Linking spatial stock dynamics and economics: Evaluation of indicators and fishery management for the travelling eastern king prawn (Melicertus plebejus)

Reduced economic circumstances have moved management goals towards higher profit, rather than maximum sustainable yields in several Australian fisheries. The eastern king prawn is one such fishery, for which we have developed new methodology for stock dynamics, calculation of model-based and data-based reference points and management strategy evaluation. The fishery is notable for the northward movement of prawns in eastern Australian waters, from the State jurisdiction of New South Wales to that of Queensland, as they grow to spawning size, so that vessels fishing in the northern deeper waters harvest more large prawns. Bio-economic fishing data were standardized for calibrating a length-structured spatial operating model. Model simulations identified that reduced boat numbers and fishing effort could improve profitability while retaining viable fishing in each jurisdiction. Simulations also identified catch-rate levels that were effective for monitoring in simple within-year effort-control rules. However, favourable performance of catch-rate indicators was achieved only when a meaningful upper limit was placed on total allowed fishing effort. The methods and findings will allow improved measures for monitoring fisheries and inform decision makers on the uncertainty and assumptions affecting economic indicators.

Stock structure of the blue threadfin (Eleutheronema tetradactylum) across northern Australia derived from life-history characteristics

Life history characteristics were used to determine the stock structure of the polynemid Eleutheronema tetradactylum across northern Australia. Growth, estimated from back-calculated length-at-age from sagittal otoliths, and length at sex change were estimated from samples collected from 12 different locations across western, northern and eastern Australia between 2007 and 2009. Comparison of back-calculated length-at-age, growth and length at sex change between locations revealed significant variation in the life-history characteristics of E. tetradactylum across northern Australia, with significant differences detected in 43 of 45 location comparisons. Differences in otolith size relative to fish length also existed amongst locations. No differences in other morphometric relationships were detected. The results of this study provide evidence for a high degree of spatial population subdivision for E. tetradactylum across northern Australia, the finding of which has implications for E. tetradactylum fisheries throughout its range, and provides a biological basis for spatial management of the species in Australia. (C) 2012 Elsevier B.V. All rights reserved.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

Multiple roles of transfer prices: One vs. two books

This paper investigates multiple roles of transfer prices for shipments of goods and services between entities of a multinational enterprise. At the center is the role of transfer pricing (TP) in tax manipulation, but other roles having to do with internal operations or strategic delegation, etc. are also considered. The interesting question is to what extent and how the different roles of TPs interfere with each other. The answer depends on whether companies use one or two books, i.e. whether they (can) apply different TPs for different purposes. We illustrate, in a stylized model, the competing aims of tax manipulation and strategic delegation. Finally, we briefly look at selected reform proposals, concluding that either TP problems are not addressed, or else new distortions will be introduced instead.

Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications

The interdependence of Greece and other European stock markets and the subsequent portfolio implications are examined in wavelet and variational mode decomposition domain. In applying the decomposition techniques, we analyze the structural properties of data and distinguish between short and long term dynamics of stock market returns. First, the GARCH-type models are fitted to obtain the standardized residuals. Next, different copula functions are evaluated, and based on the conventional information criteria and time varying parameter, Joe-Clayton copula is chosen to model the tail dependence between the stock markets. The short-run lower tail dependence time paths show a sudden increase in comovement during the global financial crises. The results of the long-run dependence suggest that European stock markets have higher interdependence with Greece stock market. Individual country’s Value at Risk (VaR) separates the countries into two distinct groups. Finally, the two-asset portfolio VaR measures provide potential markets for Greece stock market investment diversification.

Design of multiunit electronic exchanges through decomposition

In this paper, we exploit the idea of decomposition to match buyers and sellers in an electronic exchange for trading large volumes of homogeneous goods, where the buyers and sellers specify marginal-decreasing piecewise constant price curves to capture volume discounts. Such exchanges are relevant for automated trading in many e-business applications. The problem of determining winners and Vickrey prices in such exchanges is known to have a worst-case complexity equal to that of as many as (1 + m + n) NP-hard problems, where m is the number of buyers and n is the number of sellers. Our method proposes the overall exchange problem to be solved as two separate and simpler problems: 1) forward auction and 2) reverse auction, which turns out to be generalized knapsack problems. In the proposed approach, we first determine the quantity of units to be traded between the sellers and the buyers using fast heuristics developed by us. Next, we solve a forward auction and a reverse auction using fully polynomial time approximation schemes available in the literature. The proposed approach has worst-case polynomial time complexity. and our experimentation shows that the approach produces good quality solutions to the problem. Note to Practitioners- In recent times, electronic marketplaces have provided an efficient way for businesses and consumers to trade goods and services. The use of innovative mechanisms and algorithms has made it possible to improve the efficiency of electronic marketplaces by enabling optimization of revenues for the marketplace and of utilities for the buyers and sellers. In this paper, we look at single-item, multiunit electronic exchanges. These are electronic marketplaces where buyers submit bids and sellers ask for multiple units of a single item. We allow buyers and sellers to specify volume discounts using suitable functions. Such exchanges are relevant for high-volume business-to-business trading of standard products, such as silicon wafers, very large-scale integrated chips, desktops, telecommunications equipment, commoditized goods, etc. The problem of determining winners and prices in such exchanges is known to involve solving many NP-hard problems. Our paper exploits the familiar idea of decomposition, uses certain algorithms from the literature, and develops two fast heuristics to solve the problem in a near optimal way in worst-case polynomial time.

Finnish Short-Term Stock Returns

Functioning capital markets are a crucial part of a competitive economy since they provide the mechanisms to allocate resources. In order to be well functioning a capital market has to be efficient. Market efficiency is defined as a market where prices at any time fully reflect all available information. Basically, this means that abnormal returns cannot be predicted since they are dependent on future, presently unknown, information. The debate of market efficiency has been going on for several decades. Most academics today would probably agree that financial markets are reasonably efficient since virtually nobody has been able to achieve continuous abnormal positive returns. However, it is clear that a set of return anomalies exists, although they are apparently to small to enable substantial economic profit. Moreover, these anomalies can often be attributed to market design. The motivation for this work is to expand the knowledge of short-term trading patterns and to offer some explanations for these patterns. In the first essay the return pattern during the day is examined. On average stock prices move during two time periods of the day, namely, immediately after the opening and around the formal close of the market. Since stock prices, on average, move upwards these abnormal returns are generally positive and cause the distinct U-shape of intraday returns. In the second essay the results in the first essay are examined further. The return pattern around the former close is shown to partly be the result of manipulative action by market participants. In the third essay the focus is shifted towards trading patterns of the underlying stocks on days when index options and index futures on the stocks expire. Generally no expiration day effect was found. However, some indication of an expiration day effect was found when a large amount of open in- or at-the-money contracts existed. Also, the effects were likelier to be found for shares with high index-weight but fairly low trading volume. Last, in the forth essay the attention is turned to the behaviour of different tax clienteles around the dividend ex-day. Two groups of investors showed abnormal trading behaviour. Domestic non-financial investors, especially domestic companies, showed a dividend capturing behaviour, i.e. buying cum-dividend and selling ex-dividend shares. The opposite behaviour was found for foreign investors and domestic financial institutions. The effect was more notable for high yield, high volume stocks.

Essays on Market Microstructure: Price Discovery and Informed Trading

Market microstructure is “the study of the trading mechanisms used for financial securities” (Hasbrouck (2007)). It seeks to understand the sources of value and reasons for trade, in a setting with different types of traders, and different private and public information sets. The actual mechanisms of trade are a continually changing object of study. These include continuous markets, auctions, limit order books, dealer markets, or combinations of these operating as a hybrid market. Microstructure also has to allow for the possibility of multiple prices. At any given time an investor may be faced with a multitude of different prices, depending on whether he or she is buying or selling, the quantity he or she wishes to trade, and the required speed for the trade. The price may also depend on the relationship that the trader has with potential counterparties. In this research, I touch upon all of the above issues. I do this by studying three specific areas, all of which have both practical and policy implications. First, I study the role of information in trading and pricing securities in markets with a heterogeneous population of traders, some of whom are informed and some not, and who trade for different private or public reasons. Second, I study the price discovery of stocks in a setting where they are simultaneously traded in more than one market. Third, I make a contribution to the ongoing discussion about market design, i.e. the question of which trading systems and ways of organizing trading are most efficient. A common characteristic throughout my thesis is the use of high frequency datasets, i.e. tick data. These datasets include all trades and quotes in a given security, rather than just the daily closing prices, as in traditional asset pricing literature. This thesis consists of four separate essays. In the first essay I study price discovery for European companies cross-listed in the United States. I also study explanatory variables for differences in price discovery. In my second essay I contribute to earlier research on two issues of broad interest in market microstructure: market transparency and informed trading. I examine the effects of a change to an anonymous market at the OMX Helsinki Stock Exchange. I broaden my focus slightly in the third essay, to include releases of macroeconomic data in the United States. I analyze the effect of these releases on European cross-listed stocks. The fourth and last essay examines the uses of standard methodologies of price discovery analysis in a novel way. Specifically, I study price discovery within one market, between local and foreign traders.

Essays on Stock Option Compensation and the Role of Incentives and Risk (summary section only)

Managerial pay-for-performance sensitivity has increased rapidly around the world. Early empirical research showed that pay-for-performance sensitivity resulting from stock ownership and stock options appeared to be quite low during the 1970s and early 1980s in the U.S. However, recent empirical research from the U.S. shows an enormous increase in pay-for-performance sensitivity. The global trend has also reached Finland, where stock options have become a major ingredient of executive compensation. The fact that stock options seem to be an appealing form of remuneration from a theoretical point of view combined with the observation that the use of this compensation form has increased significantly during the recent years, implies that research on the dynamics of stock option compensation is highly relevant for the academic community, as well as for practitioners and regulators. The research questions of the thesis are analyzed in four separate essays. The first essay examines whether stock option compensation practices of Finnish firms are consistent with predictions from principal-agent theory. The second essay explores one of the major puzzles in the compensation literature by studying determinants of stock option contract design. In theory, optimal contract design should vary according to firm characteristics. However, in the U.S., variation in contract design seems to be surprisingly low, a phenomenon generally attributed to tax and accounting considerations. In Finland, however, firms are not subject to stringent contracting restrictions, and the variation in contract design tends, in fact, to be quite substantial. The third essay studies the impact of price- and risk incentives arising from stock option compensation on firm investment. In addition, the essay explores one of the most debated questions in the literature, in particular, the relation between incentives and firm performance. Finally, several strands of literature in both economics and corporate finance hypothesize that economic uncertainty is related to corporate decision-making. Previous research has shown that risk tends to slow down firm investment. In the fourth essay, it is hypothesized that firm risk slows down growth from a more universal perspective. Consistent with this view, it is shown that risk not only tends to slow down firm investment, but also employment growth. Moreover, the essay explores whether the nature of firms’ compensation policies, in particular, whether firms make use of stock option compensation, affects the relation between risk and firm growth. In summary, the four essays contribute to the current understanding of stock options as a form of equity incentives, and how incentives and risk affect corporate decision-making. By this, the thesis promotes the knowledge related to the modern theory of the firm.

Bootstrap and Fast Double Bootstrap Tests of Cointegration Rank with Financial Time Series

The likelihood ratio test of cointegration rank is the most widely used test for cointegration. Many studies have shown that its finite sample distribution is not well approximated by the limiting distribution. The article introduces and evaluates by Monte Carlo simulation experiments bootstrap and fast double bootstrap (FDB) algorithms for the likelihood ratio test. It finds that the performance of the bootstrap test is very good. The more sophisticated FDB produces a further improvement in cases where the performance of the asymptotic test is very unsatisfactory and the ordinary bootstrap does not work as well as it might. Furthermore, the Monte Carlo simulations provide a number of guidelines on when the bootstrap and FDB tests can be expected to work well. Finally, the tests are applied to US interest rates and international stock prices series. It is found that the asymptotic test tends to overestimate the cointegration rank, while the bootstrap and FDB tests choose the correct cointegration rank.

An Empirical Comparison of Linear and Nonlinear Volatility Models for Nordic Stock Returns

This paper examines how volatility in financial markets can preferable be modeled. The examination investigates how good the models for the volatility, both linear and nonlinear, are in absorbing skewness and kurtosis. The examination is done on the Nordic stock markets, including Finland, Sweden, Norway and Denmark. Different linear and nonlinear models are applied, and the results indicates that a linear model can almost always be used for modeling the series under investigation, even though nonlinear models performs slightly better in some cases. These results indicate that the markets under study are exposed to asymmetric patterns only to a certain degree. Negative shocks generally have a more prominent effect on the markets, but these effects are not really strong. However, in terms of absorbing skewness and kurtosis, nonlinear models outperform linear ones.

Test of the Clustering Hypothesis in the Helsinki Exchanges

This paper investigates the clustering pattern in the Finnish stock market. Using trading volume and time as factors capturing the clustering pattern in the market, the Keim and Madhavan (1996) and the Engle and Russell (1998) model provide the framework for the analysis. The descriptive and the parametric analysis provide evidences that an important determinant of the famous U-shape pattern in the market is the rate of information arrivals as measured by large trading volumes and durations at the market open and close. Precisely, 1) the larger the trading volume, the greater the impact on prices both in the short and the long run, thus prices will differ across quantities. 2) Large trading volume is a non-linear function of price changes in the long run. 3) Arrival times are positively autocorrelated, indicating a clustering pattern and 4) Information arrivals as approximated by durations are negatively related to trading flow.