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Article
Publication date: 23 October 2020

Dan Tang and Xintian Zhuang

Blockchain-driven supply chain finance (BCT-SCF) has recently been receiving increased global attention. A number of business programmes have been carried out using this…

Abstract

Purpose

Blockchain-driven supply chain finance (BCT-SCF) has recently been receiving increased global attention. A number of business programmes have been carried out using this approach, but existing research has rarely focussed on this novel SCF model. This paper aims to fill this gap by proposing a mathematical model to analyse the value of BCT-SCF.

Design/methodology/approach

First, this paper considers a multi-period two-echelon supply chain consisting of a capital-constrained supplier and a newsvendor-like retailer. Then, two financing channels are proposed. The supply chain actors can either factor accounts receivable (AR) from a bank or obtain financing through a BCT-SCF platform by which AR can be converted into a bill receivable and used to make payment. Further, to investigate the preferences of all actors between the two financing channels, this paper compares the two channels and examines how the degree of financial constraints and the cost of implementing the BCT-SCF model impact the financing preferences of all actors.

Findings

BCT-SCF model can help a supply chain realise its optimisation both in production and financing efficiency, the preference for the BCT-SCF model increases as the initial capital of supplier and the BCT-SCF platform usage fee rate decrease.

Practical implications

This research bridges the gap between theoretical analysis of BCT-SCF and its realistic application. The results demonstrate that with the BCT-SCF model, a win-win situation among supply chain actors is possible, which is helpful for the supply chain to choose a more efficient financing channel.

Originality/value

This research introduces a mathematical model based on the “receivable chain” of CZBank and the model is set in a multi-period supply chain, which is the first time BCT-SCF has been considered as part of a more complex but realistic background setting.

Details

Kybernetes, vol. 50 no. 8
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 28 January 2014

Harald Kinateder and Niklas Wagner

– The paper aims to model multiple-period market risk forecasts under long memory persistence in market volatility.

Abstract

Purpose

The paper aims to model multiple-period market risk forecasts under long memory persistence in market volatility.

Design/methodology/approach

The paper proposes volatility forecasts based on a combination of the GARCH(1,1)-model with potentially fat-tailed and skewed innovations and a long memory specification of the slowly declining influence of past volatility shocks. As the square-root-of-time rule is known to be mis-specified, the GARCH setting of Drost and Nijman is used as benchmark model. The empirical study of equity market risk is based on daily returns during the period January 1975 to December 2010. The out-of-sample accuracy of VaR predictions is studied for 5, 10, 20 and 60 trading days.

Findings

The long memory scaling approach remarkably improves VaR forecasts for the longer horizons. This result is only in part due to higher predicted risk levels. Ex post calibration to equal unconditional VaR levels illustrates that the approach also enhances efficiency in allocating VaR capital through time.

Practical implications

The improved VaR forecasts show that one should account for long memory when calibrating risk models.

Originality/value

The paper models single-period returns rather than choosing the simpler approach of modeling lower-frequency multiple-period returns for long-run volatility forecasting. The approach considers long memory in volatility and has two main advantages: it yields a consistent set of volatility predictions for various horizons and VaR forecasting accuracy is improved.

Details

The Journal of Risk Finance, vol. 15 no. 1
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 22 February 2021

Reza Sakiani, Abbas Seifi and Reza Ramezani Khorshiddost

There is usually a considerable shortage of resources and a lack of accurate data about the demand amount in a post-disaster situation. This paper aims to model the…

Abstract

Purpose

There is usually a considerable shortage of resources and a lack of accurate data about the demand amount in a post-disaster situation. This paper aims to model the distribution and redistribution of relief items. When the new data on demand and resources become available the redistribution of previously delivered items may be necessary due to severe shortages in some locations and surplus inventory in other areas.

Design/methodology/approach

The presented model includes a vehicle routing problem in the first period and some network flow structures for succeeding periods of each run. Thereby, it can produce itineraries and loading plans for each vehicle in all periods when it is run in a rolling horizon manner. The fairness in distribution is sought by minimizing the maximum shortage of commodities among the affected areas while considering operational costs. Besides, equity of welfare in different periods is taken into account.

Findings

The proposed model is evaluated by a realistic case study. The results show that redistribution and multi-period planning can improve efficiency and fairness in supply after the occurrence of a disaster.

Originality/value

This paper proposes an operational model for distribution and redistribution of relief items considering the differences of items characteristics. The model integrates two well-known structures, vehicle routing problem with pickup and delivery and network flow problem to take their advantages. To get more practical results, the model relaxes some simplifying assumptions commonly used in disaster relief studies. Furthermore, the model is used in a realistic case study.

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Book part
Publication date: 29 February 2008

Jennifer L. Castle and David F. Hendry

Structural models' inflation forecasts are often inferior to those of naïve devices. This chapter theoretically and empirically assesses this for UK annual and quarterly…

Abstract

Structural models' inflation forecasts are often inferior to those of naïve devices. This chapter theoretically and empirically assesses this for UK annual and quarterly inflation, using the theoretical framework in Clements and Hendry (1998, 1999). Forecasts from equilibrium-correction mechanisms, built by automatic model selection, are compared to various robust devices. Forecast-error taxonomies for aggregated and time-disaggregated information reveal that the impacts of structural breaks are identical between these, helping to interpret the empirical findings. Forecast failures in structural models are driven by their deterministic terms, confirming location shifts as a pernicious cause thereof, and explaining the success of robust devices.

Details

Forecasting in the Presence of Structural Breaks and Model Uncertainty
Type: Book
ISBN: 978-1-84950-540-6

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Article
Publication date: 1 June 2010

Eleftherios Giovanis

The purpose of this paper is to examine two different approaches in the prediction of the economic recession periods in the US economy.

Abstract

Purpose

The purpose of this paper is to examine two different approaches in the prediction of the economic recession periods in the US economy.

Design/methodology/approach

A logit regression was applied and the prediction performance in two out‐of‐sample periods, 2007‐2009 and 2010 was examined. On the other hand, feed‐forwards neural networks with Levenberg‐Marquardt error backpropagation algorithm were applied and then neural networks self‐organizing map (SOM) on the training outputs was estimated.

Findings

The paper presents the cluster results from SOM training in order to find the patterns of economic recessions and expansions. It is concluded that logit model forecasts the current financial crisis period at 75 percent accuracy, but logit model is useful as it provides a warning signal three quarters before the current financial crisis started officially. Also, it is estimated that the financial crisis, even if it reached its peak in 2009, the economic recession will be continued in 2010 too. Furthermore, the patterns generated by SOM neural networks show various possible versions with one common characteristic, that financial crisis is not over in 2009 and the economic recession will be continued in the USA even up to 2011‐2012, if government does not apply direct drastic measures.

Originality/value

Both logistic regression (logit) and SOMs procedures are useful. The first one is useful to examine the significance and the magnitude of each variable, while the second one is useful for clustering and identifying patterns in economic recessions and expansions.

Details

Journal of Financial Economic Policy, vol. 2 no. 2
Type: Research Article
ISSN: 1757-6385

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Article
Publication date: 28 November 2019

Morteza Bayat, Mostafa Khanzadi, Farnad Nasirzadeh and Ali Chavoshian

This study aims to determine the optimal value of concession period length in combination with capital structure in build–operate–transfer (BOT) contracts, based on direct…

Abstract

Purpose

This study aims to determine the optimal value of concession period length in combination with capital structure in build–operate–transfer (BOT) contracts, based on direct negotiation procurement and considering the conflicting financial interests of different parties involved in the project.

Design/methodology/approach

The financial model of a BOT project is developed considering all the influencing factors. Then, fuzzy set theory is used to take into account the existing risks and uncertainties. Bilateral bargaining game based on alternating-offers protocol is applied between the government and the sponsor to divide project financial benefit considering the lender’s requirements. Finally, concession period and equity level will be determined simultaneously according to the sponsor’s and government’s share of project financial benefit and the lender’s requirements.

Findings

The proposed model is implemented on a real case study, and a fair and efficient agreement on concession period length and capital structure is achieved between the government and the sponsor considering the lender’s requirements. It is revealed that being the first proposer in the bargaining process will affect the concession period length; however, it will not affect the equity level. Moreover, it is shown that considering income tax as a part of government’s financial benefit increases the length of concession period.

Research limitations/implications

The presented model concentrates on direct negotiation procurement in BOT projects where the sponsor and government bargain on dividing financial benefits of project. It is assumed that the product/service price is determined before according to market analysis or users’ affordability. All the revenue of project during concession period is assumed to belong to the sponsor.

Practical implications

The proposed model provides a practical tool to aid BOT participants to reach a fair and efficient agreement on concession period and capital structure. This could prevent failing or prolonging the negotiation and costly renegotiation.

Originality/value

By investigation of previous studies, it is revealed that none of them can determine the optimal value of concession period length and capital structure simultaneously considering the BOT negotiation process and different financial interests of parties involved in the project. The proposed model presents a new approach to determine the financial variables considering the conflicting interests of involved parties. The other novelty aspects of the presented model are as follows: introducing a new approach for calculating the sponsor and the government’s share of project financial benefit that will affect the determination of the concession period length and considering the effect of existing risks and uncertainties on final agreement between the involved parties using fuzzy set theory.

Details

Construction Innovation , vol. 20 no. 1
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 11 February 2019

Md. Tanweer Ahmad and Sandeep Mondal

This paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a…

Abstract

Purpose

This paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining equipment company (MEC). Practically, involved parameters’ value does not remain constant as planning periods due to fluctuation in the demand and their market dynamics. Therefore, dynamicity in the parameter is considered as an important factor when a company forms a responsive chain through most eligible suppliers with respect to planning periods. This area of study may be considered for their complexities to the approaches toward order-allocations with bi-products of unused and repair spare-parts.

Design/methodology/approach

An integrated methodology of analytic hierarchy process (AHP) and mixed-integer non-linear programming (MILP) is implemented in the two stages during each planning periods. In the first stage, AHP is used to obtain the relative weights with respect to each spare-parts of each criterion and based on that, the ranking is evaluated in accordance with case considered. And in the second stage, MILP is formulated to find the allocations of each spare-part with two distinct approaches through Model-1 and Model-2 separately. Moreover, Model-1 and Model-2 are outlined based on the ranking and efficient parameters-value under cost, limited capacities, quality level and delay lead time respectively.

Findings

The ranking and their optimal order-allocation of potential suppliers are obtained during consecutive planning periods for both unused and repair spare-parts. Subsequently, sensitivity analysis is conducted to deduce the key nuggets with the comparison of Model-1 and Model-2 in the changing of capacity, demand and cost per spare-parts. From this analysis, it is found that suppliers who have optimal parameter settings would be better for order-allocations than ranking during the changing planning period.

Practical implications

This paper points out the situation-specific approach for SS problem for a mining industry which often faces disruptive supplying environments. The managerial implication between ranking and parameters are highlighted through Model-1 and Model-2 by sensitivity analysis.

Originality/value

It provides useful directions for managers who are involved in the procurement of spare-parts in the mining environment. For this, suppliers are selected for order-allocation by using Model-1 and Model-2 in the dynamic business environment. The solvability of the model is presented using LINGO 17. Furthermore, the case company selected in this study can be extended to other sectors.

Details

Journal of Modelling in Management, vol. 14 no. 1
Type: Research Article
ISSN: 1746-5664

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Article
Publication date: 17 December 2020

Haytem Troug and Matt Murray

The purpose of this paper then, is to add to the existing literature on financial contagion. While a vast amount of the debate has been made using data from the late…

Abstract

Purpose

The purpose of this paper then, is to add to the existing literature on financial contagion. While a vast amount of the debate has been made using data from the late 1990s, this paper differentiates itself by analysing more current data, centred around the most recent global financial crisis, with specific focus on the stock markets of Hong Kong and Tokyo.

Design/methodology/approach

Employing Pearson and Spearman correlation measures, the dynamic relationship of the two markets is determined over tranquil and crisis periods, as specified by an Markov-Switching Bayesian Vector AutoRegression (MSBVAR) model.

Findings

The authors find evidence in support of the existence of financial contagion (defined as an increase in correlation during a crisis period) for all frequencies of data analysed. This contagion is greatest when examining lower-frequency data. Additionally, there is also weaker evidence in some data sub-samples to support “herding” behaviour, whereby higher market correlations persist, following a crisis period.

Research limitations/implications

The intention of this paper was not to analyse the cause or transmission mechanism of contagion between financial markets. Therefore future studies could extend the methodology used in this paper by including exogenous macroeconomic factors in the MSBVAR model.

Originality/value

The results of this paper serve to explain why the debate of the persistence and in fact existence of financial contagion remains alive. The authors have shown that the frequency of a time series dataset has a significant impact on the level of observed correlation and thus observation of financial contagion.

Details

Journal of Economic Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 20 February 2017

Worawuth Kongsilp and Cesario Mateus

The purpose of this paper is to investigate the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and…

Abstract

Purpose

The purpose of this paper is to investigate the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and recent financial crisis.

Design/methodology/approach

Using a broad sample of stock options traded on the American Stock Exchange and the Chicago Board Options Exchange from January 2001 to December 2010, the effect of different idiosyncratic volatility forecasting measures are examined on future stock returns in four different periods (Bear and Bull markets).

Findings

First, the authors find clear and robust empirical evidence that the implied idiosyncratic volatility is the best stock return predictor for every sub-period both in Bear and Bull markets. Second, the cross-section firm-specific characteristics are important when it comes to stock returns forecasts, as the latter have mixed positive and negative effects on Bear and Bull markets. Third, the authors provide evidence that short selling constraints impact negatively on stock returns for only a Bull market and that liquidity is meaningless for both Bear and Bull markets after the recent financial crisis.

Practical implications

These results would be helpful to disclose more information on the best idiosyncratic volatility measure to be implemented in global financial crises.

Originality/value

This study empirically analyses the effect of different idiosyncratic volatility measures for a period that involves both the dotcom bubble and the recent financial crisis in four different periods (Bear and Bull markets) and contributes the existing literature on volatility measures, volatility risk and stock return predictability in global financial crises.

Details

China Finance Review International, vol. 7 no. 1
Type: Research Article
ISSN: 2044-1398

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Article
Publication date: 28 February 2020

John Roufagalas and Alexei G. Orlov

The purpose of the paper is twofold: to construct and analyze a novel endogenous growth model, in which unbounded growth is possible without the need to assume increasing…

Abstract

Purpose

The purpose of the paper is twofold: to construct and analyze a novel endogenous growth model, in which unbounded growth is possible without the need to assume increasing returns to scale, and to use the model to estimate the long-run (or dynamic) costs of recessions.

Design/methodology/approach

In the proposed model, endogenous technology and human capital accumulation serve as the “twin engines of growth.” Simulations are used to derive growth rates consistent with long-term experience of developed countries, to understand better the differences between balanced growth and unbounded growth and to provide an estimate of the dynamic costs of capacity utilization shocks that produce business cycle-like behavior.

Findings

Conservative calculations show that the costs of the capacity shocks can be large – about 1.5 percent of the present value of output over a 100-period horizon. The theoretical model also suggests that differences in the technology production and human capital accumulation functions, possibly due to differing institutions, may help explain diverse growth experiences.

Originality/value

The paper, for first time, combines two strands of the economic growth theory – endogenous technology and endogenous human capital production – into a single model. It uses the implications of the model to argue, through simulations, that the benefits of counter-cyclical policies are potentially large in the long run.

Details

Journal of Economic Studies, vol. 47 no. 2
Type: Research Article
ISSN: 0144-3585

Keywords

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