In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims to facilitate working with these data sets and to provide a set of fundamental building blocks for implementing statistical models. We will discuss specific design issues encountered in the course of developing pandas with relevant examples and some comparisons with the R language. We conclude by discussing possible future directions for statistical computing and data analysis using Python.
The authors find support for a negative relation between conditional expected monthly return and conditional variance of monthly return using a GARCH-M model modified by allowing (1) seasonal patterns in volatility, (2) positive and negative innovations to returns having different impacts on conditional volatility, and (3) nominal interest rates to predict conditional variance. Using the modified GARCH-M model, they also show that monthly conditional volatility may not be as persistent as was thought. Positive unanticipated returns appear to result in a downward revision of the conditional volatility, whereas negative unanticipated returns result in an upward revision of conditional volatility. Copyright 1993 by American Finance Association.
R. Porta, Florencio Lopez‐de‐Silanes, A. Shleifer
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Recent research has documented large differences among countries in ownership concentration in publicly traded firms, in the breadth and depth of capital markets, in dividend policies, and in the access of firms to external finance. A common element to the explanations of these differences is how well investors, both shareholders and creditors, are protected by law from expropriation by the managers and controlling shareholders of firms. We describe the differences in laws and the effectiveness of their enforcement across countries, discuss the possible origins of these differences, summarize their consequences, and assess potential strategies of corporate governance reform. We argue that the legal approach is a more fruitful way to understand corporate governance and its reform than the conventional distinction between bank-centered and market-centered financial systems.
In recent years, behavioral economics has revolutionized various fields, including finance, marketing, and public policy. Its application in people management, however, remains an emerging area of exploration. By integrating psychological insights into economic decision-making, behavioral economics offers a nuanced understanding of human behavior, essential for designing effective HR practices. While many of the concepts are not new in organizational behavior research and related fields, thanks to the incorporation of formalized models of choice, behavioral economics brings analytical clarity to domains traditionally studied through descriptive or qualitative methods in the behavioral sciences. This review article delves into how behavioral economics can shed light on key aspects of people management, focusing on five domains: incentives, decision-making, leadership, personalization, and organizational change. We offer a critical overview integrating some of the most well-known findings with applicability in these areas as well as promising avenues for future research. One of the main conclusions is that behavioral economics offers a powerful lens to approach people management, but also that behavioral principles need to be understood in depth (beyond average effects, for example) as generalization is often flawed, claiming for personalized solutions and interventions grounded on comprehensive perspectives.
Abstract In recent years, the European Union (EU) has introduced several policy measures to better align financial markets with sustainability goals. So far, these policies have mainly aimed to improve how information on the sustainability impacts of investments is collected and transmitted. Policymakers hope that adjustments to the epistemic infrastructure of financial markets will lead to a shift in investments that translates into transformational change in the real economy. The EU’s sustainable finance policies often follow a reflexive law approach and confine themselves to setting procedural and organisational norms. This article analyses the potential and limitations of this approach and argues that sustainable finance policies must be sufficiently detailed and binding to avoid the risk, associated with reflexive law policies, of granting too much discretion to agents with vested interests detrimental to the governance aims. However, detailed and binding policies do not fully realise the advantages in dealing with highly complex and dynamic situations that are often ascribed to reflexive law policies. While sustainable finance policies that address the epistemic infrastructure of financial markets are for various reasons still important, their potential and advantages compared to other governance approaches should not be exaggerated.