系统性风险评估和分析框架。.zip

# Systemic Risk This framework calculates, analyses and compares the following systemic risk measures: * **BUBBLES DETECTION MEASURES** * `BUB (Bubbles Flag)` * `BMPH (Boom Phases Flag)` * `BRPH (Burst Phases Flag)` * `BC (Bubbling Capitalization)` * `BCP (Bubbling Capitalization Percentage)` * *References*: [Phillips et al. (2015)](https://doi.org/10.1111/iere.12132), [Phillips & Shi (2018)](https://doi.org/10.1016/bs.host.2018.12.002), [Phillips & Shi (2019)](https://doi.org/10.1111/obes.12307), [Brunnermeier et al. (2020)](https://doi.org/10.1093/rfs/hhaa011) * **COMPONENT MEASURES** * `AR (Absorption Ratio)` by [Kritzman et al. (2010)](https://doi.org/10.2139/ssrn.1633027) * `CATFIN` by [Allen et al. (2012)](https://doi.org/10.1093/rfs/hhs094) * `CS (Correlation Surprise)` by [Kinlaw & Turkington (2012)](https://doi.org/10.2139/ssrn.2133396) * `TI (Turbulence Index)` by [Kritzman & Li (2010)](https://doi.org/10.2469/faj.v66.n5.3) * `Principal Component Analysis` * **CONNECTEDNESS MEASURES** * `DCI (Dynamic Causality Index)` * `CIO ("In & Out" Connections)` * `CIOO ("In & Out - Other" Connections)` * `Network Centralities: Betweenness, Degree, Closeness, Clustering, Eigenvector & Katz` * *References*: [Billio et al. (2011)](https://doi.org/10.2139/ssrn.1963216) * **CROSS-ENTROPY MEASURES** * `JPoD (Joint Probability of Default)` * `FSI (Financial Stability Index)` * `PCE (Probability of Cascade Effects)` * `DiDe (Distress Dependency)` * `SI (Systemic Importance)` * `SV (Systemic Vulnerability)` * `CoJPoDs (Conditional Joint Probabilities of Default)` * *References*: [Segoviano & Goodhart (2009)](http://doi.org/10.5089/9781451871517.001), [Radev (2012)](https://doi.org/10.2139/ssrn.2048585), [Segoviano & Espinoza (2017)](http://www.systemicrisk.ac.uk/publications/discussion-papers/consistent-measures-systemic-risk), [Cortes et al. (2018)](http://doi.org/10.5089/9781484338605.001) * **CROSS-QUANTILOGRAM MEASURES** * `Full Cross-Quantilograms` * `Partial Cross-Quantilograms` * *References*: [Han et al. (2016)](https://doi.org/10.1016/j.jeconom.2016.03.001) * **CROSS-SECTIONAL MEASURES** * `Idiosyncratic Metrics: Beta, Value-at-Risk & Expected Shortfall` * `CAViaR (Conditional Autoregressive Value-at-Risk)` by [White et al. (2015)](https://doi.org/10.1016/j.jeconom.2015.02.004) * `CoVaR & Delta CoVaR (Conditional Value-at-Risk)` by [Adrian & Brunnermeier (2008)](https://doi.org/10.2139/ssrn.1269446) * `MES (Marginal Expected Shortfall)` by [Acharya et al. (2010)](https://doi.org/10.2139/ssrn.1573171) * `SES (Systemic Expected Shortfall)` by [Acharya et al. (2010)](https://doi.org/10.2139/ssrn.1573171) * `SRISK (Conditional Capital Shortfall Index)` by [Brownlees & Engle (2010)](https://doi.org/10.2139/ssrn.1611229) * **DEFAULT MEASURES** * `D2C (Distance To Capital)` by [Chan-Lau & Sy (2007)](https://doi.org/10.1057/palgrave.jbr.2350056) * `D2D (Distance To Default)` by [Vassalou & Xing (2004)](https://doi.org/10.1111/j.1540-6261.2004.00650.x) * `DIP (Distress Insurance Premium)` by [Black et al. (2012)](https://doi.org/10.2139/ssrn.2181645) * `SCCA (Systemic Contingent Claims Analysis)` by [Jobst & Gray (2013)](https://doi.org/10.5089/9781475572780.001) * **LIQUIDITY MEASURES** * `ILLIQ (Illiquidity Measure)` by [Amihud (2002)](https://doi.org/10.1016/S1386-4181(01)00024-6) * `RIS (Roll Implicit Spread)` by [Hasbrouck (2009)](https://doi.org/10.1111/j.1540-6261.2009.01469.x) * `Classic Indicators: Hui-Heubel Liquidity Ratio, Turnover Ratio & Variance Ratio` * **REGIME-SWITCHING MEASURES** * `2-States Model: High & Low Volatility` * `3-States Model: High, Medium & Low Volatility` * `4-States Model: High & Low Volatility With Corrections` * `AP (Average Probability of High Volatility)` * `JP (Joint Probability of High Volatility)` * *References*: [Billio et al. (2010)](https://www.bis.org/bcbs/events/sfrworkshopprogramme/billio.pdf), [Abdymomunov (2011)](https://doi.org/10.2139/ssrn.1972255) * **SPILLOVER MEASURES** * `SI (Spillover Index)` * `Spillovers From & To` * `Net Spillovers` * *References*: [Diebold & Yilmaz (2008)](https://doi.org/10.1111/j.1468-0297.2008.02208.x), [Diebold & Yilmaz (2012)](https://doi.org/10.1016/j.ijforecast.2011.02.006), [Diebold & Yilmaz (2014)](https://doi.org/10.1016/j.jeconom.2014.04.012) * **TAIL DEPENDENCE MEASURES** * `ACHI (Average Chi)` by [Balla et al. (2014)](https://doi.org/10.1016/j.jfs.2014.10.002) * `ADR (Asymptotic Dependence Rate)` by [Balla et al. (2014)](https://doi.org/10.1016/j.jfs.2014.10.002) * `FRM (Financial Risk Meter)` by [Mihoci et al. (2020)](https://doi.org/10.1108/S0731-905320200000042016) Some of the aforementioned models have been improved or extended according to the methodologies described in the [V-Lab Documentation](https://vlab.stern.nyu.edu/docs), which represents a great source of systemic risk measurement. The project has been published in `"MATLAB Digest | Financial Services | May 2019"`. If you found it useful to you, please consider making a donation to support its maintenance and development: [](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=CTTYMG23C36G6) ## Requirements The minimum required `MATLAB` version is `R2014b`. In addition, the following products and toolboxes must be installed in order to properly execute the script: * Computer Vision System Toolbox * Curve Fitting Toolbox * Econometrics Toolbox * Financial Toolbox * Image Processing Toolbox * Optimization Toolbox * Parallel Computing Toolbox * Statistics and Machine Learning Toolbox * System Identification Toolbox ## Usage 1. Create a properly structured database (see the section below). 1. Execute one of the following scripts (they can be edited following your needs and criteria): * `run.m` to perform the computation of systemic risk measures; * `analyze.m` to analyze previously computed systemic risk measures. ## Dataset Datasets must be built following the structure of default ones included in every release of the framework (see `Datasets` folder). Below a list of the supported Excel sheets and their respective content: * **Shares:** prices or returns expressed in logarithmic scale of the benchmark index (the column can be labeled with any desired name and must be placed just after observation dates) and the firms, with daily frequency. * **Volumes:** trading volume of the firms expressed in currency amount, with daily frequency. * **Capitalizations:** market capitalization of the firms, with daily frequency. * **CDS:** the risk-free rate expressed in decimals (the column must be called `RF` and must be placed just after observation dates) and the credit default swap spreads of the firms expressed in basis points, with daily frequency. * **Balance Sheet Components:** the balance sheet components of the firms expressed in omogeneous observations frequency, currency and scale, structured as below: * **Assets:** the book value of assets. * **Equity:** the book value of equity. * **Separate Accounts:** the separate accounts of insurance firms. * **State Variables:** systemic state variables, with daily frequency. * **Groups:** group definitions are based on three-value tuples where the `Name` field represents the group names, the `Short Name` field represents the group acronyms and the `Count` field represents the number of firms to include in the group. The sum of the `Count` fields must be equal to the number of firms. For example, the following groups definition: > Firms in the Shares Sheet: A, B, C, D, E, F, G, H > Insurance Companies: 2 > Investment Banks: 2 > Commercial Banks: 3 > Government-sponsored Enterprises: 1 produces the following outcome: > "Insurance Companies" contains A and B > "Investment Banks" contains C and D > "Commercial Banks" contains E,