Academic literature on the topic 'Statistics and trade'

The main objective of this paper is to equip the trade policy analyst with an appropriate method of seasonally adjusting trade data with weekly observations. To that end, a structural time series model containing a trend, seasonal and irregular component is specified. The seasonal component is represented by a time-varying periodic spline. Casting the model in state-space form enables time-varying parameters as well as use of the powerful Kalman filter for trend estimation. The resulting trend can then be interpreted as a seasonally adjusted series. A simulation exercise shows that the correct trend is identified with an average absolute error of 0.4 percent. An application to Swedish imports during 2017-2021 shows that the model produces a reasonable trend estimate when applied in 'real-time' and that its application is preferred to smoothing the series using a simple moving average.

Since Benoit Mandelbrot's discovery of the fractal nature of financial price series, the quantitative analysis of financial markets has been an area of increasing interest for scientists, traders, and regulators. Further, major technological advances over this time have facilitated not only financial innovations, but also the computational ability to analyze and model markets. The stylized facts are qualitative statistical signatures of financial market data that hold true across different stocks and over many different timescales. In pursuit of a mechanistic understanding of markets, we look to accurately quantify such statistics. With this quantification, we can test computational market models against the stylized facts and run controlled experiments. This requires both discovery of new stylized facts, and a persistent testing of old stylized facts on new data. Using NASDAQ provided data covering the years 2008-2009, we analyze the trades of 120 stocks. An analysis of the stylized facts guides our exploration of the data, where our results corroborate other findings in the existing body of literature. In addition, we search for statistical indicators of market instability in our data sets. We find promising areas for further study, and obtain three key results. Throughout our sample data, high frequency trading plays a larger role in rapid price changes of all sizes than would be randomly expected, but plays a smaller role than usual during rapid price changes of large magnitude. Our analysis also yields further evidence of the long term persistence in the autocorrelations of signed order flow, as well as evidence of long range dependence in price returns.

This thesis provides a systematic study of currency crash risk and funding liquidity risk in carry trade strategy in the foreign exchange (FX) market. Carry trade, which involves longing currencies with high interest rate and shorting currencies with low interest rate, is a popular currency trading strategy in the FX market for obtaining annualized excess return as high as 12%. This thesis studies exchange rates of 9 currencies over 13 years from a microstructure perspective. We identify a global skewness factor and use it to measure the currency crash risk. Applying a portfolio approach in cross-sectional asset pricing, we find that global skewness factor explains more than 80% of carry trade excess returns. On the other hand, funding liquidity is effective in predicting the future currency crash risk. Funding liquidity explains more than 70% of carry trade excess returns. We also use the coefficient of price impact from customer order flows to measure the liquidity, which reveals heterogeneous information content possessed by different types of customers. We find that the order flow implied liquidity risk factor can explain a fraction of carry trade excess returns but with small risk premium on quarterly basis. We provide empirical evidence to show that the excess return and crash risk in carry trade is endogenous; i.e., the crash risk premium is inherent in carry trade process. As the natural condition widely affects all investors, we argue that funding constraints are effective in explaining the excess returns of carry trade. When capital moves smoothly in a liquid condition and investor have sufficient funding supply, carry trade is prosperous in the FX market. When investors hit their funding constraints, market-wide liquidity drop, which force the carry trade positions diminishing. The exchange rates respond as that the low interest rate currencies appreciate and high interest rate currencies depreciate, which exacerbates currency crash risk and induces large loss to carry traders. Our cross-sectional analysis provides empirical evidence to show that funding constraints helps to explain the forward premium puzzle and push the exchange rate shift back to the direction the UIP expects.

This thesis explores the role of trade and trade liberalization policies on Tanzanian economy with special focus on the performance of agricultural sector. In terms of methodology, we first use parametric and non-parametric tests to evaluate the impact of liberalization policies on the growth rate of exports. Secondly, we use ordinary least square and instrumental variable to test the “inverse relationship hypothesis” and then we estimate the effect of liberalization on land productivity. We also extend this analysis to Uganda in order to ascertain whether similar findings could be replicated in other developing countries. Thirdly, we employ the co-integration technique to evaluate the effects of openness on economic growth. The parametric and non-parametric tests shows that: despite the marked variation in the composition of traditional exports especially during the late 1990s; largely from coffee and cotton to cashewnuts and tobacco, the contribution of trade liberalization in fostering export growth is rather weak. Second, although the volume of food crops during the post reform period is much higher than before the reforms, there are no symptoms of increased growth overtime. The empirical evidence from econometric analysis shows the existence of diminishing returns to land in the agricultural sector. On the other hand, the impact of trade liberalization on land productivity is mixed; while in some traditional exports its impact is negative and significant, in others the impact is positive but not significant. Contrary to the conventional wisdom as documented in the traditional theories of comparative advantage, the problem with Tanzanian agriculture is not related to the land size but low productivity. Interestingly, these results are also replicated in the Ugandan case. The cointegration analysis shows that the share of trade to GDP is negatively correlated with economic growth. In general, the contribution of this thesis has wider implications in the development policy, at least for the case of Tanzania and other developing countries. First, trade liberalization policies are counterproductive unless diminishing returns to land is squarely addressed. Secondly, the existence of diminishing returns to land is incompatible with the simple prediction of the theory of comparative advantage. The presumption behind trade liberalization is that specialization according to the “comparative advantage” doctrine would inevitably enhance increased productivity (i.e., efficiency). Our results do not conform to this presumption. Third, diminishing returns means that as production increases with international specialization, every additional unit of commodity produced would be more expensive to produce. Fourth, the persistence of diminishing returns to land is incompatible with poverty reduction.