57 resultados para liquidity profitability,

em CentAUR: Central Archive University of Reading - UK


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We evaluate the profitability and technical efficiency of aquaculture in the Philippines. Farm-level data are used to compare two production systems corresponding to the intensive monoculture of tilapia in freshwater ponds and the extensive polyculture of shrimps and fish in brackish water ponds. Both activities are very lucrative, with brackish water aquaculture achieving the higher level of profit per farm. Stochastic frontier production functions reveal that technical efficiency is low in brackish water aquaculture, with a mean of 53%, explained primarily by the operator's experience and by the frequency of his visits to the farm. In freshwater aquaculture, the farms achieve a mean efficiency level of 83%. The results suggest that the provision of extension services to brackish water fish farms might be a cost-effective way of increasing production and productivity in that sector. By contrast, technological change will have to be the driving force of future productivity growth in freshwater aquaculture.

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Research into the topic of liquidity has greatly benefited from the availability of data. Although bid-ask spreads were inaccessible to researchers, Roll (1984) provided a conceptual model that estimated the effective bid-ask prices from regular time series data, recorded on a daily or longer interval. Later data availability improved and researchers were able to address questions regarding the factors that influenced the spreads and the relationship between spreads and risk, return and liquidity. More recently transaction data have been used to measure the effective spread and researchers have been able to refine the concepts of liquidity to include the impact of transactions on price movements (Clayton and McKinnon, 2000) on a trade-by-trade analysis. This paper aims to use techniques that combine elements from all three approaches and, by studying US data over a relatively long time period, to throw light on earlier research as well as to reveal the changes in liquidity over the period controlling for extraneous factors such as market, age and size of REIT. It also reveals some comparable results for the UK market over the same period.

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Research on the topic of liquidity has greatly benefited from the improved availability of data. Researchers have addressed questions regarding the factors that influence bid-ask spreads and the relationship between spreads and risk, return and liquidity. Intra-day data have been used to measure the effective spread and researchers have been able to refine the concepts of liquidity to include the price impact of transactions on a trade-by-trade analysis. The growth in the creation of tax-transparent securities has greatly enhanced the visibility of securitized real estate, and has naturally led to the question of whether the increased visibility of real estate has caused market liquidity to change. Although the growth in the public market for securitized real estate has occurred in international markets, it has not been accompanied by universal publication of transaction data. Therefore this paper develops an aggregate daily data-based test for liquidity and applies the test to US data in order to check for consistency with the results of prior intra-day analysis. If the two approaches produce similar results, we can apply the same technique to markets in which less detailed data are available and offer conclusions on the liquidity of a wider set of markets.

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This paper draws from a wider research programme in the UK undertaken for the Investment Property Forum examining liquidity in commercial property. One aspect of liquidity is the process by which transactions occur including both how properties are selected for sale and the time taken to transact. The paper analyses data from three organisations; a property company, a major financial institution and an asset management company, formally a major public sector pension fund. The data covers three market states and includes sales completed in 1995, 2000 and 2002 in the UK. The research interviewed key individuals within the three organisations to identify any common patterns of activity within the sale process and also identified the timing of 187 actual transactions from inception of the sale to completion. The research developed a taxonomy of the transaction process. Interviews with vendors indicated that decisions to sell were a product of a combination of portfolio, specific property and market based issues. Properties were generally not kept in a “readiness for sale” state. The average time from first decision to sell the actual property to completion had a mean time of 298 days and a median of 190 days. It is concluded that this study may underestimate the true length of the time to transact for two reasons. Firstly, the pre-marketing period is rarely recorded in transaction files. Secondly, and more fundamentally, studies of sold properties may contain selection bias. The research indicated that vendors tended to sell properties which it was perceived could be sold at a ‘fair’ price in a reasonable period of time.

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This paper investigates the role of credit and liquidity factors in explaining corporate CDS price changes during normal and crisis periods. We find that liquidity risk is more important than firm-specific credit risk regardless of market conditions. Moreover, in the period prior to the recent “Great Recession” credit risk plays no role in explaining CDS price changes. The dominance of liquidity effects casts serious doubts on the relevance of CDS price changes as an indicator of default risk dynamics. Our results show how multiple liquidity factors including firm specific and aggregate liquidity proxies as well as an asymmetric information measure are critical determinants of CDS price variations. In particular, the impact of informed traders on the CDS price increases when markets are characterised by higher uncertainty, which supports concerns of insider trading during the crisis.

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Purpose – Commercial real estate is a highly specific asset: heterogeneous, indivisible and with less information transparency than most other commonly held investment assets. These attributes encourage the use of intermediaries during asset acquisition and disposal. However, there are few attempts to explain the use of different brokerage models (with differing costs) in different markets. This study aims to address this gap. Design/methodology/approach – The study analyses 9,338 real estate transactions in London and New York City from 2001 to 2011. Data are provided by Real Capital Analytics and cover over $450 billion of investments in this period. Brokerage trends in the two cities are compared and probit regressions are used to test whether the decision to transact with broker representation varies with investor or asset characteristics. Findings – Results indicate greater use of brokerage in London, especially by purchasers. This persists when data are disaggregated by sector, time or investor type, pointing to the role of local market culture and institutions in shaping brokerage models and transaction costs. Within each city, the nature of the investors involved seems to be a more significant influence on broker use than the characteristics of the assets being traded. Originality/value – Brokerage costs are the single largest non-tax charge to an investor when trading commercial real estate, yet there is little research in this area. This study examines the role of brokers and provides empirical evidence on factors that influence the use and mode of brokerage in two major investment destinations.

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Research has highlighted the usefulness of the Gilt–Equity Yield Ratio (GEYR) as a predictor of UK stock returns. This paper extends recent studies by endogenising the threshold at which the GEYR switches from being low to being high or vice versa, thus improving the arbitrary nature of the determination of the threshold employed in the extant literature. It is observed that a decision rule for investing in equities or bonds, based on the forecasts from a regime switching model, yields higher average returns with lower variability than a static portfolio containing any combinations of equities and bonds. A closer inspection of the results reveals that the model has power to forecast when investors should steer clear of equities, although the trading profits generated are insufficient to outweigh the associated transaction costs.

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This paper examines the effects of liquidity during the 2007–09 crisis, focussing on the Senior Tranche of the CDX.NA.IG Index and on Moody's AAA Corporate Bond Index. It aims to understand whether the sharp increase in the credit spreads of these AAA-rated credit indices can be explained by worse credit fundamentals alone or whether it also reflects a lack of depth in the relevant markets, the scarcity of risk-capital, and the liquidity preference exhibited by investors. Using cointegration analysis and error correction models, the paper shows that during the crisis lower market and funding liquidity are important drivers of the increase in the credit spread of the AAA-rated structured product, whilst they are less significant in explaining credit spread changes for a portfolio of unstructured credit instruments. Looking at the experience of the subprime crisis, the study shows that when the conditions under which securitisation can work properly (liquidity, transparency and tradability) suddenly disappear, investors are left highly exposed to systemic risk.

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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.