Is trading behavior stable across contexts? Evidence from style and multi-style investors

In this paper we study priming of identity within the context of inherent vs. contextual financial decision making. We use a sample of individual trading accounts in equity-style funds taken from one fund family to test the hypothesis that trading styles are inherent vs. contextual. Our sample contains investors who invest either in a growth fund, a value fund, or both. We document behavioral differences between growth fund investors and value fund investors. We find that their trades depend on past returns in different ways: growth fund investors tend towards momentum trading and value fund investors tend towards contrarian trading. These differences may be due to inherent clientele characteristics, including beliefs about market prices, specific personality traits and cognitive strategies that cause them to self-select into one or the other style. We use a sample of investors that trade in both types of funds to test this proposition. Consistent with the contextual hypothesis, we find that investors who hold both types of funds trade growth fund shares differently than value fund shares.     

Time-varying forecasts by variational approximation of sequential Bayesian inference

Methods developed for making time-varying forecasts in economic and financial analysis include (a) equal-weighted moving-window (or rolling) regression, (b) time-weighted (e.g. exponentially weighted) regression, (c) the Kalman filter (KF) and (d) adaptive Kalman filters. This paper developed a new method based on variational approximation of sequential Bayesian inference (VASB). Concepts and notions of the sequential Bayesian analysis and the variational approximation of an intractable posterior are simple and straightforward. Our VASB algorithm is not complicated and is easy to code. For a regression on multiple time-series, the regression coefficients, standard errors, prediction and residual error are time-varying and are estimated jointly at every time step. For a single time-series (e.g. price returns of an asset), its mean and variance are time-varying and are predicted jointly at every time step. The VASB algorithm performs better than the rolling and time-weighted statistics or regressions and the KF in terms of higher predictive power and stronger robustness. Derivations of the VASB algorithm are presented in the appendices.     

How do crowd logistics platforms create value? An exploratory case study from China

ABSTRACT

Crowd logistics platforms play an important role in value creation, but the extant literature has not clarified how platforms create value. Consequently, this multiple case study identifies three main types of value creation capabilities for crowd logistics platforms: resource matching, operations management, and risk control. Additionally, the study demonstrates that these crowd logistics platform capabilities create value by providing the most accurate matches between resources and requests while also enhancing driver agility and compliance. Based on these findings, we present four propositions that extend our understanding of crowd logistics platforms’ value creation capabilities and the process through which these capabilities lead to value creation. The study also provides valuable insights for crowd logistics companies to improve their value creation capabilities.     

Jack's Sports Bar

This two‐part case focuses on indicators or red flags of a possible fraud being committed by a majority shareholder against a minority shareholder. The student assumes the role of an accountant investigating the possible fraud. In Part 1 the student is provided with a whistleblower complaint and examines the draft financial statements that will be used for the purchase price of the sale of shares by the minority shareholder to the majority shareholder. In Part 2 the student is provided with further information on inventory controls and the accounting practices. Drawing on the student's knowledge of control systems and financial statement analysis, the student's task is to identify the possible fraudulent transactions and quantify their effect.     

The impact of water access on short‐term migration in rural India

Migration is an important risk‐reduction strategy for households in developing countries. In this paper, we examine the impact of rainfall variability and irrigation availability on short‐term migration decisions in India. Our results show that both rainfall shocks and the availability of irrigation impact the decisions of households to dispatch migrants. For irrigation, we find that migration responds to costs and that deep fossil‐water wells, which provide a constant source of water, eliminate any benefit of short‐term migration. This suggests that regions with access to more secure and stable sources of water are less likely to rely on migration as an income‐smoothing mechanism, at least in the short run. Whether this holds in the long run will depend on the continued stability and availability of irrigation water.