31,320 research outputs found

    High-frequency Trading and its Role in Fragmented Markets

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    The financial services industry is among the leading industries in IT-spending. Still, little research exists which investigates how IT influences the financial services sector. Against this background, we study how a technology which emerged within the last years affects securities trading: High-Frequency Trading (HFT). Hereby, we focus on HFT and its impact on market efficiency. On the basis of a long-term analysis, we find that HFT decreases price dispersion among two distant markets. Analyzing the introduction of the German HFT Act, we further observe that the price dispersion between two leading trading venues for German blue chip securities increased. We conclude that HFT increases market efficiency in the European market landscape by transmitting information between distant markets

    Impersonal efficiency and the dangers of a fully automated securities exchange

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    This report identifies impersonal efficiency as a driver of market automation during the past four decades, and speculates about the future problems it might pose. The ideology of impersonal efficiency is rooted in a mistrust of financial intermediaries such as floor brokers and specialists. Impersonal efficiency has guided the development of market automation towards transparency and impersonality, at the expense of human trading floors. The result has been an erosion of the informal norms and human judgment that characterize less anonymous markets. We call impersonal efficiency an ideology because we do not think that impersonal markets are always superior to markets built on social ties. This report traces the historical origins of this ideology, considers the problems it has already created in the recent Flash Crash of 2010, and asks what potential risks it might pose in the future

    Analysis of Radio Spectrum Market Evolution Possibilities

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    A tremendous growth in wireless traffic volumes and a shortage of feasible radio spectrum has led to a situation where the old and rigid spectrum regime is not a viable option for spectrum management and a shift towards a more market driven approach has begun. Great uncertainty still exists over how such a radio spectrum market will come about and what kind of shape it would take. This paper studies some long term macro level evolution possibilities for how this radio spectrum market could emerge and what would be the corresponding value chain configurations. The scenario planning and system dynamics methods are utilized to build four alternative future spectrum market scenarios.Spectrum Markets, Spectrum Policy, Flexible Spectrum Usage, Cognitive Radio, Value Networks, Scenario Planning, System Dynamics.

    Risk Aversion, Transparency, and Market Performance

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    Using a model of market making with inventories based on Biais (1993), we find that investors obtain more favorable execution prices, and they hence invest more, when markets are fragmented. In our model, risk-averse dealers use less aggressive price strategies in more transparent markets (centralized) because quote dissemination alleviates uncertainty about the prices quoted by other dealers and, hence, reduces the need to compete aggressively for order flow. Further, we show that the move toward greater transparency (centralization) may have detrimental effects on liquidity and welfare.Publicad

    Anomalous price impact and the critical nature of liquidity in financial markets

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    We propose a dynamical theory of market liquidity that predicts that the average supply/demand profile is V-shaped and {\it vanishes} around the current price. This result is generic, and only relies on mild assumptions about the order flow and on the fact that prices are (to a first approximation) diffusive. This naturally accounts for two striking stylized facts: first, large metaorders have to be fragmented in order to be digested by the liquidity funnel, leading to long-memory in the sign of the order flow. Second, the anomalously small local liquidity induces a breakdown of linear response and a diverging impact of small orders, explaining the "square-root" impact law, for which we provide additional empirical support. Finally, we test our arguments quantitatively using a numerical model of order flow based on the same minimal ingredients.Comment: 16 pages, 7 figure

    Competing on Speed

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    Two forces have reshaped global securities markets in the last decade: Exchanges operate at much faster speeds and the trading landscape has become more fragmented. In order to analyze the positive and normative implications of these evolutions, we study a framework that captures (i) exchanges' incentives to invest in faster trading technologies and (ii) investors' trading and participation decisions. Our model predicts that regulation that protect prices will lead to fragmentation and faster trading speed. Asset prices decrease when there is intermediation competition and are further depressed by price protection. Endogenizing speed can also change the slope of asset demand curves. On normative side, we find that for a given number of exchanges, faster trading is in general socially desirable. Similarly, for a given trading speed, competition among exchange increases participation and welfare. However, when speed is endogenous, competition between exchanges is not necessarily desirable. In particular, speed can be inefficiently high. Our model sheds light on important features of the experience of European and U.S. markets since the implementation of Reg. NMS, and provides some guidance for optimal regulations.
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