从赌博游戏中的损失厌恶行为看情感预测与体验在决策中的作用

In Kermer, Driver-Linn, Wilson and Gilbert’s (2006) study on affective forecast, they found that people have a tendency to overestimate affective reactions in gains and losses, and people expect losses to have greater hedonic impact than gains of equal magnitude. Because of thus affective forecasting error, people prefer to irrationally avoid losses. Loss aversion is then seen as both a wealth-maximizing error and an affect-maximizing error. The present study examined the relationships among affective forecast, affective experience and loss aversion, and tested Kermer et al.’s (2006) conclusion that people’s loss aversion is an affective forecasting error. In experiment 1, we examined the relationship between affective forecast and loss aversion. Kermer et al.’s (2006) hypothesized that when people expect losses to have greater hedonic impact than gains, they will accept the gambling task, and when people expect gains to have greater hedonic impact than losses, they will refuse the gambling task. We found that (1) individuals with lower loss aversion had a greater tendency to accept a gambling task than those with higher loss aversion; (2) individuals with lower loss aversion expected losses and gains to have smaller affective impacts than those with higher loss aversion. Thus, people never exactly calculated their forecasting affective. In experiment 2, we examined the relationship between affective forecast and affective experience. Consistent with Kermer et al.’s (2006) finding, we found that our participants tended to overestimate affective reactions in gains as well as losses. More interestingly, Kermer et al.’s (2006) found that participants’ predictions for a loss were significantly more distant from experienced emotions than were their predictions for a win, we, however, found the opposite —participants’ predictions for a win were significantly more distant from the experienced emotions than were their predictions for a loss. These experiments further validated the relations between affection and decision making, and contributed to our understanding on the affective reactions to future events. Our study imply that it was not the exact calculation of affective forecast on decision outcomes, but rather the magnitude of affection on outcomes, that influenced people’s affective decision making. It indicated that those with lower magnitude of affection would less like to avoid losses, and thus more like to accept a gambling task.

社会形势预警的几种建模方法比较

Based on social survey data conducted by local research group in some counties executed in the nearly past five years in China, the author proposed and solved two kernel problems in the field of social situation forecasting: i) How can the attitudes’ data on individual level be integrated with social situation data on macrolevel; ii) How can the powers of forecasting models’ constructed by different statistic methods be compared? Five integrative statistics were applied to the research: 1) algorithm average (MEAN); 2) standard deviation (SD); 3) coefficient variability (CV); 4) mixed secondary moment (M2); 5) Tendency (TD). To solve the former problem, the five statistics were taken to synthesize the individual and mocrolevel data of social situations on the levels of counties’ regions, and form novel integrative datasets, from the basis of which, the latter problem was accomplished by the author: modeling methods such as Multiple Regression Analysis (MRA), Discriminant Analysis (DA) and Support Vector Machine (SVM) were used to construct several forecasting models. Meanwhile, on the dimensions of stepwise vs. enter, short-term vs. long-term forecasting and different integrative (statistic) models, meta-analysis and power analysis were taken to compare the predicting power of each model within and among modeling methods. Finally, it can be concluded from the research of the dissertation: 1) Exactly significant difference exists among different integrative (statistic) models, in which, tendency (TD) integrative models have the highest power, but coefficient variability (CV) ones have the lowest; 2) There is no significant difference of the power between stepwise and enter models as well as short-term and long-term forecasting models; 3) There is significant difference among models constructed by different methods, of which, support vector machine (SVM) has the highest statistic power. This research founded basis in all facets for exploring the optimal forecasting models of social situation’s more deeply, further more, it is the first time methods of meta-analysis and power analysis were immersed into the assessments of such forecasting models.

不确定性类型对概率表达和概率判断的影响

The present research firstly reviewed the experimental literature on probability expression and probability judgment, hypothesizing that individuals’ preference of probability expressions (verbal probability vs. numerical probability) and tendency for overextremity in probability judgment might differ with respect to different types of uncertainty. Five studies were conducted to test this hypothesis. In Study 1, questionnaires were used to explore the communication preference among Chinese-speaking people. Study 2 adapted the View of Uncertainty Questionnaire to explore the difference of verbal answers to three kinds of uncertainty. Study 3 and Study 4 used methods of the paper-and-pencil questionnaire and the laboratory experiment, respectively, to test the effects of uncertainty types on the preference of probability expressions and on the tendency for over-extreme probability judgment. Finally, Study 5 focused on individuals’ preference of probability expressions under various kinds of scenarios. The results were as follows: 1. The Communication Model Preference paradox phenomenon appears to be even more pronounced in the Chinese culture than in American English cultural settings. 2. The Chinese prefer more verbal probability expressions when communicating uncertainty in a weather-forecasting context than in a general context. 3. Sample groups with lower level of westernization tend to give more extreme answers and less probabilistic answers. 4. Types of uncertainty did have effects on individuals’ tendency for over-extreme probability judgment: under a traditional probability judgment task, people tend to be more over-extreme on internal uncertainty events than on external uncertainty events; however, this result is reversed under a gambling task. 5. Individuals’ preference for verbal probability expressions is more salient on internal uncertain events than on external uncertain events.

Process control in agile supply chain network.

The work comprises a new theoretical development applied to aid decision making in an increasingly important commercial sector. Agile supply, where small volumes of high margin, short life cycle innovative products are offered, is increasingly carried out through a complex global supply chain network. We outline an equilibrium solution in such a supply chain network, which works through limited cooperation and coordination along edges (links) in the network. The links constitute the stochastic modelling entities rather than the nodes of the network. We utilise newly developed phase plane analysis to identify, model and predict characteristic behaviour in supply chain networks. The phase plane charts profile the flow of inventory and identify out of control conditions. They maintain quality within the network, as well as intelligently track the way the network evolves in conditions of changing variability. The methodology is essentially distribution free, relying as it does on the study of forecasting errors, and can be used to examine contractual details as well as strategic and game theoretical concepts between decision-making components (agents) of a network. We illustrate with typical data drawn from supply chain agile fashion products.

Collaboration on procurement of e-content between the National Health Service and higher education in the UK

Urquhart, C. J., Cox, A. M.& Spink, S. (2007). Collaboration on procurement of e-content between the National Health Service and higher education in the UK. Interlending & Document Supply, 35(3), 164-170. Sponsorship: JISC, LKDN

An econometric analysis of international air travel demand in Saudi Arabia

Abed, S. Y., Ba-Fail, A. O., & Jasimuddin, S. (2001). An econometric analysis of international air travel demand in Saudi Arabia. Journal of Air Transport Management, 7(3), 143-148 RAE2008

Wykorzystanie gier decyzyjnych/symulacyjnych w naukach społecznych. Wybrane problemy

Treścią publikacji jest przedstawienie wybranych problemów prognozowania w naukach społecznych. W artykule skoncentrowano się na metodzie gier decyzyjnych/symulacyjnych, które – zwłaszcza wraz z rozwojem teorii gier oraz komputerów – są coraz częściej wykorzystywane w wielu dziedzinach. Na wybranych przykładach gier decyzyjnych/symulacyjnych – Poznań International Model United Nations 2013/POZiMUN; S.E.N.S.E. a także gry sieciowej EVE Online – wskazano jak ważne są takie ćwiczenia, by móc precyzyjniej przewidywać przyszłość. Zwrócono także szczególną uwagę na kwestię przypadku oraz czynników zakłócających, które mogą destabilizować proces przewidywania. Poruszono ponadto problem podejmowania decyzji w aspekcie klasycznej oraz kwantowej logiki.

Structural Analysis of Network Traffic Flows

Network traffic arises from the superposition of Origin-Destination (OD) flows. Hence, a thorough understanding of OD flows is essential for modeling network traffic, and for addressing a wide variety of problems including traffic engineering, traffic matrix estimation, capacity planning, forecasting and anomaly detection. However, to date, OD flows have not been closely studied, and there is very little known about their properties. We present the first analysis of complete sets of OD flow timeseries, taken from two different backbone networks (Abilene and Sprint-Europe). Using Principal Component Analysis (PCA), we find that the set of OD flows has small intrinsic dimension. In fact, even in a network with over a hundred OD flows, these flows can be accurately modeled in time using a small number (10 or less) of independent components or dimensions. We also show how to use PCA to systematically decompose the structure of OD flow timeseries into three main constituents: common periodic trends, short-lived bursts, and noise. We provide insight into how the various constituents contribute to the overall structure of OD flows and explore the extent to which this decomposition varies over time.

Generating Representative ISP Technologies From First-Principles

Understanding and modeling the factors that underlie the growth and evolution of network topologies are basic questions that impact capacity planning, forecasting, and protocol research. Early topology generation work focused on generating network-wide connectivity maps, either at the AS-level or the router-level, typically with an eye towards reproducing abstract properties of observed topologies. But recently, advocates of an alternative "first-principles" approach question the feasibility of realizing representative topologies with simple generative models that do not explicitly incorporate real-world constraints, such as the relative costs of router configurations, into the model. Our work synthesizes these two lines by designing a topology generation mechanism that incorporates first-principles constraints. Our goal is more modest than that of constructing an Internet-wide topology: we aim to generate representative topologies for single ISPs. However, our methods also go well beyond previous work, as we annotate these topologies with representative capacity and latency information. Taking only demand for network services over a given region as input, we propose a natural cost model for building and interconnecting PoPs and formulate the resulting optimization problem faced by an ISP. We devise hill-climbing heuristics for this problem and demonstrate that the solutions we obtain are quantitatively similar to those in measured router-level ISP topologies, with respect to both topological properties and fault-tolerance.

Essays on Vietnam’s Financial Reforms: Foreign Exchange Statistics and Evidence of Long-Run Equilibrium

In this paper, we examine exchange rates in Vietnam’s transitional economy. Evidence of long-run equilibrium are established in most cases through a single co-integrating vector among endogenous variables that determine the real exchange rates. This supports relative PPP in which ECT of the system can be combined linearly into a stationary process, reducing deviation from PPP in the long run. Restricted coefficient vectors ß’ = (1, 1, -1) for real exchange rates of currencies in question are not rejected. This empirics of relative PPP adds to found evidences by many researchers, including Flre et al. (1999), Lee (1999), Johnson (1990), Culver and Papell (1999), Cuddington and Liang (2001). Instead of testing for different time series on a common base currency, we use different base currencies (USD, GBP, JPY and EUR). By doing so we want to know the whether theory may posit significant differences against one currency? We have found consensus, given inevitable technical differences, even with smallerdata sample for EUR. Speeds of convergence to PPP and adjustment are faster compared to results from other researches for developed economies, using both observed and bootstrapped HL measures. Perhaps, a better explanation is the adjustment from hyperinflation period, after which the theory indicates that adjusting process actually accelerates. We observe that deviation appears to have been large in early stages of the reform, mostly overvaluation. Over time, its correction took place leading significant deviations to gradually disappear.

Correcting the errors: Volatility forecast evaluation using high-frequency data and realized volatilities

We develop general model-free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit recent nonparametric asymptotic distributional results, are both easy-to-implement and highly accurate in empirically realistic situations. We also illustrate that properly accounting for the measurement errors in the volatility forecast evaluations reported in the existing literature can result in markedly higher estimates for the true degree of return volatility predictability.

Prediction in dynamic models with time-dependent conditional variances

This paper considers forecasting the conditional mean and variance from a single-equation dynamic model with autocorrelated disturbances following an ARMA process, and innovations with time-dependent conditional heteroskedasticity as represented by a linear GARCH process. Expressions for the minimum MSE predictor and the conditional MSE are presented. We also derive the formula for all the theoretical moments of the prediction error distribution from a general dynamic model with GARCH(1, 1) innovations. These results are then used in the construction of ex ante prediction confidence intervals by means of the Cornish-Fisher asymptotic expansion. An empirical example relating to the uncertainty of the expected depreciation of foreign exchange rates illustrates the usefulness of the results. © 1992.

Oil and gas projects in the Western Amazon: threats to wilderness, biodiversity, and indigenous peoples.

BACKGROUND: The western Amazon is the most biologically rich part of the Amazon basin and is home to a great diversity of indigenous ethnic groups, including some of the world's last uncontacted peoples living in voluntary isolation. Unlike the eastern Brazilian Amazon, it is still a largely intact ecosystem. Underlying this landscape are large reserves of oil and gas, many yet untapped. The growing global demand is leading to unprecedented exploration and development in the region. METHODOLOGY/PRINCIPAL FINDINGS: We synthesized information from government sources to quantify the status of oil development in the western Amazon. National governments delimit specific geographic areas or "blocks" that are zoned for hydrocarbon activities, which they may lease to state and multinational energy companies for exploration and production. About 180 oil and gas blocks now cover approximately 688,000 km(2) of the western Amazon. These blocks overlap the most species-rich part of the Amazon. We also found that many of the blocks overlap indigenous territories, both titled lands and areas utilized by peoples in voluntary isolation. In Ecuador and Peru, oil and gas blocks now cover more than two-thirds of the Amazon. In Bolivia and western Brazil, major exploration activities are set to increase rapidly. CONCLUSIONS/SIGNIFICANCE: Without improved policies, the increasing scope and magnitude of planned extraction means that environmental and social impacts are likely to intensify. We review the most pressing oil- and gas-related conservation policy issues confronting the region. These include the need for regional Strategic Environmental Impact Assessments and the adoption of roadless extraction techniques. We also consider the conflicts where the blocks overlap indigenous peoples' territories.

Can exchange rates forecast commodity prices?

We show that "commodity currency" exchange rates have surprisingly robust power in predicting global commodity prices, both in-sample and out-of-sample, and against a variety of alternative benchmarks. This result is of particular interest to policy makers, given the lack of deep forward markets in many individual commodities, and broad aggregate commodity indices in particular. We also explore the reverse relationship (commodity prices forecasting exchange rates) but find it to be notably less robust. We offer a theoretical resolution, based on the fact that exchange rates are strongly forward-looking, whereas commodity price fluctuations are typically more sensitive to short-term demand imbalances. © 2010 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Discounting the distant future: How much do uncertain rates increase valuations?

We demonstrate that when the future path of the discount rate is uncertain and highly correlated, the distant future should be discounted at significantly lower rates than suggested by the current rate. We then use two centuries of US interest rate data to quantify this effect. Using both random walk and mean-reverting models, we compute the "certainty-equivalent rate" that summarizes the effect of uncertainty and measures the appropriate forward rate of discount in the future. Under the random walk model we find that the certainty-equivalent rate falls continuously from 4% to 2% after 100 years, 1% after 200 years, and 0.5% after 300 years. At horizons of 400 years, the discounted value increases by a factor of over 40,000 relative to conventional discounting. Applied to climate change mitigation, we find that incorporating discount rate uncertainty almost doubles the expected present value of mitigation benefits. © 2003 Elsevier Science (USA). All rights reserved.