Dissecting Tether’s Nonlinear Dynamics during Covid-19

The present study is on the five cryptocurrency daily mean return time series linearity dynamics during the Covid-19 period. These cryptocurrencies were chosen based on their influence on the market, primarily driven by its market capitalisation. Tether is included as the most important stable coin on the market, nominally pegged to the U.S. dollar (USD). The reason to investigate it is that there are some inconsistencies in its behaviour as opposed to the other four cryptocurrencies. This study found that the behaviour of Tether cryptocurrency daily average return time series pattern is highly nonlinear and chaotic in nature, whereas the other four cryptocurrencies (namely Bitcoin, Ethereum, XRP and Bitcoin Cash) daily average return time series were found to be linear in nature. To further study Tether’s nonlinear time series rich dynamics, this study deployed one category of the regime switching models popularly known as the threshold regressions. The study estimates fairly suggest that both the threshold autoregression (TAR) and smooth transition autoregressive (STAR) models with lag 1 are adequate to capture the rich nonlinear and chaotic dynamics of Tether’s daily average return time series.

Testing for regime-switching behaviour in Finnish agricultural land prices

PurposeThis study analyses agricultural land price dynamics in order to better understand price development and to improve forecast accuracy. Understanding the evolution of agricultural land prices is important when considering sound investment decisions.Design/methodology/approachThis study applies threshold autoregression to model agricultural land prices. The data includes quarterly observations on Finnish agricultural land prices.FindingsThe study shows that Finnish agricultural land prices exhibit regime-switching behaviour when using past changes in prices as a threshold variable. The threshold autoregressive model not only fits the data better but also improves the accuracy of price forecasts compared to the linear autoregressive model.Originality/valueThe results show that a sharp fall in agricultural land prices temporarily changes the regular development of prices. This information significantly improves the accuracy of price predictions.

INTERAKSI PASAR BARANG DAN PASAR UANG DI INDONESIA: PENDEKATAN MODEL MUNDELL-FLEMING

Paper ini bertujuan untuk menginvestigasi interaksi pasar barang dan pasar uang dengan pendekatan model mundel-fleming di Indonesia dalam periode 1997 – 2017 melewati tiga shock krisis keuangan yaitu krisis keuangan Asia,Krisis Subprime mortgage dan krisis utang eropa. Penelitian ini menggunakan metode kuantitatif deskriptif dengan model Threshold Autoregression (TAR) menyimpulkan bahwa di Indonesia terdapat interaksi antara pasar barang dan pasar uang.

An interview with Howell Tong

Howell Tong (simplified Chinese: 汤家豪) is a pioneer in the field of nonlinear time series analysis, linking it with deterministic chaos. He is the father of the threshold time series models, which have extensive applications in ecology, economics, epidemiology and finance. Since October 1, 2009, he has been an Emeritus Professor at the London School of Economics and was twice (2009, 2010) holder of the Saw Swee Hock Professorship of Statistics at the National University of Singapore. He was a Distinguished Visiting Professor of Statistics at the University of Hong Kong from 2005 to 2013. He got a Master in Science degree in 1969 and a Doctor of Philosophy degree in 1972 from the University of Manchester Institute of Science and Technology (UMIST), where he studied under Maurice Priestley. From 1999 to September 2009, Tong was Chair of Statistics at LSE and founded the Centre for the Analysis of Time Series. Between 1997 and 2004, Tong was also Chair Professor of Statistics, Founding Dean of the Graduate School and later Pro-Vice Chancellor, University of Hong Kong. He was elected a Fellow of the Institute of Mathematical Statistics in 1993, an Honorary Fellow of the Institute of Actuaries, England in 1999, and a Foreign Member of the Norwegian Academy of Science and Letters in 2000. In 2000, he became the first statistician to win the (class II) the State Prize in Natural Sciences in China. In 2002, the University of Hong Kong gave him their then-highest award, the Distinguished Research Achievement Award, carrying with it a research grant of HK$1,000,000 per annum for three years. The Royal Statistical Society, UK, awarded him their Guy Medal in Silver in 2007 in recognition of his “…many important contributions to time series analysis over a distinguished career and in particular for his fundamental and highly influential paper ‘Threshold autoregression, limit cycles and cyclical data,’ read to the Society in 1980, which paved the way for a major body of work in non-linear time series modelling.” In 2012, the International Chinese Statistical Association awarded him the Distinguished Achievement Award. Tong is also a Distinguished Professor-at-Large at the University of Electronic Science and Technology of China in Chengdu, China, and a Distinguished Visiting Professor at Tsinghua University in Beijing, China.

The Making of a National Currency: Spatial Transaction Costs and Money Market Integration in Spain (1825–1874)

This article analyzes the integration of the Spanish money market in the nineteenth century. We use a Band-Threshold Autoregression model of prices of bills-of-exchange in ten cities to measure market convergence and efficiency in 1825–1875. While price gaps generally decreased during the period, progress in efficiency was limited to a small group of cities. We suggest that convergence was associated to the reduction in transaction costs, which started well before the railways through improvements in roads and postal services. By contrast, the heterogeneous behavior of efficiency might be associated to economic geography changes and their effects on monetary leadership.