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The anticipative information refers to some information about future events that may be disclosed in advance. This information may regard, for example, financial assets and their future trends. In our paper, we assume the existence of some anticipative information in a market whose risky asset dynamics evolve according to a Brownian motion and a Poisson process. Using Malliavin calculus and filtration enlargement techniques, we derive the information drift of the mentioned processes and, both in the pure jump case and in the mixed one, we compute the additional expected logarithmic utility. Many examples are shown, where the anticipative information is related to some conditions that the constituent processes or their running maximum may verify, in particular, we show new examples considering Bernoulli random variables.

In contrast to the literature involving U.S. bank domestic lending, we find that mutual funds affiliated with lending banks reduce their equity investment and turnover in the non-U.S.-listed stock of their non-U.S. borrowers compared to non-lending banks or unaffiliated mutual funds. Reduced equity holdings increase loan spreads, preserving the lending bank’s cross-border information monopoly. Equity market holdings and turnover are reduced when banks lend to firms in emerging nations and when the geographic distance between the lender and the mutual fund manager is greatest. Thereby, long-range information percolation may benefit global institutions at the expense of individual subsidiaries.

In the theory of portfolio selection, there are few methods that effectively address the combined challenge of insider information and model uncertainty, despite numerous methods proposed for each individually. This paper studies the problem of the robust optimal investment for an insider under model uncertainty. To address this, we extend the Itô formula for forward integrals by Malliavin calculus, and use it to establish an implicit anticipating stochastic differential game model for the robust optimal investment. Since traditional stochastic control theory proves inadequate for solving anticipating control problems, we introduce a new approach. First, we employ the variational method to convert the original problem into a nonanticipative stochastic differential game problem. Then we use the stochastic maximum principle to derive the Hamiltonian system governing the robust optimal investment. In cases where the insider information filtration is of the initial enlargement type, we derive the closed-form expression for the investment by using the white noise theory when the insider is ’small’. When the insider is ’large’, we articulate a quadratic backward stochastic differential equation characterization of the investment. We present the numerical result and conduct an economic analysis of the optimal strategy across various scenarios.

Protecting the rights of stock market participants in the modern world is an important aspect of its functioning, ensuring the security of investments of participants and their property status. The misuse of insider information with the aim of obtaining certain benefits, and market manipulation are some of the most ambitious crimes that violate the rights of a wide range of people, and a direct threat to their material well-being. Insider trading involves trading transactions with securities, which is carried out by private individuals, holding information about the Issuer of the financial asset. In this work, we use methods of legal statistics that allow us to obtain quantitative data on the application of liability for violations of anti-insider Russian legislation. In addition, a comparative legal method is used to comparatively characterize measures to combat insider activity in the world. The purpose of the research is to identify the shortcomings of the modern criminal law mechanism for countering insider activity in the Russian securities market and develop measures to improve its effectiveness. The criminal law regulation of insider information in the world and domestic experience are analyzed. As a result of the study, a number of shortcomings inherent in this mechanism were identified. Thus, the study of foreign practice has shown that the existing measures in Russia to combat insiders in the securities market are not effective. This is due to many factors, the main of which are the imperfection of the legal framework, the lack of practical application of criminal penalties, their low effectiveness, the lack of specific penalties, etc. The article highlights the problems of administrative and criminal liability for market manipulation and illegal use of insider information. The article analyzes the criminal law regulation of mitigating liability for insider information in the world and domestic experience. Based on the analysis and comparison of Russian and international practices in the fight against insiders, conclusions are drawn about the need to adjust the domestic monitoring mechanism and improve criminal law methods to ensure its functioning. The article actualizes the problems of administrative and criminal liability for the manipulation of the market and the misuse of insider information.

Institutional owners frequently invest in a diversified portfolio of firms to avoid firm-specific risks. I investigate the particular scenario in which the institutional owners have shares in both the acquiring and the acquired target firms of an M&A deal. Using a quasi-experimental approach, I find that the acquirer pays less premium and performs better after the M&A effectiveness when the ratio between the value owned by common institutional shareholders in the acquirer and the value held by the same shareholders in the target firm is higher. The value paid is higher, and the performance worsens when this ratio is lower. The results suggest the common institutional owners can obtain benefits from promoting and implementing such M&A deals as a secondary compensation for their lack of control, usually at the expense of the controlling shareholders.

This paper examines the effects of social network structures on prediction market accuracy in the presence of insider information through a randomized laboratory experiment. In the experiment, insider information is operationalized as signals on the state of nature with high precision. Motivated by the literature on insider information in the context of financial markets, we test and confirm two characterizations of insider information in the context of prediction markets: abnormal performance and less diffusion. Experimental results suggest that a more balanced social network structure is crucial to the success of prediction markets, whereas network structures akin to star networks are ill suited to prediction markets. As compared with other network structures, insider information has less positive effects on prediction market accuracy in star networks. We also find that the bias of the public information has a larger negative effect on prediction market accuracy in star networks.

Community-academic partnerships are increasingly used to engage community members and researchers in research activities; however, little is known about the motivations and perceptions of community members to participate in such projects. The overall goal was to elicit Community Advisory Board (CAB) members' motivations and perceptions of involvement in a community-academic partnership about cancer prevention. An external evaluator conducted 15 one-on-one semi-structured interviews with CAB members of the project. Coders conducted a conventional content analysis to derive themes from the interview data. Emergent themes were grouped into four categories: CAB members' 1) motivation to participate in the project, 2) perceptions that they had insider information, 3) views of roles and responsibilities in project planning and implementation, and 4) challenges and suggestions to improve the community-academic relationship. This study found substantial evidence that CAB members perceived they were working to involve the Hispanic community in health promotion.

We model in a dynamic way an insider's private information flow which is successively augmented by a family of initial enlargement of filtrations. According to the a priori available information, we propose several density hypotheses which are presented in hierarchical order from the weakest to the strongest. We compare these hypotheses, in particular, with Jacod's one, and deduce conditional expectations under each of them by providing consistent expressions with respect to the common reference filtration. Finally, this framework is applied to a default model with insider information on the default threshold and some numerical illustrations are performed.

PurposeThis study explores whether institutional investors can distinguish an undervalued share repurchase from a falsely signaled share repurchase. This study also aims to determine what information institutions use when investing in repurchase stocks.Design/methodology/approachThis study uses unique Taiwanese data and concentrates on foreign institutions because they are the most sophisticated investors in Taiwan.FindingsThe results show that foreign institutional trading in open market repurchase (OMR) stocks will earn both positive concurrent and post-OMR excess returns. In addition, there is a significant positive relationship between pre-OMR insider trading and foreign institutional trading during the OMR period; that is, foreign institutions follow insiders to trade their OMR stocks.Practical implicationsThis study finds that foreign institutions use publicly available data on insider trading to choose OMR stocks and create excess returns. This encourages individual investors without private information, who can also earn a positive return if they diligently study available public information.Originality/valueThis study contributes to the international investment literature by determining the price impacts associated with foreigner trading in the firm-level returns of the host country. In addition, this study finds that foreign institutions choose OMRs based on insider trading information, which fills the gap in existing studies on share repurchasing. Moreover, this study enriches the insider literature by showing how foreign institutions can benefit by using insider trading information.

We use excess return, risks, MB ratios, and cumulative abnormal return as proxies to examine the CEO's market timing. The empirical results indicate that CEOs have been exactly in timing the market for Seasonal equity offering (SEO) events. CEOs have more incentives to execute seasonal equity offering when CAR reach peak and market risk drop to the lowest point that investors become less worried about risks. Evidence also shows that institutional investors do not own insider information before SEO but when issuance date appears, they recognize that CEOs are exploiting insider information in order to issue stocks at the highest price. Hence, the institutional investors switch their trading behavior from long positions to short positions to dodge the potential losses inflicted by the CEO's market timing. The fund manager recognizes that CEOs are implementing market timing so they can earn a positive return in the future. In contrast, security dealers and foreign investors do not recognize the CEO's market timing action, so they do not react, resulting in negative returns in the future.