278 resultados para traders


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The aim of this study is to examine the relationship between momentum profitability and the stock market trading mechanism and is motivated by recent changes to the trading systems that have taken place on the London Stock Exchange. Since 1975 the London stock market has employed three different trading systems: a floor based system, a computerized dealer system called SEAQ and the automated auction system SETS. Since each new trading system has reduced the level of execution costs, one might expect, a priori, the magnitude of momentum profits to decline with each amendment to the trading system. However, the opposite empirical result is found showing that shares trading on the automated system generate higher momentum profits than those trading on the floor system and companies trading on the SETS system display greater momentum profitability than those trading on SEAQ. Our empirical results concur with the theoretical findings of the trader’s hesitation model of Du [Du, J., 2002. Heterogeneity in investor confidence and asset market under- and overreaction. Working paper] and the empirical findings of Arena et al. [Arena, M., Haggard, S., Yan, X., Price momentum and idiosyncratic volatility. Financial Review, in press].

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This paper examines the profitability that the widely published momentum strategy achieves following bull and bear markets. Investors can gain stronger momentum profits by adopting the continuation strategy after poor lagged market returns. The longer the duration used to describe the bear state, the stronger the momentum returns that are realised. The results contradict the theoretical findings of the investors' overconfidence model of Daniel et al. (`Investor Psychology and Security Market Under- and Over-Reactions', Journal of Finance, 53, 1839-85, 1998) and the follow-the-trend model of Kim (`Long-term Momentum Hypothesis: Contrarian and Momentum Strategies', Working Paper, 2002), but concur with the theoretical results of the traders' hesitation model of Du (`Heterogeneity in Investor Confidence and Asset Market Under- and Overreaction', Working Paper, 2002).

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The aim of our paper is to examine whether Exchange Traded Funds (ETFs) diversify away the private information of informed traders. We apply the spread decomposition models of Glosten and Harris (1998) and Madhavan, Richardson and Roomans (1997) to a sample of ETFs and their control securities. Our results indicate that ETFs have significantly lower adverse selection costs than their control securities. This suggests that private information is diversified away for these securities. Our results therefore offer one explanation for the rapid growth in the ETF market.

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Agent-based technology is playing an increasingly important role in today’s economy. Usually a multi-agent system is needed to model an economic system such as a market system, in which heterogeneous trading agents interact with each other autonomously. Two questions often need to be answered regarding such systems: 1) How to design an interacting mechanism that facilitates efficient resource allocation among usually self-interested trading agents? 2) How to design an effective strategy in some specific market mechanisms for an agent to maximise its economic returns? For automated market systems, auction is the most popular mechanism to solve resource allocation problems among their participants. However, auction comes in hundreds of different formats, in which some are better than others in terms of not only the allocative efficiency but also other properties e.g., whether it generates high revenue for the auctioneer, whether it induces stable behaviour of the bidders. In addition, different strategies result in very different performance under the same auction rules. With this background, we are inevitably intrigued to investigate auction mechanism and strategy designs for agent-based economics. The international Trading Agent Competition (TAC) Ad Auction (AA) competition provides a very useful platform to develop and test agent strategies in Generalised Second Price auction (GSP). AstonTAC, the runner-up of TAC AA 2009, is a successful advertiser agent designed for GSP-based keyword auction. In particular, AstonTAC generates adaptive bid prices according to the Market-based Value Per Click and selects a set of keyword queries with highest expected profit to bid on to maximise its expected profit under the limit of conversion capacity. Through evaluation experiments, we show that AstonTAC performs well and stably not only in the competition but also across a broad range of environments. The TAC CAT tournament provides an environment for investigating the optimal design of mechanisms for double auction markets. AstonCAT-Plus is the post-tournament version of the specialist developed for CAT 2010. In our experiments, AstonCAT-Plus not only outperforms most specialist agents designed by other institutions but also achieves high allocative efficiencies, transaction success rates and average trader profits. Moreover, we reveal some insights of the CAT: 1) successful markets should maintain a stable and high market share of intra-marginal traders; 2) a specialist’s performance is dependent on the distribution of trading strategies. However, typical double auction models assume trading agents have a fixed trading direction of either buy or sell. With this limitation they cannot directly reflect the fact that traders in financial markets (the most popular application of double auction) decide their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders. Experiments are conducted under both dynamic and static settings of the continuous BDA market. We find that the allocative efficiency of a continuous BDA market mainly comes from rational selection of trading directions. Furthermore, we introduce a high-performance Kernel trading strategy in the BDA market which uses kernel probability density estimator built on historical transaction data to decide optimal order prices. Kernel trading strategy outperforms some popular intelligent double auction trading strategies including ZIP, GD and RE in the continuous BDA market by making the highest profit in static games and obtaining the best wealth in dynamic games.

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In this paper we examine the intraday trading patterns of Exchange Traded Funds (ETFs) listed on the London Stock Exchange. ETFs have been shown to be characterised by much lower bid–ask spread costs and by lower levels of information asymmetry than individual securities. One possible explanation for intraday trading patterns is that concentration of trading arises at the start of the trading day because informed traders have private information that quickly diminishes in value as trading progresses. Since ETFs have lower trading costs and lower levels of information asymmetry we would expect these securities to display less pronounced intraday patterns than individual securities. We fail to find that ETFs are characterised by concentrated trading bouts during the day and therefore find support for the argument that information asymmetry is the cause of intraday volume patterns in stock markets. We find that ETF bid–ask spreads and volatility are elevated at the open but not at the close. This lends support to the “accumulation of information” explanation that sees high spreads and volatility at the open as a consequence of information accumulating during a market closure and impacting on the market when it next opens.

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Book revew: Marketinggeschichte: die Genese einer modernen Sozialtechnik [Marketing history: The genesis of a modern social technique], edited by Hartmut Berghoff, Frankfurt/Main, Campus Verlag, 2007, 409 pp., illus., [euro]30.00 (paperback), ISBN 978-3-593-38323-1. This edited volume is the result of a workshop at Göttingen University in 2006 and combines a number of different approaches to the research into the history of marketing in Germany's economy and society. The majority of contributions loosely focus around the occurrence of a ‘marketing revolution’ in the 1970s, which ties in with interpretations of the Americanisation of German business. This revolution replaced the indigenous German idea of Absatzwirtschaft (the economics of sales) with the American-influenced idea of Marketing, which was less functionally oriented and more strategic, and which aimed to connect processes within the firm in order to allow a greater focus on the consumer. The entire volume is framed by Hartmut Berghoff's substantial and informative introduction, which introduces a number of actors and trends beyond the content of the volume. Throughout the various contributions, authors provide explanations of the timing and nature of marketing revolutions. Alexander Engel identifies an earlier revolution in the marketing of dyes, which undergoes major change with the emergence of chemical dyes. While the natural dyestuff had been a commodity, with producers removed from consumers via a global network of traders, chemical dyes were products and were branded at an early stage. This was a fundamental change in the nature of production and sales. As Roman Rossfeld shows in his contribution on the Swiss chocolate industry (which focuses almost exclusively on Suchard), even companies that produced non-essential consumer goods which had always required some measure of labelling grappled for years with the need to develop fewer and higher impact brands, as well as an efficient sales operation. A good example for the classical ‘marketing revolution’ of the 1970s is the German automobile industry. Ingo Köhler convincingly argues that the crisis situation of German car manufacturers – the change from a seller's to a buyer's market, appreciation of the German mark which undermines exports, the oil crises coupled with higher inflation and greater frugality of consumers and the emergence of new competitors – lead companies to refocus from production to the demands of the consumer. While he highlights the role of Ford in responding most rapidly to these problems, he does not address whether the multinational was potentially transferring American knowledge to the German market. Similarly, Paul Erker illustrates that a marketing revolution in transport and logistics happened much later, because the market remained highly regulated until the 1980s. Both Paul Erker and Uwe Spiekermann in their contribution, present comparisons of two different sectors or companies (the tire manufacturer Continental and the logistics company Dachser, and agriculture and trade, respectively). In both cases, however, it remains unclear why these examples were chosen for comparison, as both seem to have little in common and are not always effectively used to demonstrate differences. The weakest section of the book is the development of marketing as an academic discipline. The attempt at sketching the phases in the evolution of marketing as an academic discipline by Ursula Hansen and Matthias Bode opens with an undergraduate-level explanation on the methodology of historical periodisation that seems extraneous. Considerably stronger is the section on the wider societal impact of marketing, and Anja Kruke shows how the new techniques of opinion research was accepted by politics and business – surprisingly more readily by politicians than their commercial counterparts. In terms of contemporary personalities, Hans Domizlaff emerges as one fascinating figure of German marketing history, which several contributors refer to and whose career as the German cigarette manufacturer Reemtsma is critically analysed by Tino Jacobs. Domizlaff was Germany's own ‘marketing guru’, whose successful campaigns led to the wide-ranging reception of his ideas about the nature of good branding and marketing. These are variously described as intuitive, elitist, and sachlich, a German concept of a sober, fact-based, and ‘no frills’ approach. Domizlaff did not believe in market research. Rather, he saw the genius of the individual advertiser as key to intuitively ascertaining the people's moods, wishes, and desires. This seems to have made him peculiarly suited to the tastes of the German middle class, according to Thomas Mergel's contribution on the nature of political marketing in the republic. Especially in politics, any form of hard sales tactics were severely frowned upon and considered to demean the citizen as incapable of making an informed choice, a mentality that he dates back to the traditions of nineteenth-century liberalism. Part of this disdain of ‘selling politics like toothpaste’ was also founded on the highly effective use of branding by the National Socialists, who identified their party through the use of an increasingly standardised image of Adolf Hitler and the swastika. Alexander Schug extends on previous research that criticised the simplistic notion of Hitler's charisma as the only explanation of the popular success and distances his approach from those who see it in terms of propaganda and demagogy. He argues that the NSDAP used the tools of advertising and branding precisely because they had to introduce their new ideology into a political marketplace dominated by more established parties. In this they were undoubtedly successful, more so than they intended: as bakers sold swastika cookies and butchers formed Führer heads out of lard, the NSDAP sought to regain control over the now effectively iconic images that constituted their brand, which was in danger of being trivialised and devalued. Key to understanding the history of marketing in Germany is on the one hand the exchange of ideas with the United States, and on the other the impact of national-socialist policies, and the question whether they were a force of modernisation or retardation. The general argument in the volume appears to favour the latter explanation. In the 1930s, some of the leading marketing experts emigrated to the USA, leaving German academia and business isolated. The aftermath of the Second World War left a country that needed to increase production to satisfy consumer demand, and there was little interest in advanced sales techniques. Although the Nazis were progressive in applying new marketing methods to their political campaign, this retarded the adoption of sales techniques in politics for a long time. Germany saw the development of idiosyncratic approaches by people like Domizlaff in the 1930s and 1940s, when it lost some leading thinkers, and only engaged with American marketing conceptions in the 1960s and 1970s, when consumers eventually became more important than producers.

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Typical Double Auction (DA) models assume that trading agents are one-way traders. With this limitation, they cannot directly reflect the fact individual traders in financial markets (the most popular application of double auction) choose their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders. Based on experiments under both static and dynamic settings, we find that the allocative efficiency of a static continuous BDA market comes from rational selection of trading directions and is negatively related to the intelligence of trading strategies. Moreover, we introduce Kernel trading strategy designed based on probability density estimation for general DA market. Our experiments show it outperforms some intelligent DA market trading strategies. Copyright © 2013, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

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We consider an infinite exchange economy with countably many traders, which can be regarded as a natural extension of finite exchange economies to an infinite one. In our countable economy the core defined in the traditional manner would be empty. To avoid this unwanted situation we have to strengthen the notion of “improves upon”. We will achieve this based on the idea that forming coalitions involve costs.

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Az árhatásfüggvények azt mutatják meg, hogy egy adott értékű megbízás mekkora relatív árváltozást okoz. Az árhatásfüggvény ismerete a piaci szereplők számára fontos szerepet játszik a jövőben benyújtandó ajánlataikhoz kapcsolódó árhatás előrejelzésében, a kereskedés árváltozásból eredő többletköltségének becslésében, illetve az optimális kereskedési algoritmus kialakításában. Az általunk kidolgozott módszer révén a piaci szereplők a teljes ajánlati könyv ismerete nélkül egyszerűen és gyorsan tudnak virtuális árhatásfüggvényt meghatározni, ugyanis bemutatjuk az árhatásfüggvény és a likviditási mértékek kapcsolatát, valamint azt, hogy miként lehet a Budapesti Likviditási Mérték (BLM) idősorából ár ha tás függ vényt becsülni. A kidolgozott módszertant az OTP-részvény idősorán szemléltetjük, és a részvény BLM-adatsorából a 2007. január 1-je és 2011. június 3-a közötti időszakra virtuális árhatás függvényt becsülünk. Empirikus elemzésünk során az árhatás függ vény időbeli alakulásának és alapvető statisztikai tulajdonságainak vizsgálatát végezzük el, ami révén képet kaphatunk a likviditás hiányában fellépő tranzakciós költségek múltbeli viselkedéséről. Az így kapott információk például a dinamikus portfólióoptimalizálás során lehetnek a kereskedők segítségére. / === / Price-effect equations show what relative price change a commission of a given value will have. Knowledge of price-effect equations plays an important part in enabling market players to predict the price effect of their future commissions and to develop an optimal trading algorithm. The method devised by the authors allows a virtual price-effect equation to be defined simply and rapidly without knowledge of the whole offer book, by presenting the relation between the price-effect equation and degree of liquidity, and how to estimate the price-effect equation from the time line of the Budapest Liquidity Measure (BLM). The methodology is shown using the time line for OTP shares and the virtual price-effect equation estimated for the 1 January 2007 to 3 June 2011 period from the shares BML data set. During the empirical analysis the authors conducted an examination of the tendency of the price-effect equation over time and for its basic statistical attributes, to yield a picture of the past behaviour of the transaction costs arising in the absence of liquidity. The information obtained may, for instance, help traders in dynamic portfolio optimization.

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Kimutatható-e az e-kereskedelem hatása a vállalati teljesítményre a recesszióval küzdő magyar kiskereskedelmi piacon? A hagyományos bolti értékesítés vagy on-line kereskedelem vezet hazánkban jobb pénzügyi teljesítményhez? Ezekre a kérdésekre a magyar IKT (infokommunikációs technológiai) kiskereskedők 187 elemű mintáján igyekeznek a szerzők választ keresni, az adatgyűjtést újszerű módon részben automatizált webpókokra bízva, következtetéseiket pedig elsősorban klaszterelemzési technikákra építve. Megállapítják, hogy bár a legjobb bolti kereskedők többnyire valamivel nagyobb és stabilabb profitrátákkal jellemezhetők a válság éveiben is, a piac megtartása és növelése terén már egyértelműen az e-kereskedők jeleskedtek. Eredményeik szerint az e-kereskedelem hozzásegítheti a kiskereskedőket a munkaerő-hatékonyság növeléséhez is, ám ha gyors rendelkezésre állással vagy alacsony árakkal csábítják vevőiket, akkor a profittöbblet egy részét felőrölheti a magasabb készlettartási igény vagy az árverseny. _____ The study examines whether e-commerce has a significant impact on corporate performance on the Hungarian retail market struggling with the effects of economic downturn. Is it brick-and-mortal retail or e-commerce that leads to a better financial performance? Using the innovative data gathering tools of automotive web crawlers the authors seek answers to these questions on a sample of 187 Hungarian ICT retailers. Based on cluster analysis they conclude that while the best traditional retailers have somewhat higher and more stable profitability ratios even during the years of recession, e-tailers are more successful in retaining and increasing their market share. E-commerce is also associated with higher human resource productivity, but the possible profit surplus originating from this advantage could be jeopardized in the long run as new electronic traders typically attract their customers by shorter service time or lower prices.

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This study focuses on empirical investigations and seeks implications by utilizing three different methodologies to test various aspects of trader behavior. The first methodology utilizes Prospect Theory to determine trader behavior during periods of extreme wealth contracting periods. Secondly, a threshold model to examine the sentiment variable is formulated and thirdly a study is made of the contagion effect and trader behavior. ^ The connection between consumers' sense of financial well-being or sentiment and stock market performance has been studied at length. However, without data on actual versus experimental performance, implications based on this relationship are meaningless. The empirical agenda included examining a proprietary file of daily trader activities over a five-year period. Overall, during periods of extreme wealth altering conditions, traders "satisfice" rather than choose the "best" alternative. A trader's degree of loss aversion depends on his/her prior investment performance. A model that explains the behavior of traders during periods of turmoil is developed. Prospect Theory and the data file influenced the design of the model. ^ Additional research included testing a model that permitted the data to signal the crisis through a threshold model. The third empirical study sought to investigate the existence of contagion caused by declining global wealth effects using evidence from the mining industry in Canada. Contagion, where a financial crisis begins locally and subsequently spreads elsewhere, has been studied in terms of correlations among similar regions. The results provide support for Prospect Theory in two out of the three empirical studies. ^ The dissertation emphasizes the need for specifying precise, testable models of investors' expectations by providing tools to identify paradoxical behavior patterns. True enhancements in this field must include empirical research utilizing reliable data sources to mitigate data mining problems and allow researchers to distinguish between expectations-based and risk-based explanations of behavior. Through this type of research, it may be possible to systematically exploit "irrational" market behavior. ^

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We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

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Liquidity is an important market characteristic for participants in every financial market. One of the three components of liquidity is market depth. Prior literature lacks a comprehensive analysis of depth in U.S. futures markets due to past limitations on the availability of data. However, recent innovations in data collection and dissemination provide new opportunities to investigate the depth dimension of liquidity. In this dissertation, the Chicago Mercantile Exchange (CME) Group proprietary database on depth is employed to study the dynamics of depth in the U.S. futures markets. This database allows for the analysis of depth along the entire limit order book rather than just at the first level. The first essay examines the characteristics of depth within the context of the five-deep limit order book. Results show that a large amount of depth is present in the book beyond the best level. Furthermore, the findings show that the characteristics of five-deep depth between day and night trading vary and that depth is unequal across levels within the limit order book. The second essay examines the link between the five-deep market depth and the bid-ask spread. The results suggest an inverse relation between the spread and the depth after adjusting for control factors. The third essay explores transitory volatility in relation to depth in the limit order book. Evidence supports the relation between an increase in volatility and a subsequent decrease in market depth. Overall, the results of this dissertation are consistent with limit order traders actively managing depth along the limit order book in electronic U.S. futures markets.

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This study focuses on empirical investigations and seeks implications by utilizing three different methodologies to test various aspects of trader behavior. The first methodology utilizes Prospect Theory to determine trader behavior during periods of extreme wealth contracting periods. Secondly, a threshold model to examine the sentiment variable is formulated and thirdly a study is made of the contagion effect and trader behavior. The connection between consumers' sense of financial well-being or sentiment and stock market performance has been studied at length. However, without data on actual versus experimental performance, implications based on this relationship are meaningless. The empirical agenda included examining a proprietary file of daily trader activities over a five-year period. Overall, during periods of extreme wealth altering conditions, traders "satisfice" rather than choose the "best" alternative. A trader's degree of loss aversion depends on his/her prior investment performance. A model that explains the behavior of traders during periods of turmoil is developed. Prospect Theory and the data file influenced the design of the model. Additional research included testing a model that permitted the data to signal the crisis through a threshold model. The third empirical study sought to investigate the existence of contagion caused by declining global wealth effects using evidence from the mining industry in Canada. Contagion, where a financial crisis begins locally and subsequently spreads elsewhere, has been studied in terms of correlations among similar regions. The results provide support for Prospect Theory in two out of the three empirical studies. The dissertation emphasizes the need for specifying precise, testable models of investors' expectations by providing tools to identify paradoxical behavior patterns. True enhancements in this field must include empirical research utilizing reliable data sources to mitigate data mining problems and allow researchers to distinguish between expectations-based and risk-based explanations of behavior. Through this type of research, it may be possible to systematically exploit "irrational" market behavior.

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We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.