Optimal Prevention for Correlated Risks

2013 ◽  
Author(s):  
Christophe Courbage ◽  
Henri Louberge ◽  
Richard Peter
Keyword(s):  
Correlated Risks

Correlated risks and the value of information

2010 ◽  
Vol 102 (1) ◽  
pp. 77-87 ◽  
Author(s):  
Louis Eeckhoudt ◽  
Alban Thomas ◽  
Nicolas Treich
Keyword(s):  
Value Of Information ◽  
Correlated Risks

History of spouse violence against mother: Correlated risks and unique effects in child mental health

1994 ◽  
Vol 9 (1) ◽  
pp. 79-98 ◽  
Author(s):  
Steve Spaccarelli ◽  
Irwin N. Sandler ◽  
Mark Roosa
Keyword(s):  
Mental Health ◽  
Child Mental Health ◽  
Correlated Risks ◽  
History Of

Stochastic Bounds for Discrete-time Claim Processes with Correlated Risks

2004 ◽  
Vol 2004 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Rosa E. Lillo ◽  
Patrizia Semeraro
Keyword(s):  
Discrete Time ◽  
Correlated Risks

Pricing Insurance and Warranties: Ambiguity and Correlated Risks

1992 ◽  
Vol 17 (1) ◽  
pp. 35-60 ◽  
Author(s):  
Robin M. Hogarth ◽  
Howard Kunreuther
Keyword(s):  
Correlated Risks

Sizing Up Categories

2021 ◽  
Vol 22 (1) ◽  
pp. 1-30
Author(s):  
Lee Anne Fennell
Keyword(s):  
Adverse Selection ◽  
Classification System ◽  
Strategic Behavior ◽  
Category Membership ◽  
Information Environment ◽  
Fine Grained ◽  
The World ◽  
Correlated Risks

Abstract Categories intentionally create discontinuities. By breaking the world up into cognizable chunks, they simplify the information environment. But the signals they provide may be inaccurate or scrambled by strategic behavior. This Article considers how law might approach the problem of optimal categorization, given the role of categories in managing and transmitting information. It proceeds from the observation that high categorization costs can be addressed through two opposite strategies—making classifications more fine-grained (splitting), and making classifications more encompassing (lumping). Although continuizing and other forms of splitting offer intuitive answers to inaccurate classification and gaming along category lines, lumping is sometimes a better solution. If category membership carries multiple and offsetting implications, the incentive to manipulate the classification system is dampened. To take a simple example, insurance that covers only one risk is more vulnerable to adverse selection than is an insurance arrangement that covers two inversely correlated risks. Making categories larger, more durable, and more heterogeneous can produce such offsets. These and other forms of bundling can arrest damaging instabilities in categorization.

scholarly journals MODELLING ON-FARM DIVERSIFICATION THROUGH PORTFOLIO OPTIMIZATION AND GOAL PROGRAMMING: A CASE STUDY FROM BOLIVIA

AGROFOR ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Andrea MARKOS
Keyword(s):  
Low Cost ◽  
Rural Poverty ◽  
Agricultural Risk ◽  
Farm Diversification ◽  
Watershed Conservation ◽  
Rural Livelihood ◽  
Correlated Risks ◽  
Rural Context ◽  
On Farm

Modern Portfolio Theory provides a theoretical framework for agricultural risk reduction. Powerful yet accessible tools have been developed to optimize scarce capital/labor allocation to increase returns and reduce correlated risks via diversification. Such tools are used to assess rural livelihood diversification induced by an incentive-based program for watershed conservation piloted between 2003 and 2011 in a context of rural poverty in Bolivia. The tools assembled and tested in this study may provide low-cost diagnostics to improve implementers’ understanding of risks and returns in a specific rural context. Comparing alternative portfolio frontiers may represent a useful and transformative tool to understand socio-ecological systems such as watersheds, facilitating regime shifts that benefit ecosystem services and livelihoods.

scholarly journals Vulnerability and mutual insurance

2021 ◽  
Author(s):  
Roland Eisen
Keyword(s):  
Mutual Insurance ◽  
Correlated Risks

AbstractVulnerability comes, according to Orio Giarini, with two risks: human-made risks, also called entrepreneurial risks, and natural or pure risks such as accidents and earthquakes. Both types of risk are growing in dimension and are increasingly interrelated. To control the vulnerability, sophisticated insurance products are called for. Here, mutual insurance is relevant, in particular when risks are large, probabilities uncertain or unknown, and events interrelated or correlated. In this paper the following three examples are discussed and the advantages of mutual insurance are shown: unknown probabilities connected with unforeseeable events, correlated risks and macroeconomic or demographic risks.

scholarly journals Correlated risks vs contagion in stochastic transition models

2013 ◽  
Vol 37 (11) ◽  
pp. 2241-2269 ◽  
Author(s):  
Patrick Gagliardini ◽  
Christian Gouriéroux
Keyword(s):  
Stochastic Transition ◽  
Correlated Risks ◽  
Transition Models

scholarly journals Correlation Misperception in Choice

2017 ◽  
Vol 107 (4) ◽  
pp. 1264-1292 ◽  
Author(s):  
Andrew Ellis ◽  
Michele Piccione
Keyword(s):  
Decision Maker ◽  
Expected Utility ◽  
Joint Distribution ◽  
Subjective Expected Utility ◽  
Theoretic Analysis ◽  
Correlated Risks ◽  
Flexible Model

We present a decision-theoretic analysis of an agent's understanding of the interdependencies in her choices. We provide the foundations for a simple and flexible model that allows the misperception of correlated risks. We introduce a framework in which the decision maker chooses a portfolio of assets among which she may misperceive the joint returns, and present simple axioms equivalent to a representation in which she attaches a probability to each possible joint distribution over returns and then maximizes subjective expected utility using her ( possibly misspecified) beliefs. (JEL D11, D81, D83, G11)

scholarly journals Equity Risk and Return across Hidden Market Regimes

Risks ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 188
Author(s):  
Dmitry A. Endovitsky ◽  
Viacheslav V. Korotkikh ◽  
Denis A. Khripushin
Keyword(s):  
Risk And Return ◽  
Day Trading ◽  
Equity Risk ◽  
Significant Difference ◽  
Trading Profits ◽  
Sample Data ◽  
Correlated Risks ◽  
Market Regime ◽  
Lagged Effects ◽  
Market Regimes

The key to understanding the dynamics of stock markets, particularly the mechanisms of their changes, is in the concept of the market regime. It is regarded as a regular transition from one state to another. Although the market agenda is never the same, its functioning regime allows us to reveal the logic of its development. The article employs the concept of financial turbulence to identify hidden market regimes. These are revealed through the ratio of the components, which describe single changes of correlated risks and volatility. The combinations of typical and atypical variates of correlational and magnitude components of financial turbulence allowed four hidden regimes to be revealed. These were arranged by the degree of financial turbulence, conceptually analyzed and assessed from the perspective of their duration. The empirical data demonstrated ETF day trading profits for S&P 500 sectors, covering the period of January 1998–August 2020, as well as day trade profits of the Russian blue chips within the period of October 2006–February 2021. The results show a significant difference in regard to the market performance and volatility, which depend on hidden regimes. Both sample data groups demonstrated similar contemporaneous and lagged effects, which allows the prediction of volatility jumps in the periods following atypical correlations.

Sign in / Sign up

Export Citation Format

Share Document