Multiple Risk Measures Research Articles

Offsetable Derivatives and Investor Risk Assessment

U.S. generally accepted accounting principles (GAAP) allows banks to offset derivative assets against derivative liabilities with the same counterparty and report only the net amount on the balance sheet. Derivative offsetting under international financial reporting standards (IFRS) is much more restrictive, resulting in the single largest difference in balance sheet presentation between U.S. GAAP and IFRS. Two important factors dominate the standard-setting discussion on this issue: (1) whether these derivatives are informative about bank risk and (2) whether disclosing them substitutes for recognition on the balance sheet. Using a hand-collected global sample of banks, we first show that offsetable derivatives are positively associated with bank risk, based on multiple risk measures, suggesting that these derivatives are informative about bank risk. Next, exploiting the differential accounting treatment across U.S. GAAP and IFRS banks, we find that disclosure versus recognition of offsetable derivatives matters for the risk assessment of equity investors but not for that of (more sophisticated) credit default swap investors. Additional tests corroborate the inference that investor sophistication helps explain the differential investor assessment of recognized versus disclosed offsetable derivatives. Collectively, our findings suggest that offsetable derivatives convey information about bank risk and that, for less sophisticated investors, disclosing them may not substitute for recognizing them. This paper was accepted by Eric So, accounting. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4831 .

CRYPTO PORTFOLIO OPTIMIZATION THROUGH LENS OF TAIL RISK AND VARIANCE MEASURES

The choice of an adequate risk measure in portfolio optimization depends to a large extent on the characteristics and dynamics of the underlying assets. For investors and asset managers, a range of potential market risks provides much- needed insights into the optimization of their portfolio of assets. Since this paper focuses on multiple risk measures, it presents the investors with a better insight into the potential magnitude of the risk they are faced with. Since the risk-reward optimization target can be adjusted for a broad choice of risk measures in this paper we will test the performance of the classical risk measure i.e. standard deviation versus a tail risk measure such as expected tail loss (ETL). Our goal is to find which of the two offers the better performance for a portfolio of cryptocurrencies and if the differences are statistically significant. The setup for our analysis is testing two optimization targets (MinVar and MinETL) on 10 portfolios of cryptocurrencies randomly chosen from a sample of 70 cryptocurrencies with the highest market capitalization.

Stock Efficiency Evaluation Based on Multiple Risk Measures: A DEA-Like Envelopment Approach

Stock Efficiency Evaluation Based on Multiple Risk Measures: A DEA-Like Envelopment Approach

Deep Reinforcement Learning for Trading—A Critical Survey

Deep reinforcement learning (DRL) has achieved significant results in many machine learning (ML) benchmarks. In this short survey, we provide an overview of DRL applied to trading on financial markets with the purpose of unravelling common structures used in the trading community using DRL, as well as discovering common issues and limitations of such approaches. We include also a short corpus summarization using Google Scholar. Moreover, we discuss how one can use hierarchy for dividing the problem space, as well as using model-based RL to learn a world model of the trading environment which can be used for prediction. In addition, multiple risk measures are defined and discussed, which not only provide a way of quantifying the performance of various algorithms, but they can also act as (dense) reward-shaping mechanisms for the agent. We discuss in detail the various state representations used for financial markets, which we consider critical for the success and efficiency of such DRL agents. The market in focus for this survey is the cryptocurrency market; the results of this survey are two-fold: firstly, to find the most promising directions for further research and secondly, to show how a lack of consistency in the community can significantly impede research and the development of DRL agents for trading.

The utility of Basel III rules on excessive violations of internal risk models

The Basel III international regulatory framework for banks calls for the adoption of historical empirical distributions should a bank’s internal models fail in a significant way. If the historical distribution is the fallback to an internal model, it is important to know if the empirical distribution gives a better view of future reality. In this paper, we look at the efficacy of risk measures on energy markets and across several different stock market indexes. We calculate both the value-at-risk (VaR) and the expected shortfall (ES) on each of these data sets as well as on selected portfolios of these assets. We consider several different durations and levels for the historical risk measures, looking at the number of violations that Basel III measures for its requirements. We also calculate different error measurements for the VaR and ES. Using our results, we make some recommendations concerning the Basel III framework. The computations here strongly indicate that the Bank for International Settlements should adopt harsher guidelines than are presently in place. Further, we would offer firms the option of using internal models and reporting multiple risk measures or using historical empirical measures and only reporting a single measure.

An exact solution to a robust portfolio choice problem with multiple risk measures under ambiguous distribution

This paper proposes a unified framework to solve distributionally robust mean-risk optimization problem that simultaneously uses variance, value-at-risk (VaR) and conditional value-at-risk (CVaR) as a triple-risk measure. It provides investors with more flexibility to find portfolios in the sense that it allows investors to optimize a return-risk profile in the presence of estimation error. We derive a closed-form expression for the optimal portfolio strategy to the robust mean-multiple risk portfolio selection model under distribution and mean return ambiguity (RMP). Specially, the robust mean-variance, robust maximum return, robust minimum VaR and robust minimum CVaR efficient portfolios are all special instances of RMP portfolios. We analytically and numerically show that the resulting portfolio weight converges to the minimum variance portfolio when the level of ambiguity aversion is in a high value. Using numerical experiment with simulated data, we demonstrate that our robust portfolios under ambiguity are more stable over time than the non-robust portfolios.

Multiple risk measures for multivariate dynamic heavy–tailed models

The dynamic evolution of tail–risk interdependence among institutions is of primary importance when extreme events such as financial crisis occur. In this paper we introduce two new risk measures that generalise the Conditional Value–at–Risk and the Conditional Expected Shortfall in a multiple setting. The proposed risk measures aim to capture extreme tail co–movements among several multivariate connected market participants experiencing contemporaneous distress instances. Analytical expressions for the risk measures are obtained under a parametric model that postulates a joint dynamic evolution of the underlying institutions' losses and gains. We consider a multivariate Student–t version of Markov Switching models as a robust alternative to the usual multivariate Gaussian specification, accounting for heavy–tails and time varying non–linear correlations. An empirical application to US banks is considered to show that our model–based risk measurement framework provides a better characterisation of the dynamic evolution of the overall risk of a financial system and a more complete picture of how the risk spreads among institutions.

Dynamic mean-risk portfolio selection with multiple risk measures in continuous-time

While our society began to recognize the importance to balance the risk performance under different risk measures, the existing literature has confined its research work only under a static mean-risk framework. This paper represents the first attempt to incorporate multiple risk measures into dynamicportfolio selection. More specifically, we investigate the dynamic mean-variance-CVaR (Conditional value at Risk) formulation and the dynamic mean-variance-SFP (Safety-First Principle) formulation in a continuous-time setting, and derive the analytical solutions for both problems. Combining a downside risk measure with the variance (the second order central moment) in a dynamic mean-risk portfolio selection model helps investors control both a symmetric central risk measure and an asymmetric catastrophic downside risk. We find that the optimal portfolio policy derived from our mean-multiple risk portfolio optimization models exhibits a feature of curved V-shape. Our numerical experiments using real market data clearly demonstrate a dominance relationship of our dynamic mean-multiple risk portfolio policies over the static buy-and-hold portfolio policy.

Social Inequality in Cigarette Consumption, Cigarette Dependence, and Intention to Quit among Norwegian Smokers.

Background. The study aim was to examine the influence of education and income on multiple measures of risk of smoking continuation. Methods. Three logistic regression models were run on cigarette consumption, dependence, and intention to quit based on nationally representative samples (2007–2012) of approximately 1 200 current smokers aged 30–66 years in Norway. Results. The relative risk ratio for current versus never smokers was RRR 5.37, 95% CI [4.26–6.77] among individuals with low educational level versus high and RRR 1.53, 95% CI [1.14–2.06] in the low-income group versus high (adjusted model). Low educational level was associated with high cigarette consumption, high cigarette dependence, and no intention to quit. The difference in predicted probability for having high cigarette consumption, high cigarette dependence, and no intention to quit were in the range of 10–20 percentage points between smokers with low versus those with high educational level. A significant difference between low- and high-income levels was observed for intention to quit. The effect of education on high consumption and dependence was mainly found in smokers with high income. Conclusion. Increased effort to combat social differences in smoking behaviour is needed. Implementation of smoking cessation programmes with high reach among low socioeconomic groups is recommended.

Dynamic Mean-Risk Portfolio Selection with Multiple Risk Measures in Continuous-Time

Different risk measures emphasize different aspects of a random loss. If we examine the investment performance according to different spectra of the risk measures, any policy generated from a mean-risk portfolio model with a sole risk measure may not be a good choice. We study in this paper the dynamic portfolio selection problem with multiple risk measures in a continuous-time setting. More specifically, we investigate the dynamic mean-variance-CVaR (Conditional value at Risk) formulation and the dynamic mean-variance-SFP (Safety-First-Principle) formulation, and derive analytical solutions for both problems, when all the market parameters are deterministic. Combining a downside risk measure with the variance (the second order central moment) in a dynamic mean-risk portfolio selection model helps investors control both the symmetric central risk measure and the asymmetric downside risk at the tail part of the loss. We find that the optimal portfolio policy derived from our mean-multiple risk portfolio optimization model exhibits a feature of two-side threshold type, i.e., when the current wealth level is either below or above certain threshold, the optimal policy would dictate an increase in the allocation of the risky assets. Our numerical experiments using real market data further demonstrate that our dynamic mean-multiple risk portfolio models reduce significantly both the variance and the downside risk, when compared with the static buy-and-hold portfolio policy.

Perceived risk following melanoma genetic testing: a 2-year prospective study distinguishing subjective estimates from recall.

A major goal of predictive genetic testing is to alert people to their risk before illness onset; however, little is known about how risk perceptions change following genetic testing and whether information is recalled accurately over time. In the United States, a CDKN2A/p16 mutation confers 76% lifetime risk of melanoma. Following genetic counseling and test reporting, subjective risk estimates and recall of counselor-provided risk estimates were assessed 5 times over the next 2years among 60 adult members of 2 extended CDKN2A/p16 kindreds. No sustained changes from baseline in risk perceptions were reported. Unaffected carriers (n = 15) consistently reported significantly lower subjective risk estimates (46%) than they were actually given (76%, p < 0.001) or recalled having been given (60%, p < 0.001). Noncarriers' (n = 27) risk estimates decreased following results disclosure, but rebounded, with both subjective and recalled estimates subsequently exceeding what they were told by the counselor (both ps < 0.001). Affected carriers' (n = 18) risk estimates for developing a new melanoma corresponded well to counselor-provided information (p = 0.362). For all 3 patient groups, results were consistent across multiple risk measures and remained similar when demographic, phenotypic, and baseline behavioral contributors to melanoma risk were statistically controlled. These findings are consistent with other studies of risk perception, but additional studies of more diverse populations are needed to understand the reasons behind both the persistence of initial risk estimates and their divergence from information provided by the counselor during genetic counseling. Additionally, determining whether holding subjective risk perceptions that differ from counselor-provided information ultimately affects adherence to management recommendations will help guide the presentation of risk information in genetic counseling practice.

On the necessity of five risk measures

The banking systems that deal with risk management depend on underlying risk measures. Following the Basel II accord, there are two separate methods by which banks may determine their capital requirement. The Value at Risk measure plays an important role in computing the capital for both approaches. In this paper we analyze the errors produced by using this measure. We discuss other measures, demonstrating their strengths and shortcomings. We give examples, showing the need for the information from multiple risk measures in order to determine a bank’s loss distribution. We conclude by suggesting a regulatory requirement of multiple risk measures being reported by banks, giving specific recommendations.

Cumulative risk and adolescent's internalizing and externalizing problems: The mediating roles of maternal responsiveness and self-regulation.

The purpose of the present study was to examine longitudinal associations among maternal responsiveness, self-regulation, and behavioral adjustment in adolescents. The authors used structural equation modeling to test a model that demonstrates that the effects of early cumulative risk on behavioral problems is mediated by maternal responsiveness and self-regulation. Furthermore, the authors examine the contributions of cumulative risk and maternal responsiveness on children's self-regulatory abilities. The study uses a 3-wave longitudinal design with multiple measures of risk and self-regulation from multiple observers. Data were collected from adolescents (N = 265, male = 140) and their parents at age 9, 13, and 17. Results suggest that the mediation hypothesis held true for externalizing, but not internalizing problems. Furthermore, cumulative risk and maternal responsiveness contributed uniquely to children's self-regulation abilities. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Are Lifecycle Funds Getting a Bum Rap? A Comprehensive Comparison of Lifecycle versus Lifestyle Retirement Strategies from Accumulation through Withdrawal

In an effort to determine whether recent criticism regarding the efficacy of lifecycle mutual funds is justified, this article makes a robust comparison of two glidepath strategies commonly employed in lifecycle funds, both with each other and with a range of constant allocation portfolios designed to simulate risk-based lifestyle mutual funds. A concerted effort is made to make the model design realistic, and the analysis considers the lifecycle and lifestyle strategies through the accumulation and withdrawal phases of retirement planning. The results tend to cast a favorable light on lifecycle funds and suggest that recent research critical of lifecycle funds may be too narrowly focused. By considering a robust range of accumulation and withdrawal scenarios as well as multiple measures of risk, this analysis finds that lifecycle funds may be a rational choice for a surprisingly wide spectrum of workers and retirees. <b>TOPICS:</b>Retirement, mutual funds/passive investing/indexing, performance measurement

Estimating the Equity Risk Premium with Time-Series Forecasts of Earnings

The size of the equity risk premium remains an unanswered question in the accounting and finance literature. This study proposes a new approach to reverse-engineer the equity risk premium, distinct from prior research, in that it does not rely on analysts’ forecasts to proxy for the market’s earnings expectations. That I instead use time-series earnings forecasts allows an investigation of the equity risk premium across a broader cross-section of firms, including smaller firms that are not covered by analysts. This study finds that risk premia are significantly higher for firms not followed by analysts. This suggests that studies requiring analysts’ earnings forecasts to estimate the equity risk premium have likely underestimated its overall level. Additional validity tests on my firm- and year-specific risk premium estimates reveal that these estimates consistently and predictably relate to multiple measures of risk, particularly for firms not followed by analysts.

Thresholding Events of Extreme in Simultaneous Monitoring of Multiple Risks

This article develops a threshold system for monitoring airline performance. This threshold system divides the sample space into regions with increasing levels of risk and allows instant assessments of risk level of any observed airline performance. Of particular concern is the performance with extreme risk. In this article, a multivariate extreme value theory approach is used to establish thresholds for signaling varying levels of extremeness in the context of simultaneous monitoring of multiple risk measures. The threshold system is justified in terms of multivariate extreme quantiles, and its sample estimator is shown to be consistent. This threshold system applies to general extreme risk management. Finally, a simulation and comparison study demonstrates the good performance of the proposed multivariate extreme quantile estimator. Supplemental materials providing technical details are available online.

Prostate-Specific Antigen: A Misused and Maligned Prostate Cancer Biomarker

Prostate-Specific Antigen: A Misused and Maligned Prostate Cancer Biomarker

Comparison of Multiple Risk Measures After Weight Loss in Healthy Overweight or Obese Adults

Comparison of Multiple Risk Measures After Weight Loss in Healthy Overweight or Obese Adults

Advertising Agency Philosophies and Employee Risk Taking

On the basis of an exploratory survey of executives from a cross-section of U.S. advertising agencies, this article examines the relationship between agency creative philosophies and agent creative risk taking. The natures of both creative risk and agency philosophy are discussed. Multiple measures of risk taking are applied and the findings suggest that agency executives working in agencies with clear identities are more likely to take risks than are those in agencies without such identities (hybrid philosophies), but not for all measures of risk. The extent to which the size of client plays a role also is assessed. After an assessment of the findings, limitations and suggestions for further research are discussed.