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Freight Transport Modelling
Type: Book
ISBN: 978-1-78190-286-8

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Article
Publication date: 31 December 2019

Vaibhav Lalwani and Madhumita Chakraborty

The purpose of this paper is to compare the performance of various multifactor asset pricing models across ten emerging and developed markets.

Abstract

Purpose

The purpose of this paper is to compare the performance of various multifactor asset pricing models across ten emerging and developed markets.

Design/methodology/approach

The general methodology to test asset pricing models involves regressing test asset returns (left-hand side assets) on pricing factors (right-hand side assets). Then the performance of different models is evaluated based on how well they price multiple test assets together. The parameters used to compare relative performance of different models are their pricing errors (GRS statistic and average absolute intercepts) and explained variation (average adjusted R2).

Findings

The Fama-French five-factor model improves the pricing performance for stocks in Australia, Canada, China and the USA. The pricing in these countries appears to be more integrated. However, the superior performance in these four countries is not consistent across a variety of test assets and the magnitude of reduction in pricing errors vis-à-vis three- or four-factor models is often economically insignificant. For other markets, the parsimonious three-factor model or its four-factor variants appear to be more suitable.

Originality/value

Unlike most asset pricing studies that use test assets based on variables that are already used to construct RHS factors, this study uses test assets that are generally different from RHS sorts. This makes the tests more robust and less biased to be in favour of any multifactor model. Also, most international studies of asset pricing tests use data for different markets and combine them into regions. This study provides the evidence from ten countries separately because prior research has shown that locally constructed factors are more suitable to explain asset prices. Further, this study also tests for the usefulness of adding a quality factor in the existing asset pricing models.

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Managerial Finance, vol. 46 no. 3
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 2 October 2007

Daniel O. Rice

The purpose of this paper is to present a P2P network security pricing model that promotes more secure online information sharing in P2P networks through the creation of…

Abstract

Purpose

The purpose of this paper is to present a P2P network security pricing model that promotes more secure online information sharing in P2P networks through the creation of networks with increased resistance to malicious code propagation. Online information sharing is at an all‐time high partly due to the recent growth in, and use of, online peer‐to‐peer (P2P) networks.

Design/methodology/approach

The model integrates current research findings in incentive compatible network pricing with recent developments in complex network theory. File download prices in P2P networks are linked to network security using a graph theory measurement called the Pearson coefficient. The Pearson coefficient indicates a structural dimension of scale‐free networks (scale‐free networks like the internet) called preferential attachment. Preferential attachment refers to the network property where the probability for a node to connect to a new node is greater if the new node already has a high number of connections.

Findings

The P2P network security pricing model concept is illustrated to show how the model functions to create more secure P2P networks.

Research limitations/implications

Future research in P2P network security pricing should focus on testing the model presented in this paper by numerical experiments and simulation including the tracking of malicious code propagation on networks grown under the pricing model.

Originality/value

The P2P network security pricing model demonstrated here is a different approach to network security that has a strong potential to impact on the future security of P2P and other computer based networks.

Details

Online Information Review, vol. 31 no. 5
Type: Research Article
ISSN: 1468-4527

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Article
Publication date: 10 August 2015

Aaron Wolfgang Baur, Julian Bühler and Markus Bick

The purpose of this paper is to investigate the development of software pricing, following the advent of cloud-based business intelligence & analytics…

Abstract

Purpose

The purpose of this paper is to investigate the development of software pricing, following the advent of cloud-based business intelligence & analytics (BI & A) Software. A value-based conceptual software model is developed to ignite and structure further research.

Design/methodology/approach

A two-step research approach is applied. In step one, the available literature is screened and evaluated, and this is followed by ten semi-structured expert interviews. With that input, a conceptual software pricing model is designed. In step two, this model is validated and refined through discussions with representatives of the five leading business intelligence suites.

Findings

The paper sheds light on the value perception of customers and suggests a clear focus on the interaction between customers and vendors, and less on technical issues. The developed customer-centric, value-based pricing framework helps to improve pricing techniques and strategies.

Research limitations/implications

The research is focused on the pricing strategy of software houses and excludes differentiations of technical specifications and functionalities.

Practical implications

The research can support practitioners in the field of BI & A in rethinking their pricing methods. Placing the customer at center stage can lead to lower customer churn rates, higher customer satisfaction and more pricing flexibility.

Originality/value

This empirical study reveals the importance of a customer-centric pricing approach in the specific case of BI & A. It can also be applied to other fast-developing sectors of the software industry.

Details

Journal of Systems and Information Technology, vol. 17 no. 3
Type: Research Article
ISSN: 1328-7265

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Article
Publication date: 3 August 2015

Vipul Kumar Singh

The purpose of this paper is to investigate empirically the forecasting performance of jump-diffusion option pricing models of (Merton and Bates) with the benchmark…

Abstract

Purpose

The purpose of this paper is to investigate empirically the forecasting performance of jump-diffusion option pricing models of (Merton and Bates) with the benchmark Black–Scholes (BS) model relative to market, for pricing Nifty index options of India. The specific period chosen for this study canvasses the extreme up and down limits (jumps) of the Indian capital market. In addition, equity markets keep on facing high and low tides of financial flux amid new economic and financial considerations. With this backdrop, the paper focuses on finding an impeccable option-pricing model which can meet the requirements of option traders and practitioners during tumultuous periods in the future.

Design/methodology/approach

Envisioning the fact, the all option-pricing models normally does wrong valuation relative to market. For estimating the structural parameters that governs the underlying asset distribution purely from the underlying asset return data, we have used the nonlinear least-square method. As an approach, we analyzed model prices by dividing the option data into 15 moneyness-maturity groups – depending on the time to maturity and strike price. The prices are compared analytically by continuously updating the parameters of two models using cross-sectional option data on daily basis. Estimated parameters then used to figure out the forecasting performance of models with corresponding BS and market – for pricing day-ahead option prices and implied volatility.

Findings

The outcomes of the paper reveal that the jump-diffusion models are a better substitute of classical BS, thus improving the pricing bias significantly. But compared to jump-diffusion model of Merton’s, the model of Bates’ can be applied more uniquely to find out the pricing of three popularly traded categories: deep-out-of-the-money, out-of-the-money and at-the-money of Nifty index options.

Practical implications

The outcome of this research work reveals that the jumps are important components of pricing dynamics of Nifty index options. Incorporation of jump-diffusion process into option pricing of Nifty index options leads to a higher pricing effectiveness, reduces the pricing bias and gives values closer to the market. As the models have been tested in extreme conditions to determine the dominant effectuality, the outcome of this paper helps traders in keeping the investment protected under normal conditions.

Originality/value

The specific period chosen for this study is very unique; it canvasses the extreme up and down limits (jumps) of the Indian capital market and provides the most apt situation for testifying the pricing competitiveness of the models in question. To testify the robustness of models, they have been put into a practical implication of complete cycle of financial frame.

Details

Studies in Economics and Finance, vol. 32 no. 3
Type: Research Article
ISSN: 1086-7376

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Article
Publication date: 15 February 2016

Yiming Hu, Xinmin Tian and Zhiyong Zhu

In capital market, share prices of listed companies generally respond to accounting information. In 1995, Ohlson proposed a share valuation model based on two accounting…

Abstract

Purpose

In capital market, share prices of listed companies generally respond to accounting information. In 1995, Ohlson proposed a share valuation model based on two accounting indicators: company residual income and book value of net asset. In 2000, Zhang introduced the thought of option pricing and developed a new accounting valuation model. The purpose of this paper is to investigate the valuation deviation and the influence of some market transaction characteristics on pricing models.

Design/methodology/approach

The authors use listed companies from 1999 to 2013 as samples, and conduct comparative analysis with multiple regression.

Findings

The main findings are: first, the accounting valuation model is applicable to the capital market as a whole, and its pricing effect increases as years go by; second, in the environment of out capital market, the maturity of investors is one of important factors that causes the information content of residual income less than that of profit per share and lower pricing effect of valuation models; third, when the price earning (PE) of listed companies reaches certain level, the overall explanation capacity of accounting valuation models will become lower as PE gets higher; fourth, as for companies with higher turnover rate and more active transaction, the pricing effect of accounting valuation model is obviously lower; fifth, the pricing effect of accounting valuation models in a bull market is lower than in a bear market.

Originality/value

These findings establish connection between accounting valuation and market transaction characteristics providing an explorable orientation for the future development of accounting valuation theories and models.

Details

China Finance Review International, vol. 6 no. 1
Type: Research Article
ISSN: 2044-1398

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Article
Publication date: 8 October 2018

Aparna Prasad Bhat

The purpose of this paper is to ascertain the effectiveness of major deterministic and stochastic volatility-based option pricing models in pricing and hedging…

Abstract

Purpose

The purpose of this paper is to ascertain the effectiveness of major deterministic and stochastic volatility-based option pricing models in pricing and hedging exchange-traded dollar–rupee options over a five-year period since the launch of these options in India.

Design/methodology/approach

The paper examines the pricing and hedging performance of five different models, namely, the Black–Scholes–Merton model (BSM), skewness- and kurtosis-adjusted BSM, NGARCH model of Duan, Heston’s stochastic volatility model and an ad hoc Black–Scholes (AHBS) model. Risk-neutral structural parameters are extracted by calibrating each model to the prices of traded dollar–rupee call options. These parameters are used to generate out-of-sample model option prices and to construct a delta-neutral hedge for a short option position. Out-of-sample pricing errors and hedging errors are compared to identify the best-performing model. Robustness is tested by comparing the performance of all models separately over turbulent and tranquil periods.

Findings

The study finds that relatively simpler models fare better than more mathematically complex models in pricing and hedging dollar–rupee options during the sample period. This superior performance is observed to persist even when comparisons are made separately over volatile periods and tranquil periods. However the more sophisticated models reveal a lower moneyness-maturity bias as compared to the BSM model.

Practical implications

The study concludes that incorporation of skewness and kurtosis in the BSM model as well as the practitioners’ approach of using a moneyness-maturity-based volatility within the BSM model (AHBS model) results in better pricing and hedging effectiveness for dollar–rupee options. This conclusion has strong practical implications for market practitioners, hedgers and regulators in the light of increased volatility in the dollar–rupee pair.

Originality/value

Existing literature on this topic has largely centered around either US equity index options or options on major liquid currencies. While many studies have solely focused on the pricing performance of option pricing models, this paper examines both the pricing and hedging performance of competing models in the context of Indian currency options. Robustness of findings is tested by comparing model performance across periods of stress and tranquility. To the best of the author’s knowledge, this paper is one of the first comprehensive studies to focus on an emerging market currency pair such as the dollar–rupee.

Details

Journal of Indian Business Research, vol. 11 no. 1
Type: Research Article
ISSN: 1755-4195

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Article
Publication date: 1 February 2021

Ling Liang, Lin Tian, Jiaping Xie, Jianhong Xu and Weisi Zhang

The car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing

Abstract

Purpose

The car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing strategies, which are business-to-consumer and consumer-to-consumer modes, market pricing and platform pricing. Under these conditions, the platform's revenue-sharing ratio will be different. The purpose of this paper is to explore this research question, and seeks an optimal pricing mechanism that can achieve a win–win situation between platform and automobile manufacturer in the two market modes.

Design/methodology/approach

The authors design different profit functions for platform under the two contexts. Of course, the platform's function is constrained to the manufacturer's function. By introducing a revenue-sharing contract a Stackelberg game model dominated by the platform is established and the equilibrium solutions under the two pricing models are derived.

Findings

The study found that even if only market pricing is executed, the scale of the car-sharing market will continue to expand. As the car-sharing market becomes more saturated, platform pricing is better for the automobile manufacturer; in most cases, the platform prefers platform pricing, but when the number of private cars is relatively small, if the cost of car operation and maintenance for the automobile manufacturer is lower or the revenue-sharing ratio of private cars is high, then market pricing will be more favorable to the platform.

Practical implications

With the cross-border integration of car service platforms and the automobile manufacturing industry, the key to achieving win–win cooperation and sustainable development in the car-sharing market will converge on the question of how to design a suitable pricing mechanism and revenue-sharing method.

Originality/value

Authors have determined how a car-sharing platform achieves a win–win order pricing strategy with the manufacturer and private car owners, respectively. And authors combined the supply chain revenue-sharing contract with the car-sharing market to explore the application of the revenue-sharing contract in the sharing economy.

Details

Industrial Management & Data Systems, vol. 121 no. 3
Type: Research Article
ISSN: 0263-5577

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Book part
Publication date: 23 December 2005

David Ng and Mehdi Sadeghi

This paper studies the empirical application of an asset pricing model derived from the irrational individual behavior of loss aversion. Previous research using loss…

Abstract

This paper studies the empirical application of an asset pricing model derived from the irrational individual behavior of loss aversion. Previous research using loss aversion asset pricing finds conclusive evidence that estimations match market equity premium and volatility using simulation data. We find that within its empirical application, the estimated errors are comparable to errors estimated from the capital asset pricing model. This study of the correlations between rational and irrational asset pricing model from the empirical results finds validity for both estimated values. Finally, we see the importance of cultures, economic development and financial development on asset pricing through an empirical examination of five pacific-basin countries in the estimation of asset pricing models.

Details

Asia Pacific Financial Markets in Comparative Perspective: Issues and Implications for the 21st Century
Type: Book
ISBN: 978-0-76231-258-0

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Article
Publication date: 28 December 2020

Can-Zhong Yao and Yi-Na Mo

The purpose of this paper is to whether competition between platforms can be effective, thus leading to efficient allocations.

Abstract

Purpose

The purpose of this paper is to whether competition between platforms can be effective, thus leading to efficient allocations.

Design/methodology/approach

Based on the classic linear Hoteling model, this paper builds a two-period competition model for two competing platforms using two variants, namely, a discrimination pricing model and a unified pricing model.

Findings

In the case of the discrimination pricing model, the competition is moderate, and the two platforms split the market evenly in the first stage, while both platforms tended to offer preferential treatment to new users and set higher prices for regular customers in the second stage. Compared to the unified pricing model, in the first stage, the platform can provide a higher price that depends on the cross-network effect when it implements discrimination, and thus, obtains higher profits. However, in the second stage, fierce competition leads to the release of benefits, new and regular customers obtain lower prices and the platforms lose higher profits. In the long-run, discriminatory pricing is not the best option due to lower total profits. The two platforms will implement cooperative pricing or one platform becomes dominant.

Originality/value

Instead of focusing on the cross-network effects, this paper emphasizes the role of the same-side network effect on price discrimination regarding the platforms’ competition. The same-side network effects are investigated in relation to a discrimination pricing strategy and compared to a unified pricing strategy. Another innovative aspect is the study of these network effects in a dynamic setting based on a two-period competition model for two platforms.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

1 – 10 of over 100000