Home bias in financial markets: robust satisficing with info gaps

The observed patterns of equity portfolio allocation around the world are at odds with predictions from a capital asset pricing model (CAPM). What has come to be called the “home-bias” phenomenon is that investors tend to hold a disproportionately large share of their equity portfolio in home country stocks as compared with predictions of the CAPM. This paper provides an explanation of the home-bias phenomenon based on information-gap decision theory. The decision concept that is used here is that profit is satisficed and robustness to uncertainty is maximized rather than expected profit being maximized. Furthermore, uncertainty is modeled nonprobabilistically with info-gap models of uncertainty, which can be viewed as a possible quantification of Knightian uncertainty.

Price-Based vs. Quantity-Based Environmental Regulation under Knightian Uncertainty: An Info-Gap Robust Satisficing Perspective

Conventional wisdom among environmental economists is that the relative slopes of the marginal social benefit and marginal social cost functions determine whether a price-based or quantity-based environmental regulation leads to higher expected social welfare. We revisit the choice between price-based vs. quantity-based environmental regulation under Knightian uncertainty; that is, when uncertainty cannot be modeled with known probability distributions. Under these circumstances, the policy objective cannot be to maximize the expected net benefits of emissions control. Instead, we evaluate an emissions tax and an aggregate abatement standard in terms of maximizing the range of uncertainty under which the welfare loss from error in the estimates of the marginal benefits and costs of emissions control can be limited. The main result of our work is that the same criterion involving the relative slopes of the marginal benefit and cost functions determines whether price-based or quantity-based control is more robust to unstructured uncertainty. Hence, not only does the relative slopes criterion lead to the policy that maximizes the expected net benefits of control under structured uncertainty, it also leads to the policy that maximizes robustness to unstructured uncertainty.emissions control, environmental regulation, info-gap, Knightian uncertainty, robustness, satisficing

Reasoned decision making without math? Adaptability and robustness in response to surprise

Many real-world planning and decision problems are far too uncertain, too variable, and too complicated to support realistic mathematical models. Nonetheless, we explain the usefulness, in these situations, of qualitative insights from mathematical decision theory. We demonstrate the integration of info-gap robustness in decision problems in which surprise and ignorance are predominant and where personal and collective psychological factors are critical. We present practical guidelines for employing adaptable-choice strategies as a proxy for robustness against uncertainty. These guidelines include being prepared for more surprises than we intuitively expect, retaining sufficiently many options to avoid premature closure and conflicts among preferences, and prioritizing outcomes that are steerable, whose consequences are observable, and that do not entail sunk costs, resource depletion, or high transition costs. We illustrate these concepts and guidelines with the example of the medical management of the 2003 SARS outbreak in Vietnam

Managing uncertainty through robust-satisficing monetary policy

We employ information-gap decision theory to derive a robust monetary policy response to Knightian parameter uncertainty. This approach provides a quantitative answer to the question: For a specified policy, how much can our models and data err or vary, without rendering the outcome of that policy unacceptable to a policymaker? For a given acceptable level of performance, the policymaker selects the policy that delivers acceptable performance under the greatest range of uncertainty. We show that such information-gap robustness is a proxy for probability of policy success. Hence, policies that are likely to succeed can be identified without knowing the probability distribution. We adopt this approach to investigate empirically the robust monetary policy response to a supply shock with an uncertain degree of persistence.Knightian uncertainty, Monetary policy, Info-gap decision theory.

Fundamental uncertainty and unconventional monetary policy: an info-gap approach. Bruegel Working Paper Issue 1 / 2017

This paper applies the info-gap approach to the unconventional monetary policy of the Eurosystem and so takes into account the fundamental uncertainty on inflation shocks and the transmission mechanism. The outcomes show that a more demanding monetary strategy, in terms of lower tolerance for output and inflation gaps, entails less robustness against uncertainty, particularly if financial variables are taken into account. Augmenting the Taylor rule with a financial variable leads to a smaller loss of robustness than taking into account the effect of financial imbalances on the economy. However, in some situations, the augmented model is more robust than the baseline model. A conclusion from our framework is that including financial imbalances in the monetary policy objective does not necessarily increase policy robustness, and may even decrease it

Brain Diffusivity in Infants With Hypoxic-Ischemic Encephalopathy Following Whole Body Hypothermia: Preliminary Results

Abstract Hypoxic-ischemic encephalopathy is an important cause of neuropsychological deficits. Little is known about brain diffusivity in these infants following cooling and its potential in predicting outcome. Diffusion tensor imaging was applied to 3 groups: (1) three infants with hypoxic-ischemic encephalopathy: cooled; (2) three infants with hypoxic-ischemic encephalopathy: noncooled; and (3) four controls. Diffusivity values at the corticospinal tract, thalamus, and putamen were correlated with Apgar scores and early neurodevelopmental outcome. While cooled infants exhibited lower Apgar scores than noncooled infants, their developmental scores at a mean age of 8 months were higher. All groups differed in their diffusivity values with the cooled infants showing better values compared with the noncooled, correlating with early neurodevelopmental outcome. These preliminary results indicate that diffusion tensor imaging performed at an early age in infants with hypoxic-ischemic encephalopathy may forecast clinical outcome and support the neuroprotective effect of hypothermia treatment