scholarly journals The Irish Famine and Unusual Market Behaviour in Cork

2017 ◽  
Vol 44 (1) ◽  
pp. 3-18 ◽  
Author(s):  
Charles Read

Scholars have long debated whether there was enough food in Ireland to feed the population during the Great Irish Famine; there has been less detailed examination of high-frequency data to understand how markets distributed food after the harvests failed. This article explores a hitherto unused weekly price and quantity data set from the Cork city markets to analyse how markets may have hindered the distribution of available food from 1846 to 1849. Although, historically, economists have long suspected that raw data on the market for potatoes during the Irish Famine behaved like that for a classical ‘Giffen’ good, there is little evidence for this among foodstuffs available throughout the crisis in Cork. But bacon pigs – a food that never reached a stable equilibrium but completely disappeared from the market in 1847 – exhibited some characteristics which do not appear to accord with the classical law of demand. Further analysis of this data suggests that middle-class purchasing power outbid the poorest people in Ireland at a time when there was a surplus of superior foods and a deficiency of inferior foods. These circumstances indicate that unusual market behaviour may have made the crop failure’s redistributive consequences – as well as its mortality toll – much worse.

2004 ◽  
Vol 07 (05) ◽  
pp. 615-643 ◽  
Author(s):  
ERHAN BAYRAKTAR ◽  
H. VINCENT POOR ◽  
K. RONNIE SIRCAR

S&P 500 index data sampled at one-minute intervals over the course of 11.5 years (January 1989–May 2000) is analyzed, and in particular the Hurst parameter over segments of stationarity (the time period over which the Hurst parameter is almost constant) is estimated. An asymptotically unbiased and efficient estimator using the log-scale spectrum is employed. The estimator is asymptotically Gaussian and the variance of the estimate that is obtained from a data segment of N points is of order [Formula: see text]. Wavelet analysis is tailor-made for the high frequency data set, since it has low computational complexity due to the pyramidal algorithm for computing the detail coefficients. This estimator is robust to additive non-stationarities, and here it is shown to exhibit some degree of robustness to multiplicative non-stationarities, such as seasonalities and volatility persistence, as well. This analysis suggests that the market became more efficient in the period 1997–2000.


2014 ◽  
Vol 22 (4) ◽  
pp. 675-697
Author(s):  
Seok-Kyu Kang ◽  
Youngtae Byun ◽  
Jonghae Park

In this study we compared the effectiveness of different ETFs. For this purpose, we analyzed the volatility spillover effect (process) among KOSPI200, KOSPI200 futures and KOSPI200 ETFs such as KODEX200, KOSEF200, KINDEX200, TIGER200 using multi-variate GARCH model. The sample was generated from high frequency data set over the period from 05/24/2009 to 12/29/2011 (669 days). The volatility spillover effect was examined at 1, 5, 10, 30 minute' intervals for each market and the main results are as follows; First, KODEX200 has the highest correlations with KOSPI200 and KOSPI200 futures in four ETFs. Second, all ETFs have a cointegrated relationship with its underlying asset KOSPI200 as KOSPI200 and KOSPI200 futures do. Third, in the daily data the volatility spillover among ETFs, KOPSI200 and KOSPI200 futures was investigated in part but it was not consistent. The fourth, according to the result derived from high-frequency data analysis the volatility spillover effect from KODEX200 to KOSPI200 (KOSPI200 futures) is bigger than that from KOSPI200 (KOSPI200 futures) to KODEX200 while other ETFs are not. The overall results indicate that KODEX200 which is the biggest ETF in volume performs very important roles in finding the price of underlying asset and further researches can be expected.


2019 ◽  
Vol 56 (3) ◽  
pp. 379-400 ◽  
Author(s):  
Yulia Nevskaya ◽  
Paulo Albuquerque

Several industries have recently been criticized by parents, think tanks, and governments for creating product environments that lead to excessive screen usage. If firms do not properly manage product usage, demand may drop, and public policy makers may intervene. The authors of this study test alternative ways to manage the use of such products: redesigning the timing of rewards, introducing notifications to users, and imposing time limits. A continuous-time demand model is proposed and empirically estimated with high-frequency data. The methodology is flexible enough to simultaneously explain multiple usage decisions that happen in quick succession, such as when to start and stop usage and how to respond to rewards or messages from the firm. The approach is implemented on a data set from the online gaming industry that includes usage decisions of a large sample of individuals. The authors find that improving reward schedules and imposing time limits leads to shorter usage sessions and longer product subscriptions—a win-win outcome. Notifications are found not to be useful to manage product usage.


2021 ◽  
Vol 14 (7) ◽  
pp. 330
Author(s):  
Camillo Lento ◽  
Nikola Gradojevic

This paper explores price spillover effects around the COVID-19 pandemic market meltdown between the S&P 500 index, five other financial markets, and the VIX. Frequency domain causalities are estimated for the January–May 2020 time period on a high-frequency data set at five-minute intervals. The results reveal that price movements in the S&P 500 generally caused price movements in other financial markets before the market meltdown; however, a large number of bi-directional causalities emerged during the market meltdown. During the market recovery, S&P 500 price movements were more likely to be caused by other financial markets’ price movements. The VIX, exchange rate, and gold returns had the most prominent influence on the S&P 500 returns in the market recovery.


2017 ◽  
Author(s):  
Rim mname Lamouchi ◽  
Russell mname Davidson ◽  
Ibrahim mname Fatnassi ◽  
Abderazak Ben mname Maatoug

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