878 resultados para Algorithmic Trading
Resumo:
The system dynamics concept of `generic structure' is dividable into three sub-types. This paper analyses the validity of these three, using both practical and theoretical perspectives. Firstly, a new set of measures is developed for generating validity-`confidence'-amongst a group using generic structures in a practical modelling situation. It is concluded that different confidence criteria are implicitly employed; there is an argument for trading-off model precision and analytical quality for simplicity and ease of use and future research is needed to combine these `process' and `content' aspects of confidence. From a theoretical stance it is shown that with two of the sub-types a scientific notion of confidence is achievable whereas the third (`archetypes') involves merely metaphorical thinking. It is concluded that the theoretical status of archetypes requires further development, whilst ensuring that its benefits are retained.
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This paper examines and analyses the impacts of the reformed CAP as well as the decisions of the new round of negotiations for the olive oil and cotton sectors in the European Union. The aim of this study is to estimate changes in supply (agricultural supply plus intermediate demand and final production), demand (consumption), price and stock formation (import, export, beginning and ending stocks, national price formation) for both the olive oil and cotton sectors. The model designed for this purpose is partial equilibrium and policy oriented. The objectives of this model are to estimate changes in the production and consumption of the two products concerned, to determine how the reformed CAP and the new round of negotiations of the WTO affect these two sectors to analyse the evolution of export and import volumes, and finally to determine how this evolution will influence the welfare situation of the olive and cotton sectors.
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Purpose – Investors are now able to analyse more noise-free news to inform their trading decisions than ever before. Their expectation that more information means better performance is not supported by previous psychological experiments which argue that too much information actually impairs performance. The purpose of this paper is to examine whether the degree of information explicitness improves stock market performance. Design/methodology/approach – An experiment is conducted in a computer laboratory to examine a trading simulation manipulated from a real market-shock. Participants’ performance efficiency and effectiveness are measured separately. Findings – The results indicate that the explicitness of information neither improves nor impairs participants’ performance effectiveness from the perspectives of returns, share and cash positions, and trading volumes. However, participants’ performance efficiency is significantly affected by information explicitness. Originality/value – The novel approach and findings of this research add to the knowledge of the impact of information explicitness on the quality of decision making in a financial market environment.
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he perspective European Supergrid would consist of an integrated power system network, where electricity demands from one country could be met by generation from another country. This paper makes use of a bi-linear fixed-effects model to analyse the determinants for trading electricity across borders among 34 countries connected by the European Supergrid. The key question that this paper aims to address is the extent to which the privatisation of European electricity markets has brought about higher cross-border trade of electricity. The analysis makes use of distance, price ratios, gate closure times, size of peaks and aggregate demand as standard determinants. Controlling for other standard determinants, it is concluded that privatisation in most cases led to higher power exchange and that the benefits are more significant where privatisation measures have been in place for a longer period.
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This paper examines the time-varying nature of price discovery in eighteenth century cross-listed stocks. Specifically, we investigate how quickly news is reflected in prices for two of the great moneyed com- panies, the Bank of England and the East India Company, over the period 1723 to 1794. These British companies were cross-listed on the London and Amsterdam stock exchange and news between the capitals flowed mainly via the use of boats that transported mail. We examine in detail the historical context sur- rounding the defining events of the period, and use these as a guide to how the data should be analysed. We show that both trading venues contributed to price discovery, and although the London venue was more important for these stocks, its importance varies over time.
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The study examines the impact of liquidity risk on freight derivatives returns. The Amihud liquidity ratio and bid–ask spreads are utilized to assess the existence of liquidity risk in the freight derivatives market. Other macroeconomic variables are used to control for market risk. Results indicate that liquidity risk is priced and both liquidity measures have a significant role in determining freight derivatives returns. Consistent with expectations, both liquidity measures are found to have positive and significant effects on the returns of freight derivatives. The results have important implications for modeling freight derivatives, and consequently, for trading and risk management purposes.
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This paper examines the determinants of cross-platform arbitrage profits. We develop a structural model that enables us to decompose the likelihood of an arbitrage opportunity into three distinct factors: the fixed cost to trade the opportunity, the level at which one of the platforms delays a price update and the impact of the order flow on the quoted prices (inventory and asymmetric information effects). We then investigate the predictions from the theoretical model for the European Bond market with the estimation of a probit model. Our main finding is that the results found in the empirical part corroborate strongly the predictions from the structural model. The event of a cross market arbitrage opportunity has a certain degree of predictability where an optimal ex ante scenario is represented by a low level of spreads on both platforms, a time of the day close to the end of trading hours and a high volume of trade.
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Research evaluating perceptual responses to music has identified many structural features as correlates that might be incorporated in computer music systems for affectively charged algorithmic composition and/or expressive music performance. In order to investigate the possible integration of isolated musical features to such a system, a discrete feature known to correlate some with emotional responses – rhythmic density – was selected from a literature review and incorporated into a prototype system. This system produces variation in rhythm density via a transformative process. A stimulus set created using this system was then subjected to a perceptual evaluation. Pairwise comparisons were used to scale differences between 48 stimuli. Listener responses were analysed with Multidimensional scaling (MDS). The 2-Dimensional solution was then rotated to place the stimuli with the largest range of variation across the horizontal plane. Stimuli with variation in rhythmic density were placed further from the source material than stimuli that were generated by random permutation. This, combined with the striking similarity between the MDS scaling and that of the 2-dimensional emotional model used by some affective algorithmic composition systems, suggests that isolated musical feature manipulation can now be used to parametrically control affectively charged automated composition in a larger system.
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Carbon has been described as a ‘surreal commodity’. Whilst carbon trading, storage, sequestration and emissions have become a part of the contemporary climate lexicon, how carbon is understood, valued and interpreted by actors responsible for implementing carbon sequestration projects is still unclear. In this review paper, we are concerned with how carbon has come to take on a range of meanings, and in particular, we appraise what is known about the situated meanings that people involved in delivering, and participating in, carbon sequestration projects in the global South assign to this complex element. Whilst there has been some reflection on the new meanings conferred on carbon via the neoliberal processes of marketisation, and how these processes interact with historical and contemporary narratives of environmental change, less is known about how these meanings are (re)produced and (re)interpreted locally. We review how carbon has been defined both as a chemical element and as a tradable, marketable commodity, and discuss the implications these global meanings might have for situated understandings, particularly linked to climate change narratives, amongst communities in the global South. We consider how the concept of carbon capabilities, alongside theoretical notions of networks, assemblages and local knowledges of the environment and nature, might be useful in beginning to understand how communities engage with abstract notions of carbon. We discuss the implications of specific values attributed to carbon, and therefore to different ecologies, for wider conceptualisations of how nature is valued, and climate is understood, and particularly how this may impact on community interactions with carbon sequestration projects. Knowing more about how people understand, value and know carbon allows policies to be better informed and practices more effectively targeted at engaging local populations meaningfully in carbon-related projects.
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The literature on firm heterogeneity and trade has highlighted that most trading firms tend to engage in both importing and exporting activities. This paper provides some evidence that helps understanding to what extent this is the result of a two-way relationship. Using firm-level data for a group of 27 Eastern European and Central Asian countries from the World Bank Business Environment and Enterprise Performance Survey (BEEPS) over the period 2002–2008, we estimate a bivariate probit model of exporting and importing. After controlling for size (and other firm-level characteristics) we find that firms’ exporting activity does not increase the probability of importing, while the latter has a positive effect on foreign sales. This effect is mainly channeled through an increase in firm productivity and product innovation.
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Trading commercial real estate involves a process of exchange that is costly and which occurs over an extended and uncertain period of time. This has consequences for the performance and risk of real estate investments. Most research on transaction times has occurred for residential rather than commercial real estate. We study the time taken to transact commercial real estate assets in the UK using a sample of 578 transactions over the period 2004 to 2013. We measure average time to transact from a buyer and seller perspective, distinguishing the search and due diligence phases of the process, and we conduct econometric analysis to explain variation in due diligence times between assets. The median time for purchase of real estate from introduction to completion was 104 days and the median time for sale from marketing to completion was 135 days. There is considerable variation around these times and results suggest that some of this variation is related to market state, type and quality of asset, and type of participants involved in the transaction. Our findings shed light on the drivers of liquidity at an individual asset level and can inform models that quantify the impact of uncertain time on market on real estate investment risk.
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This paper provides an interdisciplinary perspective on mine reclamation in forested areas of Ghana, a country characterised by conflicts between mining and forest conservation. A comparison was made between above ground biomass (AGB) and soil organic carbon (SOC) content from two reclaimed mine sites and adjacent undisturbed forest. Findings suggest that on decadal timescales, reclaimed mine sites contain approximately 40% of the total carbon and 10% the AGB carbon of undisturbed forest. This raises questions regarding the potential for decommissioning mine sites to provide forestry-based legacies. Such a move could deliver a host of benefits, including improving the longevity and success of reclamation, mitigating climate change and delivering corollary enumeration for local communities under carbon trading schemes. A discussion of the antecedents and challenges associated with establishing forest-legacies highlights the risk of neglecting the participation and heterogeneity of legitimate local representatives, which threatens the equity of potential benefits and sustainability of projects. Despite these risks, implementing pilot projects could help to address the lack of transparency and data which currently characterises mine reclamation.
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This paper seeks to increase the understanding of the performance implications for investors who choose to combine an unlisted real estate portfolio (in this case German Spezialfonds) with a (global) listed real estate element. We call this a “blended” approach to real estate allocations. For the avoidance of doubt, in this paper we are dealing purely with real estate equity (listed and unlisted) allocations, and do not incorporate real estate debt (listed or unlisted) or direct property into the process. A previous paper (Moss and Farrelly 2014) showed the benefits of the blended approach as it applied to UK Defined Contribution Pension Schemes. The catalyst for this paper has been the recent attention focused on German pension fund allocations, which have a relatively low (real estate) equity content, and a high bond content. We have used the MSCI Spezialfonds Index as a proxy for domestic German institutional real estate allocations, and the EPRA Global Developed Index as a proxy for a global listed real estate allocation. We also examine whether a rules based trading strategy, in this case Trend Following, can improve the risk adjusted returns above those of a simple buy and hold strategy for our sample period 2004-2015. Our findings are that by blending a 30% global listed portfolio with a 70% allocation (as opposed to a typical 100% weighting) to Spezialfonds, the real estate allocation returns increase from 2.88% p.a. to 5.42% pa. Volatility increases, but only to 6.53%., but there is a noticeable impact on maximum drawdown which increases to 19.4%. By using a Trend Following strategy raw returns are improved from 2.88% to 6.94% p.a. , The Sharpe Ratio increases from 1.05 to 1.49 and the Maximum Drawdown ratio is now only 1.83% compared to 19.4% using a buy and hold strategy . Finally, adding this (9%) real estate allocation to a mixed asset portfolio allocation typical for German pension funds there is an improvement in both the raw return (from 7.66% to 8.28%) and the Sharpe Ratio (from 0.91 to 0.98).
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This special issue is focused on the assessment of algorithms for the observation of Earth’s climate from environ- mental satellites. Climate data records derived by remote sensing are increasingly a key source of insight into the workings of and changes in Earth’s climate system. Producers of data sets must devote considerable effort and expertise to maximise the true climate signals in their products and minimise effects of data processing choices and changing sensors. A key choice is the selection of algorithm(s) for classification and/or retrieval of the climate variable. Within the European Space Agency Climate Change Initiative, science teams undertook systematic assessment of algorithms for a range of essential climate variables. The papers in the special issue report some of these exercises (for ocean colour, aerosol, ozone, greenhouse gases, clouds, soil moisture, sea surface temper- ature and glaciers). The contributions show that assessment exercises must be designed with care, considering issues such as the relative importance of different aspects of data quality (accuracy, precision, stability, sensitivity, coverage, etc.), the availability and degree of independence of validation data and the limitations of validation in characterising some important aspects of data (such as long-term stability or spatial coherence). As well as re- quiring a significant investment of expertise and effort, systematic comparisons are found to be highly valuable. They reveal the relative strengths and weaknesses of different algorithmic approaches under different observa- tional contexts, and help ensure that scientific conclusions drawn from climate data records are not influenced by observational artifacts, but are robust.
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Liquidity is a fundamentally important facet of investments, but there is no single measure that quantifies it perfectly. Instead, a range of measures are necessary to capture different dimensions of liquidity such as the breadth and depth of markets, the costs of transacting, the speed with which transactions can occur and the resilience of prices to trading activity. This article considers how different dimensions have been measured in financial markets and for various forms of real estate investment. The purpose of this exercise is to establish the range of liquidity measures that could be used for real estate investments before considering which measures and questions have been investigated so far. Most measures reviewed here are applicable to public real estate, but not all can be applied to private real estate assets or funds. Use of a broader range of liquidity measures could help real estate researchers tackle issues such as quantification of illiquidity premiums for the real estate asset class or different types of real estate, and how liquidity differences might be incorporated into portfolio allocation models.