Influence of harvesting strategy on nutrient supply and production of dairy cows consuming diets based on grass and red clover silage

The main objective of this thesis was to elucidate the effects of regrowth grass silage and red clover silage on nutrient supply and milk production of dairy cows as compared with primary growth grass silages. In the first experiment (publication I), two primary growth and four regrowth grass silages were harvested at two stages of growth. These six silages were fed to 24 lactating dairy cows with two levels of concentrate allowance. Silage intake and energy corrected milk yield (ECM) responses, and the range in these response variables between the diets, were smaller when regrowth silages rather than primary growth silages were fed. Milk production of dairy cows reflected the intake of metabolizable energy (ME), and no differences in the ME utilization were found between the diets based on silages harvested from primary growth and regrowth. The ECM response to increased concentrate allowance was, on average, greater when regrowth rather than primary growth silages were fed. In the second experiment (publication II), two silages from primary growth and two from regrowth used in I were fed to rumen cannulated lactating dairy cows. Cows consumed less feed dry matter (DM), energy and protein, and produced less milk, when fed diets based on regrowth silages rather than primary growth silages. Lower milk production responses of regrowth grass silage diets were mainly due to the lower silage DM intake, and could not be accounted for by differences in energy or protein utilization. Regrowth grass silage intake was not limited due to neutral detergent fibre (NDF) digestion or rumen fill or passage kinetics. However, lower intake may be at least partly attributable to plant diseases such as leaf spot infections, dead deteriorating material or abundance of weeds, which are all higher in regrowth compared with primary growth, and increase with advancing regrowth. In the third experiment (publications III and IV), red clover silages and grass silages harvested at two stages of growth, and a mixed diet of red clover and grass silages, were fed to five rumen cannulated lactating dairy cows. In spite of the lower average ME intake for red clover diets, the ECM production remained unchanged suggesting more efficient utilisation of ME for red clover diets compared with grass diets. Intake of N, and omasal canal flows of total non-ammonia N (NAN), microbial and non-microbial NAN were higher for red clover than for grass silage diets, but were not affected by forage maturity. Delaying the harvest tended to decrease DM intake of grass silage and increase that of red clover silage. The digestion rate of potentially digestible NDF was faster for red clover diets than for grass silage diets. Delaying the harvest decreased the digestion rate for grass but increased it for red clover silage diets. The low intake of early-cut red clover silage could not be explained by silage digestibility, fermentation quality, or rumen fill but was most likely related to the nutritionally suboptimal diet composition because inclusion of moderate quality grass silage in mixed diet increased silage DM intake. Despite the higher total amino acid supply of cows fed red clover versus grass silage diets, further milk production responses on red clover diets were possibly compromised by an inadequate supply of methionine as evidenced by lower methionine concentration in the amino acid profile of omasal digesta and plasma. Increasing the maturity of ensiled red clover does not seem to affect silage DM intake as consistently as that of grasses. The efficiency of N utilization for milk protein synthesis was lower for red clover diets than for grass diets. It was negatively related to diet crude protein concentration similarly to grass silage diets.

The Impact of Emissions Trading on the Price of Electricity in Nord Pool : Market Power and Price Determination in the Nordic Electricity Market

The objective of this thesis is to find out how dominant firms in a liberalised electricity market will react when they face an increase in the level of costs due to emissions trading, and how this will effect the price of electricity. The Nordic electricity market is chosen as the setting in which to examine the question, since recent studies on the subject suggest that interaction between electricity markets and emissions trading is very much dependent on conditions specific to each market area. There is reason to believe that imperfect competition prevails in the Nordic market, thus the issue is approached through the theory of oligopolistic competition. The generation capacity available at the market, marginal cost of electricity production and seasonal levels of demand form the data based on which the dominant firms are modelled using the Cournot model of competition. The calculations are made for two levels of demand, high and low, and with several values of demand elasticity. The producers are first modelled under no carbon costs and then by adding the cost of carbon dioxide at 20€/t to those technologies subject to carbon regulation. In all cases the situation under perfect competition is determined as a comparison point for the results of the Cournot game. The results imply that the potential for market power does exist on the Nordic market, but the possibility for exercising market power depends on the demand level. In season of high demand the dominant firms may raise the price significantly above competitive levels, and the situation is aggravated when the cost of carbon dioixide is accounted for. Under low demand leves there is no difference between perfect and imperfect competition. The results are highly dependent on the price elasticity of demand.

From trading to eCommunity management

"The increasing pressure for enterprises to join into agile business networks is changing the requirements on the enterprise computing systems. The supporting infrastructure is increasingly required to provide common facilities and societal infrastructure services to support the lifecycle of loosely-coupled, eContract-governed business networks. The required facilities include selection of those autonomously administered business services that the enterprises are prepared to provide and use, contract negotiations, and furthermore, monitoring of the contracted behaviour with potential for breach management. The essential change is in the requirement of a clear mapping between business-level concepts and the automation support for them. Our work has focused on developing B2B middleware to address the above challenges; however, the architecture is not feasible without management facilities for trust-aware decisions for entering business networks and interacting within them. This paper discusses how trust-based decisions are supported and positioned in the B2B middleware."

On the Problem of Participation in Strategy: A Critical Discursive Perspective

We still know little of why strategy processes often involve participation problems. In this paper, we argue that this crucial issue is linked to fundamental assumptions about the nature of strategy work. Hence, we need to examine how strategy processes are typically made sense of and what roles are assigned to specific organizational members. For this purpose, we adopt a critical discursive perspective that allows us to discover how specific conceptions of strategy work are reproduced and legitimized in organizational strategizing. Our empirical analysis is based on an extensive research project on strategy work in 12 organizations. As a result of our analysis, we identify three central discourses that seem to be systematically associated with nonparticipatory approaches to strategy work: “mystification,” “disciplining,” and “technologization.” However, we also distinguish three strategy discourses that promote participation: “self-actualization,” “dialogization,” and “concretization.” Our analysis shows that strategy as practice involves alternative and even competing discourses that have fundamentally different kinds of implications for participation in strategy work. We argue from a critical perspective that it is important to be aware of the inherent problems associated with dominant discourses as well as to actively advance the use of alternative ones.

Taking the linguistic turn seriously: Strategy as a multifaceted interdiscursive phenomenon

Although we have seen a proliferation of studies examining the discursive aspects of strategy, the full potential of the linguistic turn has not yet been realized. This paper argues for a multifaceted interdiscursive approach that can help to go beyond simplistic views on strategy as unified discourse and pave the way for the new research efforts. At the meta-level, it is important to focus attention on struggles over competing conceptions of strategy in this body of knowledge. At the meso-level it is interesting to examine alternative strategy narratives to better understand the polyphony and dialogicality in organizational strategizing. At the micro-level, it is useful to reflect on the rhetorical tactics and skills that are used in strategy conversations to promote or resist specific views. This paper calls for new focused analyses at these different levels of analysis, but also for studies of the processes linking these levels.

Strategy as text and discursive practice: A genre-based approach to strategizing in City Administration

Despite the acknowledged importance of strategic planning in business and other organizations, there are few studies focusing on strategy texts and the related processes of their production and consumption. In this paper, we attempt to partially fill this research gap by examining the institutionalized aspects of strategy discourse: what strategy is as genre. Combining textual analysis and analysis of conversation, the article focuses on the official strategy of the City of Lahti in Finland. Our analysis shows how specific communicative purposes and lexico-grammatical features characterize the genre of strategy and how the actual negotiations over strategy text involve particular kinds of intersubjectivity and intertextuality.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

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.

The Relationship Between Liquidity, Trading Activity and Return - Studies of the Finnish and Swedish Stock Markets

Liquidity, or how easy an investment is to buy or sell, is becoming increasingly important for financial market participants. The objective of this dissertation is to contribute to the understanding of how liquidity affects financial markets. The first essays analyze the actions taken by underwriters immediately after listing to improve liquidity of IPO stock. To estimate the impact of underwriter activity on the pricing of the IPOs, the order book during the first weeks of trading in the IPO stock is studied. Evidence of stabilization and liquidity enhancing activities by underwriters is found. The second half of the dissertation is concerned with the daily trading of stocks where liquidity may be impacted by policy issues such as changes in taxes or exchange fees and by opening the access to the markets for foreign investors. The desirability of a transaction tax on securities trading is addressed. An increase in transaction tax is found to cause lower prices and higher volatility. In the last essay the objective is to determine if the liquidity of a security has an impact on the return investors require. The results support the notion that returns are negatively correlated to liquidity.

An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions

This paper uses the Value-at-Risk approach to define the risk in both long and short trading positions. The investigation is done on some major market indices(Japanese, UK, German and US). The performance of models that takes into account skewness and fat-tails are compared to symmetric models in relation to both the specific model for estimating the variance, and the distribution of the variance estimate used as input in the VaR estimation. The results indicate that more flexible models not necessarily perform better in predicting the VaR forecast; the reason for this is most probably the complexity of these models. A general result is that different methods for estimating the variance are needed for different confidence levels of the VaR, and for the different indices. Also, different models are to be used for the left respectively the right tail of the distribution.