Over the past decade, carbon trading has emerged as the industrialized world's primary policy response to global climate change despite considerable controversy. With carbon markets worth $144 ...billion in 2009, carbon trading represents the largest manifestation of the trend toward market-based environmental governance. In Carbon Coalitions, Jonas Meckling presents the first comprehensive study on the rise of carbon trading and the role business played in making this policy instrument a central pillar of global climate governance.Meckling explains how a transnational coalition of firms and a few market-oriented environmental groups actively promoted international emissions trading as a compromise policy solution in a situation of political stalemate. The coalition sidelined not only environmental groups that favored taxation and command-and-control regulation but also business interests that rejected any emissions controls. Considering the sources of business influence, Meckling emphasizes the importance of political opportunities (policy crises and norms), coalition resources (funding and legitimacy,) and political strategy (mobilizing state allies and multilevel advocacy).Meckling presents three case studies that represent milestones in the rise of carbon trading: the internationalization of emissions trading in the Kyoto Protocol (1989--2000); the creation of the EU Emissions Trading System (1998--2008); and the reemergence of emissions trading on the U.S. policy agenda (2001--2009). These cases and the theoretical framework that Meckling develops for understanding the influence of transnational business coalitions offer critical insights into the role of business in the emergence of market-based global environmental governance.
COMPETING ON SPEED Pagnotta, Emiliano S.; Philippon, Thomas
Econometrica,
20/May , Letnik:
86, Številka:
3
Journal Article
Recenzirano
Odprti dostop
We analyze trading speed and fragmentation in asset markets. In our model, trading venues make technological investments and compete for investors who choose where and how much to trade. Faster ...venues charge higher fees and attract speed-sensitive investors. Competition among venues increases investor participation, trading volume, and allocative efficiency, but entry and fragmentation can be excessive, and speeds are generically inefficient. Regulations that protect transaction prices (e.g., Securities and Exchange Commission trade-through rule) lead to greater fragmentation. Our model sheds light on the experience of European and U.S. markets since the implementation of Markets in Financial Instruments Directive and Regulation National Markets System.
We study intraday market intermediation in an electronic market before and during a period of large and temporary selling pressure. On May 6, 2010, U.S. financial markets experienced a systemic ...intraday event—the Flash Crash—where a large automated selling program was rapidly executed in the E-mini S&P 500 stock index futures market. Using audit trail transaction-level data for the E-mini on May 6 and the previous three days, we find that the trading pattern of the most active nondesignated intraday intermediaries (classified as High-Frequency Traders) did not change when prices fell during the Flash Crash.
In this bibliometric study, the significant transformations in the financial sector brought about by automation and technological advancements from 1984 to 2022 are explored. A total of 863 articles ...is analyzed, and a consistent upward trajectory in research focused on fast trading technologies and algorithmic strategies is identified. The key findings reveal that the research is grouped into five thematic clusters, ranging from algorithmic trading and machine learning to systemic risks associated with high-frequency trading and the impacts of algorithmic trading on market quality. This study encapsulates the evolving landscape of financial markets, emphasizing emerging trends in cryptocurrencies and machine learning, which will continue to shape future research directions. In conclusion, five macroareas and ten specific future research areas are proposed.
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•We provide a bibliometric analysis of 863 articles published from 1984 to 2022.•The article discusses the effects of automation on market dynamics, trading strategies, efficiency, and systemic risks.•Finally, we conclude by identifying future trends in financial technology and areas for further research.
We propose a model of trade in over-the-counter (OTC) markets in which each dealer with private information can engage in bilateral transactions with other dealers, as determined by her links in a ...network. Each dealer's strategy is represented as a quantity-price schedule. We analyze the effect of trade decentralization and adverse selection on information diffusion, expected profits, trading costs, and welfare. Information diffusion through prices is not affected by dealers' strategic trading motives, and there is an informational externality that constrains the informativeness of prices. Trade decentralization can both increase or decrease welfare. A dealer's trading cost is driven by both her own and her counterparties' centrality. Central dealers tend to learn more, trade more at lower costs, and earn higher expected profit.
Government agencies routinely allow pre-release access to information to accredited news agencies under embargo agreements. Using high-frequency data, we find evidence consistent with informed ...trading during embargoes of Federal Open Market Committee (FOMC) scheduled announcements. The E-mini Standard & Poor’s 500 futures’ abnormal order imbalances are in the direction of subsequent policy surprises and contain information that predicts the market reaction to the policy announcements. The estimated informed trades’ profits are arguably large. Notably, we find no evidence of informed trading prior to the start of FOMC news embargoes or during lockups ahead of nonfarm payroll, US Producer Price Index, and gross domestic product data releases.
News Trading and Speed FOUCAULT, THIERRY; HOMBERT, JOHAN; ROŞU, IOANID
The Journal of finance (New York),
February 2016, Letnik:
71, Številka:
1
Journal Article
Recenzirano
We compare the optimal trading strategy of an informed speculator when he can trade ahead of incoming news (is "fast"), versus when he cannot (is "slow"). We find that speed matters: the fast ...speculator's trades account for a larger fraction of trading volume, and are more correlated with short-run price changes. Nevertheless, he realizes a large fraction of his profits from trading on long-term price changes. The fast speculator's behavior matches evidence about high-frequency traders. We predict that stocks with more informative news are more liquid even though they attract more activity from informed high-frequency traders.
Community-based trading structures play important roles in the development of local energy market (LEM). In this paper, a decentralized optimization model for the trading community formation is ...proposed based on the Lp-box consensus alternating direction method of multipliers (ADMM), where the network features of the physical systems are explicitly represented by power loss and wheeling charging in local and regional trading level, respectively. The framework for multi-level hybrid trading network construction is introduced involving three different trading modes, i.e, traditional trading mode, agent-based trading mode and peer-to-peer (P2P) trading mode, and two hybrid trading networks, namely Traditional trading & Agent based trading (TA) and Traditional trading & Peer-to-peer trading & Agent based trading (TPA), are developed based on the trading community formation results. The corresponding profit allocation schemes are also presented for the TA and TPA hybrid trading networks respectively. A set of complex network indices is applied to analyze the network characteristics of the TA and TPA trading topologies, while the link entropy (LE) index is used to evaluate the edge significance of the communication relationship network in maintaining global connectivity. Finally, the proposed models are validated via a test system with six IEEE 33-bus systems connected through the IEEE 9-bus system. The results show that the agent-based strategy can benefit all entities compared with the SDR and contribution-based strategies, while the REO (renewable energy output)-first strategy proposed for P2P pairing is more stimulating for the selling entities with larger REOs than distance-first mode. In addition, the entities’ prices in the bi-level trading are significantly improved compared with those of the single-level trading both for agent-based trading and P2P trading. The complex index values of TA are all slightly greater than those of TPA, and a feeder with fewer managers is likely to have a larger LE value. The proposed models for trading community formation and trading network formation provide significant means for the development of sustainable LEMs.
•A decentralized trading community formation model is proposed for local energy market.•A framework for multi-level hybrid trading network construction is introduced involving different trading modes.•Two hybrid trading networks are developed with the corresponding profit allocation schemes.•A set of complex network indices is applied to analyze the network characteristics of hybrid trading networks and corresponding communication network.
Using a novel database that tracks web traffic on the Security Exchange Commission's EDGAR server between 2004 and 2015, we show that institutional investors gather information on a very particular ...subset of firms and insiders, and their surveillance is very persistent over time. This tracking behavior has powerful implications for their portfolio choice and its information content. An institution that downloaded an insider trading filing by a given firm last quarter increases its likelihood of downloading an insider trading filing on the same firm by more than 41.3 percentage points this quarter. Moreover, the average tracked stock that an institution buys generates annualized alphas of over 12% relative to the purchase of an average non tracked stock. We find that institutional managers tend to track top executives and to share educational and locational commonalities with the specific insiders they choose to follow. Collectively, our results suggest that the information in tracked trades is important for fundamental firm value and is only revealed following the information-rich dual trading by insiders and linked institutions.
This paper considers the role of high-frequency trading in a dynamic limit order market. Fast traders׳ ability to revise their quotes quickly after news arrivals helps to reduce the inefficiency that ...is rooted in the risk of being picked off, which increases trade. However, their presence induces slow traders to strategically submit limit orders with a lower execution probability, thereby reducing trade. Because speed is a source of market power, it enables fast traders to extract rents from other market participants and triggers a costly arms race that reduces social welfare. The model generates a number of testable implications concerning the effects of high-frequency trading in limit order markets.
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