Time zone normalization of FX seasonality

Abstract

This paper provides empirical evidence that the particular intra-day seasonality observed in the Foreign Exchange market is indeed due to the different geographical locations of its traders. Analysing more than 2 years of real transactions from a microscopic perspective, we design a procedure that accounts for the time zones from which traders operate. The resulting normalized intra-day seasonality shows a pattern akin to those observed in regulated exchanges where traders are more active at the beginning and at the end of their session.     

Buy or make? Agricultural production diversity,markets and dietary diversity in Afghanistan

Increasing on-farm production diversity and improving markets are recognized as ways to improve the dietary diversity of smallholders. Using instrumental variable methods to account for endogeneity, we study the interplay of production diversity, markets and diets in the context of seasonality in Afghanistan. We confirm an important seasonal dimension to the interplay. Improved crop diversity over the year is positively associated with dietary diversity in the regular season, but not in the lean season. Livestock species diversity remains important for dietary diversity throughout the year, but particularly so in the lean season when the influence of cropping diversity is low. Market aspects become important for dietary diversity specifically in the lean season.     

Sources of food price volatility and child malnutrition in Niger and Malawi

In recent times, considerable attention has been paid to the nutritional impact of the sharp hikes in the international food prices which took place in 2007–8 and 2010–11. While understandable, this growing focus has perhaps obscured the impact of other variables affecting malnutrition in Sub-Saharan Africa, i.e. the long-term impact of agricultural policies on food supply and prices, large and persistent seasonal variations in food prices, and the impact of famines which still affect parts of the continent. This paper focuses on the relative impact of these factors on child malnutrition (measured by the number of child admissions to feeding centres) in Malawi and Niger, two countries which closely represent the situation of other small, landlocked, subsistence agricultural economies facing severe food security problems. Our analysis shows that in these countries the drivers of changes in domestic staple prices and child malnutrition are related not only – or not primarily – to variations of international food prices but also to the impact of agricultural policies on food production and prices, in a persistent food price seasonality, and in recurrent and poorly managed famines. These factors can exert a strong upward pressure on food prices and child malnutrition even during years of falling international prices.     

Damping seasonal factors: Shrinkage estimators for the X-12-ARIMA program

We examine the effect of damping X-12-ARIMA's estimated seasonal variation on the accuracy of its seasonal adjustments of time series. Two methods for damping seasonals are proposed. In a simulation experiment, we generated time series data for each of 90 distinct experimental conditions that, in aggregate, characterize the variety of monthly series in the M3-competition. X-12-ARIMA consistently overestimated the actual seasonal variation by an amount consistent with statistical theory. Damping seasonals reduced X-12-ARIMA's estimation error by as much as 79% and under no conditions was estimation error increased beyond a trivial amount. Improvement depended primarily on the degree to which random variation in a series dominated seasonal variation. When the multiplicative X-12-ARIMA model did not match the data-generating model, overestimation was less for trend series than for series with no trend; otherwise the presence of trend had no discernible effect. One of the proposed methods was somewhat more accurate and robust, but more complex, than the other. In an analysis of real data—the 1428 monthly series of the M3-competition-damping X-12-ARIMA seasonals prior to forecasting (1) reduced the average forecasting MAPE by 4.9–1.4% and (2) improved forecasting accuracy for 59–65% of the series, depending on the forecasting horizon. This research suggests that damping X-12-ARIMA seasonals leads to more accurate seasonal adjustments of time series, thus providing a more reliable basis for policy-making, forecasting, and the evaluation of forecasting methods by researchers.     

季节时间序列理论发展综述

随着社会的进步,统计数据由过去的年度数据变为如今的季度、月度和日度数据,有些以实时交易为基础的超高频金融数据达到了按秒为间隔的频率,这些数据被称为季节时间序列。季节时间序列研究已经成为近十年来经济计量学和统计学中的热点,Joumal of Econometrics（1993,volume 55）就此问题进行了专题讨论。本文按照历史发展顺序对季节性时间序列理论进行了系统地介绍,并对这一领域的前沿热点问题进行了评述和展望。     

Tourism seasonality in cultural destinations: Empirical evidence from Sicily

Seasonality is one of the main phenomena affecting tourism. It depends on the characteristics of both tourism demand and tourism destinations in terms of location and services supplied. This paper focuses on a particular aspect of tourism supply: the cultural attractiveness of tourism destinations, and aims to evaluate the role of cultural tourism in tourism seasonality. We analyze the seasonality of tourist presence in different destinations in Sicily, selected according to their different degree of cultural attractiveness. The methodology adopted to measure seasonality is based on a regression analysis approach, using the Census-X12-Arima procedure. Results are discussed and some policy implications are derived.     

Benchmarking by State Space Models

We have a monthly series of observations which are obtained from sample surveys and are therefore subject to survey errors. We also have a series of annual values, called benchmarks, which are either exact or are substantially more accurate than the survey observations; these can be either annual totals or accurate values of the underlying variable at a particular month. The benchmarking problem is the problem of adjusting the monthly series to be consistent with the annual values. We provide two solutions to this problem. The first of these is a two-stage method in which we first fit a state space model to the monthly data alone and then combine the results obtained at this stage with the benchmark data. In the second solution we construct a single series from the monthly and annual values together and fit a state space model to this series in a single stage. The treatment is extended to series which behave multiplicatively. The methods are illustrated by applying them to Canadian retail sales sereis.     

The impact of low cost carriers on Korean Island tourism

Given the mixed findings of extant research on the impact of low-cost carriers (hereafter LCC) on aviation markets (with some studies showing stimulation of new demand, other studies showing LCCs encroaching on the turf of full-service carriers), the emergence of LCCs in Korea raised an interesting question as to whether or not they actually contribute to overall growth in domestic air traffic. The literature has paid limited attention to this issue so far. Employing a multivariate regression analysis with monthly data from 2000 to 2009, the impact of LCCs on tourism demand to a popular destination in Korea, Jeju Island, is examined, focusing on two specific questions: Have LCCs generated new tourism demand and brought more tourism revenue into the island’s economy? Have LCCs mitigated tourism seasonality on the island? Controlling for the effects of a number of factors, results showed that LCCs have generated new demand in addition to existing tourist flows to the island. Korean LCCs accounted for 35% of total passengers in 2009, which indicates an average growth rate of 161.7% over the last 4 years, compared to a −0.3% growth rate for all full-service carriers in Korea. However, LCCs seem to have had little impact on reducing seasonal fluctuations in passenger traffic to Jeju Island. The findings of this study will be of interest to researchers, policy makers, and a variety of stakeholders in the tourism industry interested in the relationship between no-frills airlines and island economies.     

New evidence on the impact of size and taxation on the seasonality of UK equity returns

The paper investigates the extent to which capital gains taxation and the portfolio rebalancing hypothesis may account for the seasonality of UK equity returns. The empirical results show that in small firm portfolios during the period of capital gains taxation, April but not January seasonality is consistent with the tax-loss selling hypothesis. The January seasonality, which is detected even before the introduction of capital gains taxation, is also consistent with the portfolio rebalancing hypothesis until the 1980s, when such seasonality becomes increasingly insignificant.     

The volatility of temperature and pricing of weather derivatives

We propose an Ornstein–Uhlenbeck process with seasonal volatility to model the time dynamics of daily average temperatures. The model is fitted to approximately 45 years of daily observations recorded in Stockholm, one of the European cities for which there is a trade in weather futures and options on the Chicago Mercantile Exchange. Explicit pricing dynamics for futures contracts written on the number of heating/cooling degree-days (so-called HDD/CDD futures) and the cumulative average daily temperature (so-called CAT futures) are calculated, along with a discussion on how to evaluate call and put options with these futures as underlying.