A critical overview of privacy-preserving approaches for collaborative forecasting

Cooperation between different data owners may lead to an improvement in forecast quality—for instance, by benefiting from spatiotemporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection concerns, however, said data owners might be unwilling to share their data. Interest in collaborative privacy-preserving forecasting is thus increasing. This paper analyzes the state-of-the-art and unveils several shortcomings of existing methods in guaranteeing data privacy when employing vector autoregressive models. The methods are divided into three groups: data transformation, secure multi-party computations, and decomposition methods. The analysis shows that state-of-the-art techniques have limitations in preserving data privacy, such as (i) the necessary trade-off between privacy and forecasting accuracy, empirically evaluated through simulations and real-world experiments based on solar data; and (ii) iterative model fitting processes, which reveal data after a number of iterations.     

Time,space and accounting at Nonantola Abbey (1350–1449)

Accounting historians have provided several accounts of monastic life and accounting's role in it, considering important settings such as Montecassino and San Pietro abbeys in Italy and Durham Cathedral Priory in England. Research has shown how their governance arrangements and common values enabled the Benedictines to manage their monasteries in an efficient manner which was essential in tackling the misappropriation of resources by organisational actors, including abbots. Other studies have shed light on the use of practical and effective accounting practices by the Benedictines to manage their considerable wealth and pursue their spiritual and temporal goals. Nevertheless, this body of literature is yet to explicitly consider the dimensions of time and space and their relationship with accounting practices. This study begins to address this oversight by analysing the surviving accounting records of the Benedictine abbey of Nonantola in northern Italy from 1350 to 1449. In the accounting books of Nonantola Abbey linear and cyclical conceptions of time coexisted and had an impact on the way in which transactions were reflected in the accounts. At the same time, the abbey was at the centre of a complex network of accountabilities which included lay accountants, farmers and the lessees of the abbey's properties. The main characteristic of this system was not the accuracy of the records in detailing the assets, liabilities, expenses and revenue of the abbey but the maintenance of a control system to administer an extensive agricultural network and the identification of the relationships between the abbey and the stakeholders inhabiting its space.     

Consumer experiences,attitude and behavioral intention toward online food delivery (OFD) services

Prior research has mostly examined consumer attitudes toward online services/retailing in general and a few researchers have addressed consumer experiences with online food delivery (OFD) services. The purpose of this study is to examine the structural relationship between convenience motivation, post-usage usefulness, hedonic motivation, price saving orientation, time saving orientation, prior online purchase experience, consumer attitude and behavioral intention towards OFD services. The study proposes an integrative theoretical research model based on the Contingency Framework and Extended Model of IT Continuance. 224 valid questionnaires were collected to empirically test the research model using the partial least square (PLS) path modeling approach. The results imply that the proposed hypotheses were supported, except for the relationship between prior online purchase experience and post-usage usefulness. Practical implications and limitations are discussed.     

Behavioral determinants of supply chain integration and coexistence

Economic theory considers physical production characteristics and related property rights as key determinants of the organization of an industry. Yet, we frequently observe coexisting governance modes within industries and firms, even when the transaction attributes of a commodity are homogenous. We test whether risk and time preferences, price expectations, and trust in supply chain types can explain variations and coexistence in governance. Specifically, we experimentally elicit economic preferences of forest managers in the Swiss wood sector. We find that all behavioral dimensions are related to the choice of sales channel. Most importantly, trust and expectations are key determinants in transferring property rights, while risk aversion, patience, and ownership structure explain the existence of plural forms at the firm level.     

Examining dynamic currency linkages amongst South Asian economies: An empirical study

In this paper, we examine the currency market linkages of South Asian member countries using daily data from 6 January 2004 to 31st March 2016. Time invariant and varying Copula GARCH models show that South Asian countries, except for India and Nepal/Bhutan, have low levels of currency market linkages which can be ascribed to poor levels of intra-regional trade intensity and portfolio flows. We reconfirm the copula results through Diebold and Yilmaz methodology and document that currency market connectedness is very limited in the South Asian region. The trends of the fundamental determinants of currency co-movements for the South Asian member countries were compared with its neighbouring regional economic bloc in Asia which has a much longer history and a wider membership base i.e ASEAN + 6. From a comparative analysis, it was found that South Asia member states have to work on their governance parameters, improve on their trade linkages and trade tariffs and work towards greater degree of capital account convertibility with adequate safeguards to achieve higher levels of currency market linkages.     

Pure jump models for pricing and hedging VIX derivatives

Recent non-parametric statistical analysis of high-frequency VIX data (Todorov and Tauchen, 2011) reveals that VIX dynamics is a pure jump semimartingale with infinite jump activity and infinite variation. To our best knowledge, existing models in the literature for pricing and hedging VIX derivatives do not have these features. This paper fills this gap by developing a novel class of parsimonious pure jump models with such features for VIX based on the additive time change technique proposed in Li et al., 2016a, Li et al., 2016b. We time change the 3/2 diffusion by a class of additive subordinators with infinite activity, yielding pure jump Markov semimartingales with infinite activity and infinite variation. These processes have time and state dependent jumps that are mean reverting and are able to capture stylized features of VIX. Our models take the initial term structure of VIX futures as input and are analytically tractable for pricing VIX futures and European options via eigenfunction expansions. Through calibration exercises, we show that our model is able to achieve excellent fit for the VIX implied volatility surface which typically exhibits very steep skews. Comparison to two other models in terms of calibration reveals that our model performs better both in-sample and out-of-sample. We explain the ability of our model to fit the volatility surface by evaluating the matching of moments implied from market VIX option prices. To hedge VIX options, we develop a dynamic strategy which minimizes instantaneous jump risk at each rebalancing time while controlling transaction cost. Its effectiveness is demonstrated through a simulation study on hedging Bermudan style VIX options.     

Going for gold: Investigating the (non)sense of increased advertising around major sports events

Major sports events draw unsurpassed media attention. Companies are motivated to increase their advertising investments around these events to reach large audiences in a short period. Is such an advertising surge actually beneficial though, or should companies avoid advertising in these periods because of negative effects of competitive interference? This study investigates when consumer packaged goods companies should invest in advertising to increase sales: before, during, or after the event or outside these event periods. The author estimates short- and long-term own- and cross-advertising elasticities for 206 brands using four years of weekly data. Although considerable heterogeneity exists across brands, own-advertising effectiveness diminishes especially before and during major sports events, in both the short and the long run. In addition, brands benefit less from category-demand effects through competitors' advertising. Conversely, greater increases in advertising spending resulting in significant growth in share of voice around focused, single-sport events are a successful strategy to overcome this overall general negative trend.     

Steady state adjusting trends using a data-driven local polynomial regression

Economic variables usually follow a dynamic trend pattern. However, it is difficult to estimate this trend precisely as numerous economically- and statistically-based estimation methods exist. This contribution proposes a data-driven nonparametric trend that is local polynomial, to improve arbitrary trend estimations of commonly used methods concerning the selection of the smoothing parameter and the dependence structure. An iterative plug-in (IPI) algorithm determines the bandwidth endogenously and allows a theory-based interpretation of the length of growth processes. This length of the bandwidth reflects the lengths of the steady state periods. Consequently, the bandwidth identifies the time period of stable economic conditions and can detect economic changes. To demonstrate the power of this estimation approach, an extensive simulation study is performed. Furthermore, examples using US and UK GDP data along with a guide for the optimal choice of algorithms for empirical applications are provided. This proposed method yields new insights for growth dynamics, cyclical movements and their dependence.     

Optimal dividend strategies with time-inconsistent preferences

This paper studies the optimal dividend strategies of an insurance company when the manager has time-inconsistent preferences. We consider the problem for a naive manager and a sophisticated manager, and analytically derive the optimal dividend strategies when claim sizes follow an exponential distribution. Our results show that the manager with time-inconsistent preferences tends to pay out dividends earlier than her time-consistent counterpart and that the sophisticated manager is more inclined to pay out dividends than the naive manager. Furthermore, we extend these results to the case with claim sizes following a mixed exponential distribution, and provide a numerical analysis to reveal the sensitivity of the optimal dividend strategies to changes in the premium, claims and surplus volatility.     

Are impatient farmers more risk-averse? Evidence from a lab-in-the-field experiment in rural Uganda

Based on data from a field-experiment in rural Uganda, we show that impatient farmers are more risk-averse than patient farmers. We relied on a simplified version of the Convex Time Budget (CTB) method to elicit farmers’ time preferences and on an independent method for eliciting their risk-preferences. We report two important findings. First, we show that our simplified CTB method applied to farmers from Uganda replicates the key findings of Andreoni and Sprenger’s lab experiments that involved student subjects. Second, we establish the existence of a negative correlation between risk tolerance and impatience, based on two independent measures.