Estimating the Information Rate of a Channel with Classical Input and Output and a Quantum State (Extended Version)

We consider the problem of transmitting classical information over a time-invariant channel with memory. A popular class of time-invariant channels with memory are finite-state-machine channels, where a \emph{classical} state evolves over time and governs the relationship between the classical input and the classical output of the channel. For such channels, various techniques have been developed for estimating and bounding the information rate. In this paper we consider a class of time-invariant channels where a \emph{quantum} state evolves over time and governs the relationship between the classical input and the classical output of the channel. We propose algorithms for estimating and bounding the information rate of such channels. In particular, we discuss suitable graphical models for doing the relevant computations.Comment: This is an extended version of a paper that appears in Proc. 2017 IEEE International Symposium on Information Theory, Aachen, Germany, June 201

Impact of information cost and switching of trading strategies in an artificial stock market

This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers.Comment: 15 pages, 9 figures, Physica A, 201

The Financing of Innovation: Learning and Stopping

This paper considers the financing of a research project under uncertainty about the time of completion and the probability of eventual success. We distinguish between two financing modes, namely relationship financing, where the allocation decision of the entrepreneur is observable, and arm's length financing, where it is unobservable. We find that equilibrium funding stops altogether too early relative to the efficient stopping time in both financing modes. The rate at which funding is released becomes tighter over time under relationship financing, and looser under arm's length financing. The trade-off in the choice of financing modes is between lack of commitment with relationship financing and information rents with arm's length financing.Innovation, venture capital, relationship financing, arm's length financing, learning, time-consistency, stopping, renegotiation-proofness

Flexible Envelope Request Notation (FERN)

The following topics are presented in view graph form and include the following: scheduling application; the motivation for the Flexible Envelope Request Notation (FERN); characteristics of FERN; types of information needed in requests; where information is stored in requests; FERN structures; generic requests; resource availability for pooled resources; expressive notation; temporal constraints; time formats; changes to FERN; sample FERN requests; the temporal relationship between two steps; maximum activity length to limit step delays; alternative requests; the temporal relationship between two activities; and idle resource usage between steps

A comprehensive study of personal and social information use in female brown-headed cowbirds, Molothrus ater

Brood parasites face considerable cognitive challenges when locating and selecting host nests for their young. One aspect of this challenge is determining how to use different sources of information to make decisions regarding the quality of a prospective nest. Here we investigate how female-brown-headed cowbirds, Molothrus ater, use information when prospecting for nests, and then expand upon this to investigate decisions related to foraging. In chapter 1, we demonstrated female could use social information acquired from observing the nest prospecting patterns of conspecifics to influence their own patterns of nest selection. Furthermore, we found a negative relationship between a female’s accuracy at using personal information and her tendency to copy others. In chapter 2, we found the females were able to use social information in a foraging setting as well. The female’s accuracy using personal information remained consistent across nest prospecting and foraging contexts however, the relationship between accuracy and tendency to copy others drastically reversed. A follow up experiment revealed the likely possibility that the differing relationship between personal and social information use depended on the degree of conflict that existed between the two types of information. In chapter 3, we redeveloped and implemented a new RFID tracking technology allowing us to investigate how the cognitive strategies from chapters 1 and 2 translated to a naturalistic, socially complex breeding environment. We found female cowbirds who spent more time prospecting, produced a greater quantity of eggs and demonstrated high accuracy scores during chapter 1 and 2, whereas females who relied on copying others spent significantly less time prospecting and demonstrated lower laying accuracy scores. By demonstrating how individuals’ cognitive strategies relate across context and translate to a socially complex setting, we have demonstrated the importance of examining behaviour in both of these settings and our RFID tracking technology provides researchers with the framework to effectively study this in the future

The relationship between time series models for water table depth and physical information

The relationship between parameters of autoregressive moving average exogenous variable (ARMAX) models and physical information that can be derived from databases such as digital topographical maps, digital elevation maps and soil profile descriptionswas investigated at 51 sites with open sandy soils in the Pleistocene part of the Netherlands, The ARMAX parameters appeared to be weakly related with physical information. Water-table depth predicted with ARMAX models which were guessed using physical information have large systematic errors but relatively small random errors. It is concluded that the relationships between time series model paremters and physical information can be improved with respect to the modelling as well as the quality of the data used

Time out of work and skill depreciation

This paper investigates the role of skill depreciation in the relationship between work interruptions and subsequent wages. Using unique longitudinal microdata containing information on the ability to understand and practically employ printed information, we are able to analyze changes in skills for individuals as a function of time out of work. In general, we find statistically strong evidence of a negative relationship between work interruptions and skills. Our analysis suggests that depreciation of general information-processing skills is economically significant, with a full year of non-employment being equivalent to moving 5 percentiles down the skill distribution.Work interruptions; skill depreciation; wage differentials

The Dynamics of Real-Time Online Information and Disease Progression: Understanding Spatial Heterogeneity in the Relationship

The re-emergence of infectious diseases such as measles and polio is creating logistics challenges for the state authorities to curb their spread and contain them. (CL, 2015) Real-time surveillance of infectious diseases is important to detect possible epidemics in advance to prevent shortages of medications (FDA, 2018). The outbreak of an infectious disease creates panic in the community and is accompanied by a sudden increase in the online interest in knowing more about the disease and its symptoms. Prior studies have found a strong relationship between web-based information and disease outbreak but the influence of dynamics of web-based information in real-time is often not considered (Zhang, 2017). The dynamics or rate of change of the online interest in a disease can inform or misinform about perspective cases of the disease in a region. Oftentimes, especially in this connected world individuals overreact to the situation which may send spurious online signals regarding the disease progression. Hence, we study the relationship between the dynamics of online information and the infectious disease outbreak. We also investigate if this relationship could be influenced by regional demographic factors. We analyze weekly online interest dynamics for five infectious diseases over a period of three years across 50 states of the United States. We control for several factors (including weather, demographics, and travelers) and utilize hierarchical functional data models to incorporate real-time dynamics and clustering at the regional level. Preliminary findings suggest that online interest dynamics have a significant relationship with disease outbreak and the effect is segregated at the regional level. These findings are important to develop a system for real-time surveillance and account for the influence of heterogonous online interest during an endemic outbreak

Informational efficiency and spurious spillover effects between spot and derivatives markets

Derivatives markets produce the means for price discovery as leading indicators in the transmission of new information. Examining volatility spillovers between spot and derivatives markets without accounting for possible disequilibria in the long term relationship could potentially result in spurious spillover effects. Our paper aims to contribute in this literature by controlling for possible disturbances in the long-run equilibrium relationship between the two markets. By application of a regime shift approach we provide evidence of a time varying spillover effect from derivatives to spot markets. However, this effect is inconclusive in the absence of a significant (1 − 1) cointegration relationship