance between an asset correlation matrix and a reference correlation matrix, using one of the following distance metrics:\n* Euclidean distance (default), which is the distance induced by [the Frobenius norm](https://en.wikipedia.org/wiki/Matrix_norm#Frobenius_norm)\n* Correlation matrix distance, defined in the first reference, which corresponds to [the cosine distance](https://en.wikipedia.org/wiki/Cosine_similarity) between the two vectorized asset correlation matrices\n* Bures distance, defined in the second reference\n\n References\n * [M. Herdin, N. Czink, H. Ozcelik and E. Bonek, Correlation matrix distance, a meaningful measure for evaluation of non-stationary MIMO channels, 2005 IEEE 61st Vehicular Technology Conference, 2005, pp. 136-140 Vol. 1](https://ieeexplore.ieee.org/document/1543265)\n * [Rajendra Bhatia, Tanvi Jain, Yongdo Lim, On the Bures–Wasserstein distance between positive definite matrices, Expositiones Mathematicae, Volume 37, Issue 2, 2019](https://www.sciencedirect.com/science/article/pii/S0723086918300021)\n","requestBody":{"content":{"application/json":{"examples":{"Example (correlation matrix distance)":{"description":"Compute the correlation matrix distance between an asset correlation matrix and an equicorrelation matrix","value":{"assets":3,"assetsCorrelationMatrix":[[1,0.5,0.9],[0.5,1,0.7],[0.9,0.7,1]],"distanceMetric":"correlationMatrix","referenceCorrelationMatrix":[[1,1,1],[1,1,1],[1,1,1]]}},"Example (euclidean distance)":{"description":"Compute the euclidean distance between an asset correlation matrix and an equicorrelation matrix","value":{"assets":3,"assetsCorrelationMatrix":[[1,0.5,0.9],[0.5,1,0.7],[0.9,0.7,1]],"referenceCorrelationMatrix":[[1,1,1],[1,1,1],[1,1,1]]}}},"schema":{"properties":{"assets":{"minimum":2,"type":"integer"},"assetsCorrelationMatrix":{"description":"assetsCorrelationMatrix[i][j] is the correlation between the asset i and the asset j","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"},"distanceMetric":{"default":"euclidean","description":"The distance metric to use to compute the distance between the asset correlation matrix and the reference correlation matrix","enum":["euclidean","correlationMatrix","bures"],"type":"string"},"referenceCorrelationMatrix":{"description":"referenceCorrelationMatrix[i][j] is the reference correlation between the asset i and the asset j","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"}},"required":["assets","assetsCorrelationMatrix","referenceCorrelationMatrix"]}}},"required":true},"responses":{"200":{"content":{"application/json":{"examples":{"Example":{"description":"Computed distance","value":{"assetsCorrelationMatrixDistance":0.8366600265340757}}},"schema":{"properties":{"assetsCorrelationMatrixDistance":{"description":"The computed distance between the two correlation matrices","minimum":0,"type":"number"}},"required":["assetsCorrelationMatrixDistance"],"type":"object"}}},"description":"OK"}},"summary":"Correlation Matrix Distance","tags":["Assets / Correlation Matrix"],"x-codegen-request-body-name":"body"}},"/assets/correlation/matrix/effective-rank":{"post":{"description":"Compute the effective rank of an asset correlation matrix.\n\nReferences\n* [Olivier Roy and Martin Vetterli, The effective rank: A measure of effective dimensionality, 15th European Signal Processing Conference, 2007](https://ieeexplore.ieee.org/document/7098875)\n","requestBody":{"content":{"application/json":{"examples":{"Example":{"description":"Compute the effective rank of a correlation matrix of 2 assets","value":{"assets":2,"assetsCorrelationMatrix":[[1,0],[0,1]]}}},"schema":{"properties":{"assets":{"description":"The number of assets","minimum":2,"type":"integer"},"assetsCorrelationMatrix":{"description":"assetsCorrelationMatrix[i][j] is the correlation between the asset i and the asset j","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"}},"required":["assets","assetsCorrelationMatrix"]}}},"required":true},"responses":{"200":{"content":{"application/json":{"examples":{"Example":{"description":"Computed effective rank","value":{"assetsCorrelationMatrixEffectiveRank":2}}},"schema":{"properties":{"assetsCorrelationMatrixEffectiveRank":{"description":"The effective rank of the asset correlation matrix","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"}},"required":["assetsCorrelationMatrixEffectiveRank"],"type":"object"}}},"description":"OK"}},"summary":"Correlation Matrix Effective Rank","tags":["Assets / Correlation Matrix"],"x-codegen-request-body-name":"body"}},"/assets/correlation/matrix/informativeness":{"post":{"description":"Compute the informativeness of an asset correlation matrix, using one of the following distance metrics:\n* Euclidean distance (default), which is the distance induced by [the Frobenius norm](https://en.wikipedia.org/wiki/Matrix_norm#Frobenius_norm)\n* Correlation matrix distance, defined in the second reference, which corresponds to [the cosine distance](https://en.wikipedia.org/wiki/Cosine_similarity) between the two vectorized asset correlation matrices\n* Bures distance, defined in the third reference\n\n References\n * [Austin J. Brockmeier and Tingting Mu and Sophia Ananiadou and John Y. Goulermas, Quantifying the Informativeness of Similarity Measurements, Journal of Machine Learning Research, 2017](http://jmlr.org/papers/v18/16-296.html)\n * [M. Herdin, N. Czink, H. Ozcelik and E. Bonek, Correlation matrix distance, a meaningful measure for evaluation of non-stationary MIMO channels, 2005 IEEE 61st Vehicular Technology Conference, 2005, pp. 136-140 Vol. 1](https://ieeexplore.ieee.org/document/1543265)\n * [Rajendra Bhatia, Tanvi Jain, Yongdo Lim, On the Bures–Wasserstein distance between positive definite matrices, Expositiones Mathematicae, Volume 37, Issue 2, 2019](https://www.sciencedirect.com/science/article/pii/S0723086918300021)\n","requestBody":{"content":{"application/json":{"examples":{"Example (Bures distance)":{"description":"Compute the informativeness of an asset correlation matrix usingn the Bures distance","value":{"assets":3,"assetsCorrelationMatrix":[[1,0.5,0.9],[0.5,1,0.7],[0.9,0.7,1]],"distanceMetric":"bures"}},"Example (euclidean distance)":{"description":"Compute the informativeness of an asset correlation matrix usingn the euclidean distance","value":{"assets":3,"assetsCorrelationMatrix":[[1,0.5,0.9],[0.5,1,0.7],[0.9,0.7,1]]}}},"schema":{"properties":{"assets":{"minimum":2,"type":"integer"},"assetsCorrelationMatrix":{"description":"assetsCorrelationMatrix[i][j] is the correlation between the asset i and the asset j","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"},"distanceMetric":{"default":"euclidean","description":"The distance metric to use to compute the informativeness of the asset correlation matrix","enum":["euclidean","correlationMatrix","bures"],"type":"string"}},"required":["assets","assetsCorrelationMatrix"]}}},"required":true},"responses":{"200":{"content":{"application/json":{"examples":{"Example":{"description":"Computed informativeness","value":{"assetsCorrelationMatrixInformativeness":0.020539611658192996}}},"schema":{"properties":{"assetsCorrelationMatrixInformativeness":{"description":"The informativeness of the asset correlation matrix","minimum":0,"type":"number"}},"required":["assetsCorrelationMatrixInformativeness"],"type":"object"}}},"description":"OK"}},"summary":"Correlation Matrix Informativeness","tags":["Assets / Correlation Matrix"],"x-codegen-request-body-name":"body"}},"/assets/correlation/matrix/nearest":{"post":{"description":"Compute the _closest_ - in terms of [the Frobenius norm](https://en.wikipedia.org/wiki/Matrix_norm#Frobenius_norm) - asset correlation matrix to an approximate asset correlation matrix, optionally keeping a selected number of correlations fixed.\n\nReferences\n* [Nicholas J. Higham, Computing the Nearest Correlation Matrix—A Problem from Finance, IMA J. Numer. Anal. 22, 329–343, 2002.](http://www.maths.manchester.ac.uk/~higham/narep/narep369.pdf)\n","requestBody":{"content":{"application/json":{"examples":{"Nearest correlation matrix":{"description":"Compute the nearest correlation matrix to an approximate correlation matrix","value":{"assets":3,"assetsApproximateCorrelationMatrix":[[1,1,0],[1,1,1],[0,1,1]]}},"Nearest correlation matrix with fixed a correlation":{"description":"Compute the nearest correlation matrix to an approximate correlation matrix, keeping one correlation coefficient fixed","value":{"assets":3,"assetsApproximateCorrelationMatrix":[[1,0.5,0.9],[0.5,1,-0.2],[0.9,-0.2,1]],"assetsFixedCorrelations":[[2,3]]}}},"schema":{"properties":{"assets":{"description":"The number of assets","minimum":2,"type":"integer"},"assetsApproximateCorrelationMatrix":{"description":"assetsApproximateCorrelationMatrix[i][i] is the approximate correlation between the asset i and the asset j","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"},"assetsFixedCorrelations":{"description":"assetsFixedCorrelations[k] is the couple of indices (i,j) of the assets i and j for which to keep the approximate correlation assetsApproximateCorrelationMatrix[i][j] fixed","items":{"items":{"type":"integer"},"maxItems":2,"minItems":2,"type":"array"},"type":"array"}},"required":["assets","assetsApproximateCorrelationMatrix"],"type":"object"}}},"required":true},"responses":{"200":{"content":{"application/json":{"examples":{"Nearest correlation matrix":{"description":"Computed nearest correlation matrix","value":{"assetsCorrelationMatrix":[[1,0.7606306078350177,0.15733356650676536],[0.7606306078350177,1,0.7606306078350177],[0.15733356650676536,0.7606306078350177,1]]}},"Nearest correlation matrix with fixed a correlation":{"description":"Computed nearest correlation matrix keeping one correlation coefficient fixed","value":{"assetsCorrelationMatrix":[[1,0.4314569968899409,0.7974943959465133],[0.4314569968899409,1,-0.2],[0.7974943959465133,-0.2,1]]}}},"schema":{"properties":{"assetsCorrelationMatrix":{"description":"assetsCorrelationMatrix[i][j] is the correlation between the asset i and the asset j","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"}},"required":["assetsCorrelationMatrix"],"type":"object"}}},"description":"OK"}},"summary":"Nearest Correlation Matrix","tags":["Assets / Correlation Matrix"],"x-codegen-request-body-name":"body"}},"/assets/correlation/matrix/random":{"post":{"description":"Generate an asset correlation matrix uniformly at random over the space of positive definite correlation matrices.\n\nReferences\n* [Joe, H., Generating random correlation matrices based on partial correlations. Journal of Multivariate Analysis, 2006, 97, 2177-2189](https://www.sciencedirect.com/science/article/pii/S0047259X05000886)\n","requestBody":{"content":{"application/json":{"examples":{"Example":{"description":"Generate a 2x2 correlation matrix","value":{"assets":2}}},"schema":{"properties":{"assets":{"description":"The number of assets","minimum":2,"type":"integer"}},"required":["assets"],"type":"object"}}},"required":true},"responses":{"200":{"content":{"application/json":{"examples":{"Example":{"description":"Computed random correlation matrix","value":{"assetsCorrelationMatrix":[[1,0.7606306078350177,0.15733356650676536],[0.7606306078350177,1,0.7606306078350177],[0.15733356650676536,0.7606306078350177,1]]}}},"schema":{"properties":{"assetsCorrelationMatrix":{"description":"assetsCorrelationMatrix[i][j] is the correlation between the asset i and the asset 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RiskMetrics technical document, Technical Report fourth edition](https://www.msci.com/documents/10199/5915b101-4206-4ba0-aee2-3449d5c7e95a)\n","requestBody":{"content":{"application/json":{"examples":{"Example":{"description":"Computes an exponentially weighted covariance matrix of 2 assets based on 4 returns per asset and a decay factor of 0.5","value":{"assets":[{"assetReturns":[0.01,0.01,0.02,0.01]},{"assetReturns":[-0.02,-0.02,-0.04,-0.02]}],"decayFactor":0.5}}},"schema":{"properties":{"assets":{"items":{"properties":{"assetReturns":{"description":"assetReturns[t] is the return of the asset at the time t; all the assetReturns arrays must have the same length","items":{"type":"number"},"minItems":2,"type":"array"}},"required":["assetReturns"],"type":"object"},"minItems":2,"type":"array"},"decayFactor":{"default":0.94,"description":"The exponential decay factor","exclusiveMaximum":true,"exclusiveMinimum":true,"maximum":1,"minimum":0,"type":"number"}},"required":["assets"],"type":"object"}}},"required":true},"responses":{"200":{"content":{"application/json":{"examples":{"Example":{"description":"Computed exponentially weighted covariance matrix","value":{"assetsCovarianceMatrix":[[0.000019583333333333333,-0.000039166666666666665],[-0.000039166666666666665,0.00007833333333333333]]}}},"schema":{"properties":{"assetsCovarianceMatrix":{"description":"assetsCovarianceMatrix[i][j] is the sample covariance between the asset i returns and the asset j returns","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"}},"required":["assetsCovarianceMatrix"],"type":"object"}}},"description":"OK"}},"summary":"Exponentially Weighted Covariance Matrix","tags":["Assets / Covariance Matrix"],"x-codegen-request-body-name":"body"}},"/assets/covariance/matrix/validation":{"post":{"description":"Validate whether a matrix is a covariance matrix.\n\nReferences\n* [Wikipedia, Covariance Matrix](https://en.wikipedia.org/wiki/Covariance_matrix)\n","requestBody":{"content":{"application/json":{"examples":{"Example":{"description":"Validate whether the provided matrix is a covariance matrix","value":{"assets":2,"assetsCovarianceMatrix":[[0.00035,-0.00035],[-0.00035,0.00035]]}}},"schema":{"properties":{"assets":{"description":"The number of assets","minimum":2,"type":"integer"},"assetsCovarianceMatrix":{"description":"assetsCovarianceMatrix[i][j] is the covariance between the asset i and the asset j","items":{"items":{"type":"number"},"minItems":2,"type":"array"},"minItems":2,"type":"array"}},"required":["assets","assetsCovarianceMatrix"],"type":"object"}}},"required":true},"responses":{"200":{"content":{"application/json":{"examples":{"Example":{"description":"Valid covariance matrix","value":{"message":"valid covariance matrix"}}},"schema":{"properties":{"message":{"description":"Indicates whether the matrix is a valid covariance matrix","enum":["valid covariance matrix","invalid covariance matrix - 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