Across the Oceans : Development of Overseas Business Information Transmission, 1815-1875

Earlier studies have shown that the speed of information transmission developed radically during the 19th century. The fast development was mainly due to the change from sailing ships and horse-driven coaches to steamers and railways, as well as the telegraph. Speed of information transmission has normally been measured by calculating the duration between writing and receiving a letter, or between an important event and the time when the news was published elsewhere. As overseas mail was generally carried by ships, the history of communications and maritime history are closely related. This study also brings a postal historical aspect to the academic discussion. Additionally, there is another new aspect included. In business enterprises, information flows generally consisted of multiple transactions. Although fast one-way information was often crucial, e.g. news of a changing market situation, at least equally important was that there was a possibility to react rapidly. To examine the development of business information transmission, the duration of mail transport has been measured by a systematic and commensurable method, using consecutive information circles per year as the principal tool for measurement. The study covers a period of six decades, several of the world's most important trade routes and different mail-carrying systems operated by merchant ships, sailing packets and several nations' steamship services. The main sources have been the sailing data of mail-carrying ships and correspondence of several merchant houses in England. As the world's main trade routes had their specific historical backgrounds with different businesses, interests and needs, the systems for information transmission did not develop similarly or simultaneously. It was a process lasting several decades, initiated by the idea of organizing sailings in a regular line system. The evolution proceeded generally as follows: originally there was a more or less irregular system, then a regular system and finally a more frequent regular system of mail services. The trend was from sail to steam, but both these means of communication improved following the same scheme. Faster sailings alone did not radically improve the number of consecutive information circles per year, if the communication was not frequent enough. Neither did improved frequency advance the information circulation if the trip was very long or if the sailings were overlapping instead of complementing each other. The speed of information transmission could be improved by speeding up the voyage itself (technological improvements, minimizing the waiting time at ports of call, etc.) but especially by organizing sailings so that the recipients had the possibility to reply to arriving mails without unnecessary delay. It took two to three decades before the mail-carrying shipping companies were able to organize their sailings in an optimal way. Strategic shortcuts over isthmuses (e.g. Panama, Suez) together with the cooperation between steamships and railways enabled the most effective improvements in global communications before the introduction of the telegraph.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.