Markov-switching in target stocks during takeover bids

This paper examines shifts in the market betas and the conditional volatility of stock prices of takeover targets. Using daily stock prices of five European and American targets, we find that adequately specified Markov-switching GARCH models are capable of detecting statistically significant regime-switches in all takeover deal-types (in cash bids, pure share-exchange bids, mixed bids). In particular, conditional volatility regime-switches are found to be most clear-cut for cash bids. Our econometric findings have implications for a broad range of financial applications such as the valuation of target stock options.     

Forecasting stock market returns over multiple time horizons

In this paper, we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news-driven, analytic, agent-based market model developed in Gusev et al. [Algo. Finance, 2015, 4, 5–51]. This heterogeneous framework enables us to capture dynamics at multiple timescales, expanding the model’s applications and improving precision. We study the heterogeneous model theoretically and empirically to highlight essential mechanisms underlying certain market behaviours, such as transitions between bull and bear markets and the self-similar behaviour of price changes. Most importantly, we apply this model to show that the stock market is nearly efficient on intraday timescales, adjusting quickly to incoming news, but becomes inefficient on longer timescales, where news may have a long-lasting nonlinear impact on dynamics, attributable to a feedback mechanism acting over these horizons. Then, using the model, we design algorithmic strategies that utilize news flow, quantified and measured, as the only input to trade on market return forecasts over multiple horizons, from days to months. The backtested results suggest that the return is predictable to the extent that successful trading strategies can be constructed to harness this predictability.     

Transfers of corporate control in firms with noncontrolling blockholders

I model the choice between a negotiated block trade and a public tender offer as means of acquiring control in a firm with a large minority blockholder. Potential acquirers differ in their (privately known) value‐creation ability. In equilibrium, block trades are made by lower ability acquirers compared to tender offers. The equal opportunity rule (EOR) and the “freezeout” rule are complements in promoting efficiency of control transfers. Stronger investor protection may hamper value‐increasing takeovers when the EOR is present. The model also delivers predictions about announcement returns and the incidence of block trades and tender offers under different legal regimes.     

Liquidity effects of trading frequency

In this paper, we present a discrete‐time modeling framework, in which the shape and dynamics of a Limit Order Book (LOB) arise endogenously from an equilibrium between multiple market participants (agents). We use the proposed modeling framework to analyze the effects of trading frequency on market liquidity in a very general setting. In particular, we demonstrate the dual effect of high trading frequency. On the one hand, the higher frequency increases market efficiency, if the agents choose to provide liquidity in equilibrium. On the other hand, it also makes markets more fragile, in the sense that the agents choose to provide liquidity in equilibrium only if they are market neutral (i.e., their beliefs satisfy certain martingale property). Even a very small deviation from market neutrality may cause the agents to stop providing liquidity, if the trading frequency is sufficiently high, which represents an endogenous liquidity crisis (also known as flash crash) in the market. This framework enables us to provide more insight into how such a liquidity crisis unfolds, connecting it to the so‐called adverse selection effect.     

Entrepreneurship, innovation, and corruption

Efforts to control corruption increase levels of trust in the ability of the state and market institutions to reliably and impartially enforce law and the rules of trade. Such trust facilitates the development of arms-length trade and the coordination of complex economic activities. We posit that better control of corruption will also be associated with rising levels of innovation and entrepreneurship. Absent such trust, however, monitoring and other transactions cost should restrict the scale and scope of trade and thus, hamper productivity and investment in innovation and entrepreneurship. Longitudinal data from 64 nations lends support to our propositions, thus helping unpack the puzzling relationship between entrepreneurship, innovation, and corruption.     

Quality Meets Structure: Generalized Reciprocity and Firm‐Level Advantage in Strategic Networks

In this paper we extend previous research by combining network structural and network process approaches. Specifically, in a six‐year, three‐wave study of 41 firms in two strategic networks, we found that the interaction between generalized reciprocity among a focal firm's partners and network tie intensity and betweenness centrality improved firm performance. No influences were observed for the interaction involving degree centrality and generalized reciprocity. Our research suggests that managers in strategic networks may need to consider the balance between relationship‐extensive and relationship‐intensive strategies.     

Industrial clusters,flagship enterprises and regional innovation

ABSTRACT

For a sample of all 88 counties in the State of Ohio over a 5-year period, this study documents the effect of flagship enterprises and concentrated industrial clusters on regional innovation. Consistent with the agglomeration arguments and the knowledge spillover theory of entrepreneurship, both appear to affect regional innovation positively. Additionally, regional educational attainment positively moderates the effect of industrial clusters on innovation. At the same time, flagship enterprises primarily affect regional innovation in regions with low education levels. Results are obtained with the help of conservative econometric techniques and are robust to the choice of alternative dependent variables and estimators. The findings have major policy implications and provide insights into alternative routes to encouraging regional innovation.     

The impact of financial and human resources on the export performance of Russian firms

This study contributes to the literature by investigating for the first time the effects of the entrepreneurial environment on export survival in Russia. Using the continuous-time Cox model and discrete-time complementary log-log and probit models, we study the effects of the availability of human and financial resources on export survival across Russian regions between 2002 and 2010. Taking into account uncertainty and time effects reveals that these effects are falling over time and are more important for larger exporters. Thus, there is evidence of a learning curve for exporters when the latter become more efficient in dealing with regional-level resources and the regulatory environment over time.     

Innovation Processes in the Russian Manufacturing Subsidiaries of Multinational Corporations: An Integrated View from Case Studies

The extant literature acknowledges the role of overseas subsidiaries in the growth and development of multinational companies (MNCs). Such subsidiaries are viewed as critical players in the innovation process at MNCs. This topic remains largely under-researched in the Russian context. This study aims to fill this gap by examining the dynamics of the innovation process in Russian-based subsidiaries of global MNCs. We present qualitative findings that indicate Russian subsidiaries are not only recipients of knowledge and technology developed elsewhere in the MNCs but are active developers of innovative products and solutions.     

Nonpoint-Source Pollution Reduction for an Iowa Watershed: An Application of Evolutionary Algorithms

We apply an integrated simulation-optimization framework to search for cost-efficient mix and location of agricultural conservation practices in a typical agricultural watershed for two types of nitrogen reduction targets: control of mean annual nitrogen loadings, and a “safety-first” type constraint, insisting that nitrogen targets be met in every weather realization (weather-resilient solutions). Evolutionary algorithms are developed for each of the appropriate water quality targets. Our approach allows for the derivation of a watershed-level total and marginal nitrogen abatement cost curve. Controlling for the probability of meeting water quality targets (looking for weather-resilient solutions) is found to be significantly more costly than controlling the average nitrogen loadings. Both types of solutions are assessed for robustness with respect to weather uncertainty: solutions selected to reduce average loadings do well under weather uncertainty, while the robustness of solutions selected to be resilient decreases with the stringency of the water quality goal. Nous avons appliqué un modèle intégré de simulation-optimisation pour trouver des combinaisons de pratiques agricoles de conservation efficaces en terme de coûts et les endroits où elles devraient être adoptées dans un bassin versant agricole typique pour deux types de cibles de réduction des charges d’azote : la surveillance des charges moyennes annuelles d’azote et une contrainte du type « sécurité d’abord », selon laquelle les cibles d’azote doivent être respectées peu importe les conditions météorologiques (solutions robustes aux changements météorologiques). Nous avons élaboré des algorithmes évolutifs pour chaque cible relative à la qualité de l’eau. Notre approche a permis de dériver la courbe de coût liéà la réduction marginale et totale de l’azote dans un bassin versant. L’ajustement de la probabilité que les cibles relatives à la qualité de l’eau soient respectées (solutions robustes aux changements météorologiques) s’est révélé significativement plus coûteux que de contrôler les charges moyennes d’azote. Nous avons évalué les deux types de solutions afin de vérifier leur performance dans des conditions météorologiques incertaines : les solutions retenues pour réduire les charges moyennes fonctionnent bien dans des conditions météorologiques incertaines, tandis que la performance des solutions robustes aux conditions météorologiques diminue avec le niveau visé de qualité de l’eau.