250 resultados para : Hedging


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This thesis focuses on the theoretical examination of the exchange rate economic (operating) exposure within the context of the theory of the firm, and proposes some hedging solutions using currency options. The examination of economic exposure is based on such parameters as firms' objectives, industry structure and production cost efficiency. In particular, it examines an hypothetical exporting firm with costs in domestic currency, which faces competition from foreign firms in overseas markets and has a market share expansion objective. Within this framework, the hypothesis is established that economic exposure, portrayed in a diagram connecting export prices and real exchange rates, is asymmetric (i.e. the negative effects depreciation are higher than the positive effects of a currency depreciation). In this case, export business can be seen as a real option, given by exporting firms to overseas customer. Different scenarios about the asymmetry hypothesis can be derived for different assumptions about the determinants of economic exposure. Having established the asymmetry hypothesis, the hedging against this exposure is analysed. The hypothesis is established, that a currency call option should be used in hedging against asymmetric economic exposure. Further, some advanced currency options stategies are discussed, and their use in hedging several scenarios of exposure is indicated, establishing the hypothesis that, the optimal options strategy is a function of the determinants of exposure. Some extensions on the theoretical analysis are examined. These include the hedging of multicurrency exposure using options, and the exposure of a purely domestic firm facing import competition. The empirical work addresses two issues: the empirical validity of the asymmetry hypothesis and the examination of the hedging effectiveness of currency options.

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Although risk management can be justified by financial distress, the theoretical models usually contain hedging instruments free of funding risk. In practice, management of the counterparty risk in derivative transactions is of enhanced importance, consequently not only is trading on exchanges subject to the presence of a margin account, but also in bilateral (OTC) agreements parties will require margins or collateral from their partners in order to hedge the mark-tomarket loss of the transaction. The aim of this paper is to present and compare two models where the financing need of the hedging instrument also appears, influencing the hedging strategy and the optimal hedging ratio. Both models contain the same source of risk and optimisation criterion, but the liquidity risk is modelled in different ways. In the first model, there is no additional financing resource that can be used to finance the margin account in case of a margin call, which entails the risk of liquidation of the hedging position. In the second model, the financing is available but a given credit spread is to be paid for this, so hedging can become costly.

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Bet-hedging strategies are used by organisms to survive in

unpredictable environments. To pursue a bet-hedging strategy, an

organism must produce multiple phenotypes from a single genotype. What

molecular mechanisms allow this to happen? To address this question, I

created a synthetic system that displays bet-hedging behavior, and

developed a new technique called `TrackScar' to measure the fitness

and stress-resistance of individual cells. I found that bet-hedging

can be generated by actively sensing the environment, and that

bet-hedging strategies based on active sensing need not be

metabolically costly. These results suggest that to understand how

bet-hedging strategies are produced, microorganisms must be

examined in the actual environments that they come from.

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We examine whether intraday Chinese return predictability is linked to optimal portfolio holding and hedging. We find that: (1) S&P500 futures returns only predict Chinese spot market returns in up to 5-minute of trading with predictability disappearing at higher frequencies of trade; (2) the portfolio weight is maximised at the 5-minute trading frequency, when predictability is the strongest; and (3) when predictability is the strongest, significantly less shorting of the futures is required to minimise risk when a long position is taken in the Chinese market.

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This paper analyzes the common factor structure of US, German, and Japanese Government bond returns. Unlike previous studies, we formally take into account the presence of country-specific factors when estimating common factors. We show that the classical approach of running a principal component analysis on a multi-country dataset of bond returns captures both local and common influences and therefore tends to pick too many factors. We conclude that US bond returns share only one common factor with German and Japanese bond returns. This single common factor is associated most notably with changes in the level of domestic term structures. We show that accounting for country-specific factors improves the performance of domestic and international hedging strategies.

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This study contributes to the understanding of the contribution of financial reserves to sustaining nonprofit organisations. Recognising the limited recent Australian research in the area of nonprofit financial vulnerability, it specifically examines financial reserves held by signatories to the Code of Conduct of the Australian Council for International Development (ACFID) for the years 2006 to 2010. As this period includes the Global Financial Crisis, it presents a unique opportunity to observe the role of savings in a period of heightened financial threats to sustainability. The need for nonprofit entities to maintain reserves, while appearing intuitively evident, is neither unanimously accepted nor supported by established theoretic constructs. Some early frameworks attempt to explain the savings behaviour of nonprofit organisations and its role in organisational sustainability. Where researchers have considered the issue, its treatment has usually been either purely descriptive or alternatively, peripheral to a broader attempt to predict financial vulnerability. Given the importance of nonprofit entities to civil society, the sustainability of these organisations during times of economic contraction, such as the recent Global Financial Crisis, is a significant issue. Widespread failure of nonprofits, or even the perception of failure, will directly affect, not only those individuals who access their public goods and services, but would also have impacts on public confidence in both government and the sectors’ ability to manage and achieve their purpose. This study attempts to ‘shine a light’ on the paradox inherent in considering nonprofit savings. On the one hand, a public prevailing view is that nonprofit organisations should not hoard and indeed, should spend all of their funds on the direct achievement of their purposes. Against this, is the commonsense need for a financial buffer if only to allow for the day to day contingencies of pay rises and cost increases. At the entity level, the extent of reserves accumulated (or not) is an important consideration for Management Boards. The general public are also interested in knowing the level of funds held by nonprofits as a measure of both their commitment to purpose and as an indicator of their effectiveness. There is a need to communicate the level and prevalence of reserve holdings, balancing the prudent hedging of uncertainty against a sense of resource hoarding in the mind of donors. Finally, funders (especially governments) are interested in knowing the appropriate level of reserves to facilitate the ongoing sustainability of the sector. This is particularly so where organisations are involved in the provision of essential public goods and services. At a scholarly level, the study seeks to provide a rationale for this behaviour within the context of appropriate theory. At a practical level, the study seeks to give an indication of the drivers for savings, the actual levels of reserves held within the sector studied, as well as an indication as to whether the presence of reserves did mitigate the effects of financial turmoil during the Global Financial Crisis. The argument is not whether there is a need to ensure sustainability of nonprofits, but rather how it is to be done and whether the holding of reserves (net assets) is an essential element is achieving this. While the study offers no simple answers, it does appear that the organisations studied present as two groups, the ‘savers’ who build reserves and keep ‘money in the bank’ and ‘spender-delivers’ who put their resources ‘on the ground’. To progress an understanding of this dichotomy, the study suggests a need to move from its current approach to one which needs to more closely explore accounts based empirical donor attitude and nonprofit Management Board strategy.

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Construction projects are a high risk business activity. When undertaking projects in an international context, it is further complicated by the risk of fluctuations in the foreign exchange rates (FOREX). Construction business performance is affected by these fluctuations. They affect progress and cause delays, which in turn create problems for subcontractors, namely cost overruns, disputes, arbitration, total abandonment and litigation. FOREX fluctuations also cause the price of raw materials to increase, leading the cost overruns. Managing FOREX risk is critical and past research have focused on the need for adequate insurance, careful planning and management, and foreign exchange futures hedging to overcome issues that have been caused by the FOREX risk. Analysis of FOREX risk in international construction business usually focused only on issues at the project level. There is currently lack of understanding of Organisational Capabilities (OC) to manage the impacts of FOREX risk, which when examined, are seen in isolation. This paper attempts to bridge the gap by discussing the impacts of FOREX fluctuations on the international construction business. The focus is on the OC perspective and the need to develop OC framework to mitigate the risk in sustaining construction business performance.

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Follow-the-Leader (FTL) is an intuitive sequential prediction strategy that guarantees constant regret in the stochastic setting, but has poor performance for worst-case data. Other hedging strategies have better worst-case guarantees but may perform much worse than FTL if the data are not maximally adversarial. We introduce the FlipFlop algorithm, which is the first method that provably combines the best of both worlds. As a stepping stone for our analysis, we develop AdaHedge, which is a new way of dynamically tuning the learning rate in Hedge without using the doubling trick. AdaHedge refines a method by Cesa-Bianchi, Mansour, and Stoltz (2007), yielding improved worst-case guarantees. By interleaving AdaHedge and FTL, FlipFlop achieves regret within a constant factor of the FTL regret, without sacrificing AdaHedge’s worst-case guarantees. AdaHedge and FlipFlop do not need to know the range of the losses in advance; moreover, unlike earlier methods, both have the intuitive property that the issued weights are invariant under rescaling and translation of the losses. The losses are also allowed to be negative, in which case they may be interpreted as gains.

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The increasing integration of Renewable Energy Resources (RER) and the role of Electric Energy Storage (EES) in distribution systems has created interest in using energy management strategies. EES has become a suitable resource to manage energy consumption and generation in smart grid. Optimize scheduling of EES can also maximize retailer’s profit by introducing energy time-shift opportunities. This paper proposes a new strategy for scheduling EES in order to reduce the impact of electricity market price and load uncertainty on retailers’ profit. The proposed strategy optimizes the cost of purchasing energy with the objective of minimizing surplus energy cost in hedging contract. A case study is provided to demonstrate the impact of the proposed strategy on retailers’ financial benefit.

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We address risk minimizing option pricing in a semi-Markov modulated market where the floating interest rate depends on a finite state semi-Markov process. The growth rate and the volatility of the stock also depend on the semi-Markov process. Using the Föllmer–Schweizer decomposition we find the locally risk minimizing price for European options and the corresponding hedging strategy. We develop suitable numerical methods for computing option prices.

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In my thesis I have been studying the effects of population fragmentation and extinction-recolonization dynamics on genetic and evolutionary processes in the Glanville fritillary butterfly (Melitaea cinxia). By conducting crosses within and among newly-colonized populations and using several fitness measures, I found a strong decrease in fitness following colonization by a few related individuals, and a strong negative relationship between parental relatedness and offspring fitness. Thereafter, I was interested in determining the number and relatedness of individuals colonizing new populations, which I did using a set of microsatellites I had previously developed for this species. Additionally, I am interested in the evolution of key life-history traits. By following the lifetime reproductive success of males emerging at different times in a semi-natural setup, I demonstrated that protandry is adaptive in males, and I was able to rule out, for M. cinxia, alternative incidental hypotheses evoked to explain the evolution of protandry in insects. Finally, in work I did together with Prof. Hanna Kokko, I am proposing bet-hedging as a new mechanism that could explain the evolution of polyandry in M. cinxia.

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We address asymptotic analysis of option pricing in a regime switching market where the risk free interest rate, growth rate and the volatility of the stocks depend on a finite state Markov chain. We study two variations of the chain namely, when the chain is moving very fast compared to the underlying asset price and when it is moving very slow. Using quadratic hedging and asymptotic expansion, we derive corrections on the locally risk minimizing option price.

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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.

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This study evaluates three different time units in option pricing: trading time, calendar time and continuous time using discrete approximations (CTDA). The CTDA-time model partitions the trading day into 30-minute intervals, where each interval is given a weight corresponding to the historical volatility in the respective interval. Furthermore, the non-trading volatility, both overnight and weekend volatility, is included in the first interval of the trading day in the CTDA model. The three models are tested on market prices. The results indicate that the trading-time model gives the best fit to market prices in line with the results of previous studies, but contrary to expectations under non-arbitrage option pricing. Under non-arbitrage pricing, the option premium should reflect the cost of hedging the expected volatility during the option’s remaining life. The study concludes that the historical patterns in volatility are not fully accounted for by the market, rather the market prices options closer to trading time.