{"title":"估计对冲基金杠杆：一个三步估计协议","authors":"Ariston Karagiorgis, Konstantinos Drakos","doi":"10.1111/fmii.12214","DOIUrl":null,"url":null,"abstract":"<p>Utilizing a micro-level hedge fund dataset, we propose a methodology for estimating hedge fund leverage. Initially, we perform a Principal Component Analysis on a set of 49 risk factors for dimension deduction purposes. After acquiring 10 Principal Components, we deploy the Least Absolute Shrinkage and Selection Operator regression (Lasso) per fund by seven 3-year monthly non-overlapping intervals in order to select which Principal Components affect each fund's return. As a last step, we execute a regression in the same manner as previously, with only the non-zero Principal Components. By aggregating <span></span><math>\n <semantics>\n <mrow>\n <mi>β</mi>\n <mi>s</mi>\n </mrow>\n <annotation>$\\beta {\\rm s}$</annotation>\n </semantics></math>, we estimate an average sectorial leverage of 3.3 with an average <span></span><math>\n <semantics>\n <msup>\n <mi>R</mi>\n <mn>2</mn>\n </msup>\n <annotation>$R^2$</annotation>\n </semantics></math> of 58.2%. Moreover, we observe an analogous degree of Deleveraging in 2007–2009 that includes the 2008 financial crisis as in 2019–2021 that includes the COVID-19 stress period.</p>","PeriodicalId":39670,"journal":{"name":"Financial Markets, Institutions and Instruments","volume":"34 4","pages":"155-172"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/fmii.12214","citationCount":"0","resultStr":"{\"title\":\"Estimating Hedge Fund Leverage: A Three-Step Estimation Protocol\",\"authors\":\"Ariston Karagiorgis, Konstantinos Drakos\",\"doi\":\"10.1111/fmii.12214\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Utilizing a micro-level hedge fund dataset, we propose a methodology for estimating hedge fund leverage. Initially, we perform a Principal Component Analysis on a set of 49 risk factors for dimension deduction purposes. After acquiring 10 Principal Components, we deploy the Least Absolute Shrinkage and Selection Operator regression (Lasso) per fund by seven 3-year monthly non-overlapping intervals in order to select which Principal Components affect each fund's return. As a last step, we execute a regression in the same manner as previously, with only the non-zero Principal Components. By aggregating <span></span><math>\\n <semantics>\\n <mrow>\\n <mi>β</mi>\\n <mi>s</mi>\\n </mrow>\\n <annotation>$\\\\beta {\\\\rm s}$</annotation>\\n </semantics></math>, we estimate an average sectorial leverage of 3.3 with an average <span></span><math>\\n <semantics>\\n <msup>\\n <mi>R</mi>\\n <mn>2</mn>\\n </msup>\\n <annotation>$R^2$</annotation>\\n </semantics></math> of 58.2%. Moreover, we observe an analogous degree of Deleveraging in 2007–2009 that includes the 2008 financial crisis as in 2019–2021 that includes the COVID-19 stress period.</p>\",\"PeriodicalId\":39670,\"journal\":{\"name\":\"Financial Markets, Institutions and Instruments\",\"volume\":\"34 4\",\"pages\":\"155-172\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/fmii.12214\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Financial Markets, Institutions and Instruments\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/fmii.12214\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Financial Markets, Institutions and Instruments","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/fmii.12214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 0
摘要
利用微观层面的对冲基金数据集，我们提出了一种估算对冲基金杠杆的方法。首先，我们对一组49个风险因素进行主成分分析，以进行维度扣除。在获得10个主成分后，我们对每个基金采用最小绝对收缩和选择算子回归（Lasso），以7个3年的月度非重叠间隔来选择哪些主成分影响每个基金的回报。作为最后一步，我们以与之前相同的方式执行回归，只有非零主成分。通过汇总β s $\beta {\rm s}$，我们估计平均部门杠杆为3.3，平均r2 $R^2$为58.2%。此外，我们观察到2007-2009年（包括2008年金融危机）的去杠杆化程度与2019-2021年（包括COVID-19压力期）相似。
Estimating Hedge Fund Leverage: A Three-Step Estimation Protocol
Utilizing a micro-level hedge fund dataset, we propose a methodology for estimating hedge fund leverage. Initially, we perform a Principal Component Analysis on a set of 49 risk factors for dimension deduction purposes. After acquiring 10 Principal Components, we deploy the Least Absolute Shrinkage and Selection Operator regression (Lasso) per fund by seven 3-year monthly non-overlapping intervals in order to select which Principal Components affect each fund's return. As a last step, we execute a regression in the same manner as previously, with only the non-zero Principal Components. By aggregating , we estimate an average sectorial leverage of 3.3 with an average of 58.2%. Moreover, we observe an analogous degree of Deleveraging in 2007–2009 that includes the 2008 financial crisis as in 2019–2021 that includes the COVID-19 stress period.
期刊介绍：
Financial Markets, Institutions and Instruments bridges the gap between the academic and professional finance communities. With contributions from leading academics, as well as practitioners from organizations such as the SEC and the Federal Reserve, the journal is equally relevant to both groups. Each issue is devoted to a single topic, which is examined in depth, and a special fifth issue is published annually highlighting the most significant developments in money and banking, derivative securities, corporate finance, and fixed-income securities.
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