arXiv subjects

Tatsuma Wada

Publications and source records attributed to Tatsuma Wada.

4 recordsLinked to original sources

arXiv2017

An Alternative Estimation Method of a Time-Varying Parameter Model

A non-Bayesian, regression-based or generalized least squares (GLS)-based approach is formally proposed to estimate a class of time-varying AR parameter models. This approach has partly been used by Ito et al. (2014, 2016a,b), and is proven to be efficient because, unlike conventional methods, it does not require Kalman filtering and smoothing procedures, but yields a smoothed estimate that is identical to the Kalman-smoothed estimate. Unlike the maximum likelihood estimator, the possibility of the pile-up problem is negligible. In addition, this approach enables us to deal with stochastic volatility models, models with a time-dependent variance-covariance matrix, and models with non-Gaussian errors that allow us to deal with abrupt changes or structural breaks in time-varying parameters.

stat.ME↗

arXiv2016

Time-Varying Comovement of Foreign Exchange Markets

A time-varying cointegration model for foreign exchange rates is presented. Unlike previous studies, we allow the loading matrix in the vector error correction (VEC) model to be varying over time. Because the loading matrix in the VEC model is associated with the speed at which deviations from the long-run relationship disappear, we propose a new degree of market comovement\ based on the time-varying loading matrix to measure the strength or robustness of the long-run relationship over time. Since exchange rates are determined by macrovariables, cointegration among exchange rates implies those macroeconomic variables share common stochastic trends. Therefore, the proposed degree measures the degree of market comovement. Our main finding is that the market comovement has become stronger over the past quarter century, but the rate at which market comovement strengthens is decreasing with two major turning points: one in 1995 and the other one in 2008.

q-fin.ST↗

arXiv2015

The Evolution of Stock Market Efficiency in the US: A Non-Bayesian Time-Varying Model Approach

A non-Bayesian time-varying model is developed by introducing the concept of the degree of market efficiency that varies over time. This model may be seen as a reflection of the idea that continuous technological progress alters the trading environment over time. With new methodologies and a new measure of the degree of market efficiency, we examine whether the US stock market evolves over time. In particular, a time-varying autoregressive (TV-AR) model is employed. Our main findings are: (i) the US stock market has evolved over time and the degree of market efficiency has cyclical fluctuations with a considerably long periodicity, from 30 to 40 years; and (ii) the US stock market has been efficient with the exception of four times in our sample period: during the long-recession of 1873-1879; the recession of 1902-1904; the New Deal era; and the recession of 1957-1958 and soon after it. It is then shown that our results are partly consistent with the view of behavioral finance.

q-fin.ST↗

arXiv2014

International Stock Market Efficiency: A Non-Bayesian Time-Varying Model Approach

This paper develops a non-Bayesian methodology to analyze the time-varying structure of international linkages and market efficiency in G7 countries. We consider a non-Bayesian time-varying vector autoregressive (TV-VAR) model, and apply it to estimate the joint degree of market efficiency in the sense of Fama (1970, 1991). Our empirical results provide a new perspective that the international linkages and market efficiency change over time and that their behaviors correspond well to historical events of the international financial system.

q-fin.ST↗