MODELING THE EFFECT OF INSTITUTIONAL CONSTRAINTS ON SHORT-RUN TIMBER SUPPLY ON PUBLIC LAND: A CASE STUDY OF QUOTA HOLDERS IN ALBERTA

The short-run timber supply behavior of quota holders is investigated in the face of institutional constraints and fixed stumpage prices. A dynamic optimization technique is used to predict production and estimate shadow prices of processing capacity constraints and annual allowable cut restrictions. Models for large, medium, and small tenure holders are formulated reflecting the different cost structures of different sized firms. Results indicate that all categories of quota holders incur substantial costs due to institutional constraints, and that eliminating both types of constraints simultaneously reduces costs much more than the combined savings from eliminating each type of constraint individually.     

Estimating time-varying conditional correlations between stock and foreign exchange markets

This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.     

Normalized truncated Levy walks applied to the study of financial indices

This work is devoted to the study of the statistical properties of financial indices from developed and emergent markets.     

Can core allocations be achieved in avoidable fixed cost environments using two-part price competition?

Two environments are studied in which sellers have only avoidable fixed costs and fixed capacities: (a) in the first, the core exists and is supportable by a competitive equilibrium; (b) in the second, the core exists but there is no competitive equilibrium. In both cases, demand price is constant up to capacity. Experiments using the double auction institution fail to converge to 100% efficiency allocations in either environment. We study a new mechanism in which sellers each submit fixed vendor's fees, which must be paid before units can be sold, as well as a price and corresponding maximum quantity. Buyers submit price-quantity bids. A computing center determines allocations that maximize the aggregate surplus subject to the price, quantity, and vendor fee constraints. We report 20 experiments: 5 inexperienced (45 periods) and 5 experienced (75 periods) subject groups in each of the designs (a) and (b). Buyers are simulated to be fully revealing. The same four sellers participate in both inexperienced and experienced sessions. We explain why this environment proves difficult in these experiments and what we intend to do about it in further iterations.     

石油价格波动与我国进口价格的动态关系研究——基于对油价冲击分解的结构VAR模型

以2000～2008年我国月度数据为研究样本,从油价冲击的正负冲击角度分析国际石油价格波动与我国进口价格之间的存在的动态传导关系,并对其产生的原因进行了讨论.首先采用结构VAR(SVAR)模型对我国进口价格受到的油价冲击进行结构分解,其次用移动平均形式的SVAR模型分析不同油价冲击对进口价格的影响.结果表明,油价上涨对进口价格有显著的正向拉动作用,同期经济需求上涨推动进口价格有较大涨幅;而油价下跌时进口价格跌幅较小,甚至与油价波动存在负相关关系,这主要是由经济需求增加造成的.因此,研究石油价格对进口价格水平的动态传导关系.要区分油价冲击形式,这一结论有助于政府部门针对油价正负冲击的不同影响来制定应对政策,确保经济的稳定发展.     

Managing procurement and production outsourcing under dynamic prices

This paper proposes a procurement and production outsourcing model subject to a dynamic prices environment. Using the optimal control theory we obtain the necessary conditions of the optimal procurement and production policy. From the study of optimal control conditions, we derive qualitative properties of the optimal procurement and production decisions for a few exemplifying cases. Through these results we are able to provide some managerial implications for managers to make real decisions.     

Modeling electricity spot prices using mean-reverting multifractal processes

We discuss stochastic modeling of volatility persistence and anti-correlations in electricity spot prices, and for this purpose we present two mean-reverting versions of the multifractal random walk (MRW). In the first model the anti-correlations are modeled in the same way as in an Ornstein–Uhlenbeck process, i.e. via a drift (damping) term, and in the second model the anti-correlations are included by letting the innovations in the MRW model be fractional Gaussian noise with H<1/2$H<1/2$. For both models we present approximate maximum likelihood methods, and we apply these methods to estimate the parameters for the spot prices in the Nordic electricity market. The maximum likelihood estimates show that electricity spot prices are characterized by scaling exponents that are significantly different from the corresponding exponents in stock markets, confirming the exceptional nature of the electricity market. In order to compare the damped MRW model with the fractional MRW model we use ensemble simulations and wavelet-based variograms, and we observe that certain features of the spot prices are better described by the damped MRW model. The characteristic correlation time is estimated to approximately half a year.     

Efficient Pricing of Derivatives on Assets with Discrete Dividends

It is argued that due to inconsistencies in existing methods to approximate the prices of equity options on assets which pay out fixed cash dividends at future dates, a new approach to this problem may be useful. Logically consistent methods which are guaranteed to exclude arbitrage exist, but they are not very popular in practice due to their computational complexity. An algorithm is defined which is easy to understand, computationally efficient, and which guarantees to generate prices which exclude arbitrage possibilitites. It is shown that for the method to work a mild uniform convergence condition must be satisfied and this condition is indeed satisfied for standard European and American options. Numerical results testify to the accuracy and flexibility of the method.     

The Heston stochastic volatility model in Hilbert space

We extend the Heston stochastic volatility model to a Hilbert space framework. The tensor Heston stochastic variance process is defined as a tensor product of a Hilbert-valued Ornstein–Uhlenbeck process with itself. The volatility process is then defined by a Cholesky decomposition of the variance process. We define a Hilbert-valued Ornstein–Uhlenbeck process with Wiener noise perturbed by this stochastic volatility, and compute the characteristic functional and covariance operator of this process. This process is then applied to the modeling of forward curves in energy and commodity markets. Finally, we compute the dynamics of the tensor Heston volatility model when the generator is bounded, and study its projection down to the real line for comparison with the classical Heston dynamics.