M-SD3 Model: A Multi-Dimensional Risk Decomposition

2018 ◽  
Author(s):  
Domenico Mignacca
Keyword(s):  
Risk Decomposition

scholarly journals How Fraud Risk Decomposition Affects Auditors' Fraud Risk Assessments

2020 ◽  
Vol 14 (1) ◽  
pp. P26-P32
Author(s):  
Chad A. Simon ◽  
Jason L. Smith ◽  
Mark F. Zimbelman
Keyword(s):  
High Risk ◽  
Unintended Consequences ◽  
Risk Assessments ◽  
Risk Decomposition ◽  
Fraud Risk ◽  
Trade Offs ◽  
Auditing Standards ◽  
Fraud Risk Assessments

SUMMARY In this paper, we provide a practitioner summary of our paper “The Influence of Judgment Decomposition on Auditors' Fraud Risk Assessments: Some Trade-Offs” (Simon, Smith, and Zimbelman 2018). In that study, we investigate potential unintended consequences from current auditing guidance on risk assessments. Specifically, auditing standards recommend separate assessments of the likelihood and magnitude of risks (hereafter, LM decomposition) when auditors assess risk. Our study involved several experiments, including one with experienced auditors, where we found evidence that LM decomposition leads auditors to be less concerned about high-risk fraud schemes relative to auditors who make holistic risk assessments. Our other experiments involved non-auditing settings and replicated this finding while exploring potential explanations for it. After providing a summary of our study and its results, we offer concluding remarks on the potential implications of our findings.

Portfolio Optimization with Risk Decomposition

2017 ◽  
Vol 2017 (5) ◽  
pp. 61-85
Author(s):  
Konstantin Asaturov
Keyword(s):  
Portfolio Optimization ◽  
Performance Indicators ◽  
Equity Market ◽  
Optimization Approach ◽  
Risk Decomposition ◽  
Market Index ◽  
Specific Risk ◽  
Capm Model

The paper offers the modification of traditional portfolio optimization approach to construct the portfolio with possibility to control both systematic and specific risk (portfolio with risk decomposition). Built on modern econometric tools, the author estimates and forecasts the dynamics of alphas and betas of stocks in the frame of CAPM model, which are further applied for portfolio optimization. The closing weekly prices of 10 Australian stocks and ASX Index as the market index during the period from July 2000 to July 2016 were used. Within the sample there is no evidence of arbitrage on the Australian equity market employing neutral beta portfolio. The study confirms that portfolios with risk decomposition outperform Markowitz’s one according to various performance indicators.

scholarly journals PRACTITIONER SUMMARY How Fraud Risk Decomposition Affects Auditors' Fraud Risk Assessments

2020 ◽  
pp. 0000-0000
Author(s):  
Chad A. Simon ◽  
Jason L. Smith ◽  
Mark F. Zimbelman
Keyword(s):  
High Risk ◽  
Unintended Consequences ◽  
Risk Assessments ◽  
Risk Decomposition ◽  
Fraud Risk ◽  
Auditing Standards ◽  
Fraud Risk Assessments

In this paper, we provide a practitioner summary of our paper "The Influence of Judgment Decomposition on Auditors' Fraud Risk Assessments: Some Tradeoffs" (Simon, Smith, and Zimbelman 2018). In that study, we investigate potential unintended consequences from current auditing guidance on risk assessments. Specifically, auditing standards recommend separate assessments of the likelihood and magnitude of risks (hereafter, LM decomposition) when auditors assess risk. Our study involved several experiments, including one with experienced auditors, where we found evidence that LM decomposition leads auditors to be less concerned about high-risk fraud schemes relative to auditors who make holistic risk assessments. Our other experiments involved non-auditing settings and replicated this finding while exploring potential explanations for it. After providing a summary of our study and its results, we offer concluding remarks on the potential implications of our findings.

scholarly journals A New Approach to Risk Attribution and Its Application in Credit Risk Analysis

Risks ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 65
Author(s):  
Christoph Frei
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Credit Risk ◽  
Driving Factors ◽  
New Approach ◽  
Risk Decomposition ◽  
Risk Attribution ◽  
Credit Risk Analysis ◽  
A Company ◽  
Over Time

How can risk of a company be allocated to its divisions and attributed to risk factors? The Euler principle allows for an economically justified allocation of risk to different divisions. We introduce a method that generalizes the Euler principle to attribute risk to its driving factors when these factors affect losses in a nonlinear way. The method splits loss contributions over time and is straightforward to implement. We show in an example how this risk decomposition can be applied in the context of credit risk.

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