The impact of embedded location options on price discovery of agricultural futures contracts – the evidence from the Chana contract

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanjay Mansabdar ◽  
Hussain C. Yaganti ◽  
Sankarshan Basu
Keyword(s):  
Price Discovery ◽  
Time Series Data ◽  
Futures Contracts ◽  
Series Data ◽  
Futures Prices ◽  
Content Type ◽  
Futures Contract ◽  
Agricultural Futures ◽  
Embedded Options ◽  
The Impact

Purpose Embedded options can create asymmetries in information impounded by cash and futures markets, causing errors in price discovery estimation. This paper aims to investigate the impact of embedded location options on measures of price discovery. Design/methodology/approach Various price discovery metrics are computed using observed futures prices that contain embedded location options and cash prices for Chana. Prices of a futures contract that contains no options using observed futures prices and estimates of location option value are synthesized. The price discovery measures are recomputed using synthetic option-adjusted futures contract prices and cash prices, and changes in these measures are attributed to the impact of the embedded location option. Findings If the presence of the location option is ignored, futures appear to dominate price discovery. Once the location option is adjusted for, cash markets are found to dominate price discovery. Research limitations/implications The lack of complete time-series data from the exchange for multiple commodities allows only limited empirical evidence for generalizing conclusions. Practical implications This paper highlights that regulators, exchanges and policymakers in India need to revisit delivery specifications of agricultural commodity futures contracts to enhance their utility from a price discovery perspective. Originality/value This work shows that ignoring the presence of embedded options can cause significant errors in price discovery assessment of agricultural futures contracts, particularly in heterogenous cash markets.

The impact of Benin’s first public procurement code and its amendment on healthcare equipment acquisition prices

2018 ◽  
Vol 18 (4) ◽  
pp. 306-322 ◽  
Author(s):  
Pamphile Thierry Houngbo ◽  
Maikel Kishna ◽  
Marjolein Zweekhorst ◽  
Daton Medenou ◽  
Joske G.F. Bunder-Aelen
Keyword(s):  
Health Care ◽  
Time Series Data ◽  
Good Governance ◽  
Public Procurement ◽  
Linear Regression Analysis ◽  
Interrupted Time Series ◽  
Series Data ◽  
Content Type ◽  
The Impact ◽  
Health Care Equipment

PurposeTo satisfy donors and reduce public procurement acquisition prices, Benin has implemented and amended its first public procurement code guided by top-down principles of good governance.Design/methodology/approachThis study aims to measure the impact of the code and its amendment on public procurement acquisition prices of health-care equipment from 1995 to 2010.FindingsA segmented linear regression analysis was performed using interrupted time-series data. The analysis shows that the code and its amendment did not reduce acquisition prices, indicating the limited impact of the code. The authors recommend the implementation of bottom-up processes in establishing the public procurement system, and the development of a reference pricelist of the most widely used health-care equipment, as possible solutions for improving the effectiveness of the code.

scholarly journals Heterogeneity of Cash Markets at Physical Delivery Points and the Hedging Effectiveness of Agricultural Commodity Futures in India – Lessons for Contract Optimization.

2020 ◽  
Vol 9 (SI) ◽  
pp. 79-89
Author(s):  
Sanjay Mansabdar ◽  
Hussain C Yaganti
Keyword(s):  
Contract Design ◽  
Commodity Futures ◽  
Futures Contracts ◽  
Agricultural Commodity ◽  
Futures Contract ◽  
Hedging Effectiveness ◽  
Several Variables ◽  
Agricultural Futures ◽  
Delivery Options ◽  
The Impact

Agricultural commodity futures in India are settled by physical delivery and the seller can choose the location of delivery from a list described in the contract specifications. Cash markets at these locations represent the deliverable basket for the futures contract and are the underlying assets for the delivery options granted to the seller by virtue of contract design.  These cash markets are generally heterogenous. This paper studies the impact of heterogeneity of the underlying cash markets in different locations on the hedging effectiveness of the associated futures contract. The hedging effectiveness of cottonseed oilcake and soybean futures is regressed against several variables that represent heterogeneity of the underlying cash markets using ridge regression. We find that in general, the greater the heterogeneity, the poorer the hedging effectiveness of the contract. This paper is unique in that it provides a framework for guidance for contract designers at exchanges and regulators who will find this research useful in optimizing delivery specifications for agricultural futures contracts.  This is especially important given the declining volumes in Indian agricultural commodity futures.

scholarly journals The durability of economic indicators in container shipping demand: a case study of East Asia–US container transport

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tomoya Kawasaki ◽  
Takuma Matsuda ◽  
Yui-yip Lau ◽  
Xiaowen Fu
Keyword(s):  
Time Series ◽  
East Asia ◽  
Time Series Data ◽  
Economic Indicators ◽  
Series Data ◽  
Container Shipping ◽  
Content Type ◽  
The Usa ◽  
Container Movement ◽  
The Impact

Purpose In the maritime industry, it is vital to have a reliable forecast of container shipping demand. Although indicators of economic conditions have been used in modeling container shipping demand on major routes such as those from East Asia to the USA, the duration of such indicators’ effects on container movement demand have not been systematically examined. To bridge this gap in research, this study aims to identify the important US economic indicators that significantly affect the volume of container movements and empirically reveal the duration of such impacts. Design/methodology/approach The durability of economic indicators on container movements is identified by a vector autoregression (VAR) model using monthly-based time-series data. In the VAR model, this paper can analyze the effect of economic indicators at t-k on container movement at time t. In the model, this paper considers nine US economic indicators as explanatory variables that are likely to affect container movements. Time-series data are used for 228 months from January 2001 to December 2019. Findings In the mainland China route, “building permission” receives high impact and has a duration of 14 months, reflecting the fact that China exports a high volume of housing-related goods to the USA. Regarding the South Korea and Japan routes, where high volumes of machinery goods are exported to the USA, the “index of industrial production” receives a high impact with 11 and 13 months’ duration, respectively. On the Taiwan route, as several types of goods are transported with significant shares, “building permits” and “index of industrial production” have important effects. Originality/value Freight demand forecasting for bulk cargo is a popular research field because of the public availability of several time-series data. However, no study to date has measured the impact and durability of economic indicators on container movement. To bridge the gap in the literature in terms of the impact of economic indicators and their durability, this paper developed a time-series model of the container movement from East Asia to the USA.

Determinants of Islamic banking growth: an empirical analysis

2018 ◽  
Vol 11 (1) ◽  
pp. 18-39 ◽  
Author(s):  
Tamsir Cham
Keyword(s):  
World Bank ◽  
Time Series Data ◽  
Empirical Work ◽  
Series Data ◽  
Islamic Banking ◽  
Content Type ◽  
Positive Effects ◽  
World Bank Enterprise Survey ◽  
Enterprise Survey ◽  
The Impact

Purpose This paper aims to examine the determinants of growth rate in Islamic banking using annual time series data. Design/methodology/approach The author applied several econometrics methods including generalized linear model and survey-based indicators. The author uses the World Bank Enterprise Survey data to supplement the answers. Findings The results support the view that high oil prices, stable domestic prices, higher educated populace and greater presence of capital resources have positive effects on growth in Islamic banking. The findings, however, revealed that instability adversely affects Islamic banking growth. The author found no clear conclusion on the impact of economic growth, greater presence of Muslim population and presence of sharia in the legal system of the country on growth in Islamic banking. The major constraints impeding Islamic banking growth include regulations, tax rates and skilled labor force. Originality/value There is no empirical work that has been done on the determinants of Islamic banking growth by taking into account the following factors: oil price dynamics, sharia compliant, macroeconomic variables, instability and World Bank Enterprise survey. This paper attempts to search for the push and pull factors of Islamic banking growth to fill the gap in determining the Islamic banking growth.

Forecasting construction output: a comparison of artificial neural network and Box-Jenkins model

2016 ◽  
Vol 23 (3) ◽  
pp. 302-322 ◽  
Author(s):  
Ka Chi Lam ◽  
Olalekan Shamsideen Oshodi
Keyword(s):  
Neural Network ◽  
Construction Industry ◽  
Time Series Data ◽  
Predictive Accuracy ◽  
Moving Average ◽  
Arima Model ◽  
Series Data ◽  
Effective Response ◽  
Content Type ◽  
The Impact

Purpose – Fluctuations in construction output has an adverse effect on the construction industry and the economy due to its strong linkage. Developing reliable and accurate predictive models is vital to implementing effective response strategies to mitigate the impact of such fluctuations. The purpose of this paper is to compare the accuracy of two univariate forecast models, i.e. Box-Jenkins (autoregressive integrated moving average (ARIMA)) and Neural Network Autoregressive (NNAR). Design/methodology/approach – Four quarterly time-series data on the construction output of Hong Kong were collected (1983Q1-2014Q4). The collected data were divided into two parts. The first part was fitted to the model, while the other was used to evaluate the predictive accuracy of the developed models. Findings – The NNAR model can provide reliable and accurate forecast of total, private and “others” construction output for the medium term. In addition, the NNAR model outperforms the ARIMA model, in terms of accuracy. Research limitations/implications – The applicability of the NNAR model to the construction industry of other countries could be further explored. The main limitation of artificial intelligence models is the lack of explanatory capability. Practical implications – The NNAR model could be used as a tool for accurately predicting future patterns in construction output. This is vital for the sustained growth of the construction industry and the economy. Originality/value – This is the first study to apply the NNAR model to construction output forecasting research.

scholarly journals Determinants of private domestic investment in Palestine: time series analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ibrahim M. Awad ◽  
Ghada K. Al-Jerashi ◽  
Zaid Ahmad Alabaddi
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Private Investment ◽  
Critical Issue ◽  
Background Information ◽  
Series Data ◽  
Domestic Investment ◽  
Causality Test ◽  
Content Type ◽  
The Impact

PurposeThis empirical paper aims to examine the impact of interest rate (IR) and political instability (POLINS) on Palestine's domestic private investment.Design/methodology/approachA set of econometric techniques of time series data are adopted to meet the study objectives. They include regression analysis, unit root tests, cointegration test, ARDL & Bound tests, VAR test and Granger causality test.FindingsThe study's primary results complement the neoclassical approach, which states that the IR is negatively associated with domestic private investment. The empirical results reveal that there is no long-run relationship. Also, there is no causality between domestic investment and lending rates. Accordingly, these findings alert policymakers to draw a series of steps to minimize the IR at a minimum to stimulate investment for improved economic growth and development.Practical implicationsThere is still no national currency in Palestine. The Palestinian Monetary Authority (PMA) is advised to set an appropriate ratio of the IR for the currencies-in-circulation in Palestine for boosting investment and economic development.Originality/valueThis paper provides new background information to both policymakers and researchers on the main determinants of investment in Palestine using econometric analysis. Accordingly, this critical issue is required to be examined in Palestine for stimulating investment.

Airbnb and hotels: friends, enemies or frenemies?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oswald Mhlanga
Keyword(s):  
South Africa ◽  
Time Series Data ◽  
Sharing Economy ◽  
Disruptive Innovation ◽  
Series Data ◽  
Data Set ◽  
Content Type ◽  
Complementary Role ◽  
Triple Difference ◽  
The Impact

Purpose The purpose of this paper is to explore the intricate relationship between the flagship of the sharing economy, Airbnb and hotel revenue per available room (RevPAR) in South Africa. Design/methodology/approach To identify the impact of Airbnb on hotel RevPAR, the paper used a triple difference-in-differences framework that compares changes in cities in South Africa where Airbnb started operating relative to areas without Airbnb. A total of 569 hotels were analysed. Findings While the study finds no evidence of adverse impacts of Airbnb on hotel RevPAR, the findings show that the entry of Airbnb led to a decrease in RevPAR of budget hotels. However, its impact is more pronounced during periods of peak demand, consequently, disrupting the pricing power of hotels. Research limitations/implications The research was based on the impact of Airbnb on hotel RevPAR in hotels situated in specific cities in South Africa. Caution is therefore required when generalising the findings of this study to other hotels in other geographic areas. Moreover, if a longer time series data set of hotels in the post-Airbnb time period could become available, it would be interesting to further investigate the time-varying dynamic effects of Airbnb on hotel RevPAR. However, the findings underscore the notion that innovations are not intrinsically disruptive but only relative to another product. In so doing, the study adds to the limited body of work in the field on disruptive innovation and to the academic discourse on innovation in tourism more broadly. Practical implications First, the findings suggest the impact on hotels tends towards Airbnb generally playing a largely complementary role rather than a diversionary one. However, to increase RevPAR, hotels should systematically change their pricing models to account for flexible capacity by rethinking the wisdom of seasonal pricing and reduce prices during peak seasons to avoid inviting more competition from Airbnb. Originality/value To the best of the author’s knowledge, this paper is the first to explore the relationship between Airbnb and hotel markets using a triple difference methodology.

Non-Indian aid and growth nexus in Bhutan

2015 ◽  
Vol 14 (2) ◽  
pp. 117-129
Author(s):  
Jigme Nidup
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Foreign Aid ◽  
Time Series Data ◽  
Labour Force ◽  
Unit Root Test ◽  
Series Data ◽  
Content Type ◽  
Distributed Lag ◽  
The Impact

Purpose – The purpose of this paper is to investigate the impact of Non-Indian foreign aid on economic growth. In addition, this paper also investigates the importance of governance, policy and democratic institution in fostering economic growth. Planned development activities in Bhutan are mostly funded through external assistance, particularly from India. Bhutan also receives assistance from other bilateral and multilateral countries besides India. Design/methodology/approach – This study adopts the autoregressive distributed lag approach to cointegration using time-series data from 1982 to 2012. To ensure stationarity of data, the unit root test is conducted. Necessary diagnostic tests are also performed to confirm that the model does not violate regression assumptions. Findings – Findings indicate that Non-Indian foreign aid, governance and democracy are detrimental to economic growth. Policy and investment is found insignificant determinant. However, labour force and technology are found fostering economic growth. Research limitations/implications – Less number of observations restrained detailed analysis like the use of interactive terms between aid and governance, aid and policy to see its actual impact. Data on Indian aid could not be sourced from any documents. Those available were found only for few years restricting time series analysis. Originality/value – This study explored the impact of various determinants on economic growth in Bhutan. These findings provide useful insights for policymakers in Bhutan to make necessary decisions. The analysis also suggests future ground for research to those scholars and researchers.

scholarly journals Futures trading and the underlying stock volatility: A case of the FTSE/JSE TOP 40

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Mr. Rabson Magweva ◽  
Mrs. Magret Munyimi ◽  
Mr. Justine Mbudaya
Keyword(s):  
Time Series Data ◽  
Financial Time Series ◽  
Garch Model ◽  
Stock Index ◽  
Futures Contracts ◽  
Series Data ◽  
Policy And Practice ◽  
Stock Volatility ◽  
Top 40 ◽  
The Impact

Purpose: This study analyzed the impact of listing and trading futures contracts on the underlying stock index volatility behavior. The FTSE/JSE TOP 40 index was the index of interest.Methodology: To capture the non-constant variance of the residuals, a modified Generalised Autoregressive Conditionally Heteroscedasticity (GARCH) model was adopted. This model was used was adopted given that financial time series data exhibited ARCH effects. The GARCH model was estimated after dividing the sample period into pre-and post-futures eras.Findings: The research findings point towards stabilization effects on underlying stock volatility and refute the suggestion that futures markets improve the dissemination of information to the corresponding spot markets. On the same note, the introduction of futures increased the volatility persistence of index returns.Unique contribution to theory, policy, and practice: This paper applied a modified-GARCH by incorporating a dummy variable to the traditional GARCH model. The study used an emerging economy as a case study which makes the results and conclusions more specific and applicable. On the same note, the study covered the pre-and post-global crisis of 2007/8 in a Sub-Saharan nation. In practice, stock markets are encouraged to introduce futures contracts on highly volatile spot market assets.

Does poverty lead to crime? Evidence from the United States of America

2018 ◽  
Vol 45 (10) ◽  
pp. 1424-1438 ◽  
Author(s):  
Mohammed Imran ◽  
Mosharrof Hosen ◽  
Mohammad Ashraful Ferdous Chowdhury
Keyword(s):  
Time Series Data ◽  
Property Crime ◽  
The United States ◽  
Economic Hardship ◽  
Series Data ◽  
Advanced Economy ◽  
Content Type ◽  
Long Run ◽  
The Usa ◽  
The Impact

Purpose Economic hardship and crime is always a debatable issue in the political economy literature. Some authors define poverty leads to crime some are completely opposite. The purpose of this paper is to find out the impact of poverty on crime in the USA. Design/methodology/approach Using time series data of USA over the period from 1965 to 2016, this study applies autoregressive distributed lag approach to identify the effect of poverty on crime. Findings The outcomes confirm a positive co-integrating relationship between poverty and property crime. It can be argued that poverty ultimately leads property crime in long run in the USA. However, unemployment and GDP exhibit neither long-run nor short-run relationship with property crime and they are not cointegrated for the calculated period. Research limitations/implications The subject of this paper helps to explain and analyze the nexus between poverty and crime in the USA. Practical implications Government and policymakers should focus more on poverty rather than unemployment alone to control property crime. Originality/value This study attempts to identify the consequences of economic hardship and poverty on the crime in the advanced economy like USA.

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