139 research outputs found
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User characteristics: Professional vs. lay users
(User characteristics: professional use vs lay use by Cifter A and Dong H)
The market success of a product largely depends on whether it correctly addresses the user needs. Understanding the user is increasingly becoming important in the design process. Different user models may determine different approaches to design. This paper identifies the characteristics of different types of users, with a specific focus on professional users and lay users. It gives a definition of professional users and lay users in the context of adapting products originally designed for professional use to the use of lay people (for example, home use medical devices). It summarises, and compares, the characteristics of professional users and lay users, suggesting that designers pay attention to user characteristics and the context of use so as to better address user perceptions and meet user needs
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Lay-user characteristics reflected by their interaction with a digital camera and a blood pressure monitor
The material is posted here with the permission of the publishers. Internal or personal use of this material is permitted. However, permission to reprint/republish this material must be obtained from the publisher.There is an increasing and evolving demand from the end-user market for the adaptation of products originally designed for professional-use to the use of lay people, for example, home use medical devices. However, there is a lack of understanding of lay user characteristics by product designers. This paper reports a study investigating lay user characteristics reflected by their interaction with digital products. A digital camera and a digital blood pressure monitor were tested with different user groups: 10 able-bodied young people; 10 healthy older people (65+) and 10 disabled people; and lay user characteristics were summarised
Nonlinear Combination of Financial Forecast with Genetic Algorithm
Complexity in the financial markets requires intelligent forecasting models for return volatility. In this paper, historical simulation, GARCH, GARCH with skewed student-t distribution and asymmetric normal mixture GRJ-GARCH models are combined with Extreme Value Theory Hill by using artificial neural networks with genetic algorithm as the combination platform. By employing daily closing values of the Istanbul Stock Exchange from 01/10/1996 to 11/07/2006, Kupiec and Christoffersen tests as the back-testing mechanisms are performed for forecast comparison of the models. Empirical findings show that the fat-tails are more properly captured by the combination of GARCH with skewed student-t distribution and Extreme Value Theory Hill. Modeling return volatility in the emerging markets needs âintelligentâ combinations of Value-at-Risk models to capture the extreme movements in the markets rather than individual model forecast.Forecast combination; Artificial neural networks; GARCH models; Extreme value theory; Christoffersen test
Portfolio Value-at-Risk with Time-Varying Copula: Evidence from the Americas
Model risk in the estimation of value-at-risk is a challenging threat for the success of any financial investments. The degree of the model risk increases when the estimation process is constructed with a portfolio in the emerging markets. The proper model should both provide flexible joint distributions by splitting the marginality from the dependencies among the financial assets within the portfolio and also capture the non-linear behaviours and extremes in the returns arising from the special features of the emerging markets. In this paper, we use time-varying copula to estimate the value-at-risk of the portfolio comprised of the Bovespa and the IPC Mexico in equal and constant weights. The performance comparison of the copula model to the EWMA portfolio model made by the Christoffersen back-test shows that the copula model captures the extremes most successfully. The copula model, by estimating the portfolio value-at-risk with the least violation number in the back-tests, provides the investors to allocate the minimum regulatory capital requirement in accordance with the Basel II Accord.Time-varying Copula; portfolio value-at-risk; Latin American equity markets; portfolio GARCH
Estimating the Effects of Interest Rates on Share Prices Using Multi-scale Causality Test in Emerging Markets: Evidence from Turkey
This paper examines the impacts of changes in interest rates on stock returns by using wavelet analysis with Granger causality test. Financial time series in non-coherent markets should be analyzed by advanced methods capturing complexity of the markets and non-linearities in stock returns. As a semi-parametric method, wavelets analysis might be superior to detect the chaotic patterns in the non-coherent markets. By using daily closing values of the ISE 100 Index and compounded interest rates, it is proven that and starting with 9 days time-scale effect interest rate is granger cause of ISE 100 index and the effects of interest rates on stock return increases with higher time-scales. This evidence shows that bond market has significant long-term effect on stock market for Turkey and traders should consider long-term money markets changes as well as short-term changes.Interest rates; Emerging markets; Wavelets; Stock returns; Multi-scale Granger causality
The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey
The purpose of this study is to test predictive performance of Asymmetric Normal Mixture Garch (NMAGARCH) and other Garch models based on Kupiec and Christoffersen tests for Turkish equity market. The empirical results show that the NMAGARCH perform better based on %99 CI out-of-sample forecasting Christoffersen test where Garch with normal and student-t distribution perform better based on %95 Cl out-of-sample forecasting Christoffersen test and Kupiec test. These results show that none of the model including NMAGARCH outperforms other models in all cases as trading position or confidence intervals and these results shows that volatility model should be chosen according to confidence interval and trading positions. Besides, NMAGARCH increases predictive performance for higher confidence internal as Basel requires.Garch; Asymmetric Normal Mixture Garch; Kupiec Test; Christoffersen Test; Emerging markets
The Effects of International F/X Markets on Domestic Currencies Using Wavelet Networks: Evidence from Emerging Markets
This paper proposes a powerful methodology wavelet networks to investigate the effects of international F/X markets on emerging markets currencies. We used EUR/USD parity as input indicator (international F/X markets) and three emerging markets currencies as Brazilian Real, Turkish Lira and Russian Ruble as output indicator (emerging markets currency). We test if the effects of international F/X markets change across different timescale. Using wavelet networks, we showed that the effects of international F/X markets increase with higher timescale. This evidence shows that the causality of international F/X markets on emerging markets should be tested based on 64-128 days effect. We also find that the effects of EUR/USD parity on Turkish Lira is higher on 17-32 days and 65-128 days scales and this evidence shows that Turkish lira is less stable compare to other emerging markets currencies as international F/X markets effects Turkish lira on shorten time scale.F/X Markets; Emerging markets; Wavelet networks; Wavelets; Neural networks
The Effect of Scale on Productivity of Turkish Banks in the Post-Crises Period: An Application of Data Envelopment Analysis
The purpose of this paper is to investigate the productivity of Turkish Banks according to the effect of scale in the Post-Crises Period. The data used in this study covers the period from 2002:1 to 2004:3. We applied Data Envelopment Analysis (DEA), which is a non-parametric linear programming-based technique for measuring relative performance of decision-making units (DMUs). We calculated DEA as constant & variable return-to-scale based on output oriented Malmquist Index. Although the scale effect can be measured with DEA scale efficiency measurement, we used scale indicators as input variables in order to find out not only scale efficiency but also scale affect directly. We applied DEA by using financial ratios (Athanassopoulos and Ballantine, 1995; Yeh, 1996) and branch & personel number indicators. This study uses five input variables as i) branch numbers, ii) personnel number per branch, iii) share in total assets, iv) share in total loans, v) share in total deposits; and five output variables as i) net profit-losses/total assets (ROA), ii) net profit-losses/total shareholders equity (ROE), iii) net interest income/total assets, iv) net interest income/ total operating income, and v) noninterest income/total assets. We find that difference in efficiency is mainly from technical efficiency rather than scale efficiency in the post-crises period. The other finding reveals that efficiency approximate between selected banks and supporting that advantage of scale economies can be lost in Turkish banking. Overall, the results confirm that Turkish banking has U shaped Scale Efficiency on selected profitability ratios. The application of this paper based on other financial ratios with decreasing and increasing return-to-scale DEA is left to future research.Turkish Banks; Return to Scale; Scale Efficiency; Profit Efficiency; Data Envelopment Analysis
Multi-scale Causality between Energy Consumption and GNP in Emerging Markets: Evidence from Turkey
Tests results for causality between energy consumption and economic growth do not have a consensus in the financial economics literature. Empirical evidence varies on the economies examined and methodology employed. This paper proposes a wavelet analysis as a semi- parametric model for detecting multi-scale causality between electricity consumption and growth in emerging economies. Using wavelet analysis we find that in the short run there is feedback relationship between GNP and energy consumption, while in the long run GNP leads to energy consumption. Wavelet correlation between GNP and energy consumption is maximum at 3rd time-scale(5-8 years) and this shows that GNP effects electricity consumption maximally around 5-8 years later in the long-run. We also find that the magnitude of the wavelet correlation changes based on time-scales for GNP and energy consumption and thus indicate that GNP and energy consumption are fundamentally different in the long run.Economic Growth; Energy Consumption; Employment; Wavelets; Causality
Monetary Transmission Mechanism in the New Economy: Evidence from Turkey (1997-2006)
This study aims to test the money base, money supply, credit capacity, industrial production index, interest rates, inflation and real exchange rate data of Turkey during the years 1997 â 2006 through the monetary transmission mechanism and passive money hypothesis using the vector error correction model based causality test. Empirical findings show that the passive money supply hypothesis of the new Keynesian economy is supported in part by accommodationalist views and they do not confirm to the view points of structuralist and liquidity preference theorist. However, according to the monetary transmission mechanism it has been established that long-term money supply only affects general price levels and production is influenced by interest rates in the new economy period for Turkish economy. Empirical findings show that in the new economy period interest transmission mechanism are brought to the fore.Monetary transmission mechanism; money supply endogeneity; Credit; New Keynesian Economy
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