Model Uncertainty and Liquidity

Extreme market outcomes are often followed by a lack of liquidity and a lack of trade. This market collapse seems particularly acute for markets where traders rely heavily on a specific empirical model such as in derivative markets. Asset pricing and trading, in these cases, are intrinsically model dependent. Moreover, the observed behavior of traders and institutions that places a large emphasis on 'worst-case scenarios'' through the use of 'stress testing'' and 'value-at-risk'' seems different than Savage rationality (expected utility) would suggest. In this paper we capture model-uncertainty explicitly using an Epstein-Wang (1994) uncertainty-averse utility function with an ambiguous underlying asset-returns distribution. To explore the connection of uncertainty with liquidity, we specify a simple market where a monopolist financial intermediary makes a market for a propriety derivative security. The market-maker chooses bid and ask prices for the derivative, then, conditional on trade in this market, chooses an optimal portfolio and consumption. We explore how uncertainty can increase the bid-ask spread and, hence, reduces liquidity. In addition, 'hedge portfolios'' for the market-maker, an important component to understanding spreads, can look very different from those implied by a model without Knightian uncertainty. Our infinite-horizon example produces short, dramatic decreases in liquidity even though the underlying environment is stationary.

Generalized Disappointment Aversion and Asset Prices

We provide an axiomatic model of preferences over atemporal risks that generalizes Gul (1991) A Theory of Disappointment Aversion' by allowing risk aversion to be first order' at locations in the state space that do not correspond to certainty. Since the lotteries being valued by an agent in an asset-pricing context are not typically local to certainty, our generalization, when embedded in a dynamic recursive utility model, has important quantitative implications for financial markets. We show that the state-price process, or asset-pricing kernel, in a Lucas-tree economy in which the representative agent has generalized disappointment aversion preferences is consistent with the pricing kernel that resolves the equity-premium puzzle. We also demonstrate that a small amount of conditional heteroskedasticity in the endowment-growth process is necessary to generate these favorable results. In addition, we show that risk aversion in our model can be both state-dependent and counter-cyclical, which empirical research has demonstrated is necessary for explaining observed asset-pricing behavior.

Application of neural network observer for on-line estimation of salient-pole synchronous generators' dynamic parameters using the operating data

Parameter identification is critical for modern control strategies in electrical power systems which is considered both dynamic performance and energy efficiency. This paper presents a novel application of ANN observers in estimating and tracking Salient-Pole Synchronous Generator Dynamic Parameters using time-domain, on-line disturbance measurements. The data for training ANN Observers are obtained through off-line simulations of a salient-pole synchronous generator operating in a one-machine-infinite-bus environment. The Levenberg-Marquardt algorithm has been adopted and assimilated into the back-propagation learning algorithm for training feed-forward neural networks. The inputs of ANNs are organized in conformity with the results of the observability analysis of synchronous generator dynamic parameters in its dynamic behavior. A collection of ANNs with same inputs but different outputs are developed to determine a set of the dynamic parameters. The ANNs are employed to estimate the dynamic parameters by the measurements which are carried out within each kind of fault separately. The trained ANNs are tested with on-line measurements to identify the dynamic parameters. Simulation studies indicate the ANN observer has a great ability to identify the dynamic parameters of salient-pole synchronous generator. The results also show that the tests which have given better results in estimation of each dynamic parameter can be obtained

The relation between solar cell flight performance data and materials and manufacturing data Final report

Flight performance data for solar cell power systems in satellites and correlation with manufacturing methods and material

Transition from subbarrier to deep subbarrier regimes in heavy-ion fusion reactions

We analyze the recent experimental data of heavy-ion fusion cross sections available up to deep subbarrier energies in order to discuss the threshold incident energy for a deep subbarrier fusion hindrance phenomenon. To this end, we employ a one-dimensional potential model with a Woods-Saxon internuclear potential. Fitting the experimental data in two different energy regions with different Woods-Saxon potentials, we define the threshold energy as an intersect of the two fusion excitation functions. We show that the threshold energies so extracted are in good agreement with the empirical systematics as well as with the values of the Krappe-Nix-Sierk (KNS) potential at the touching point. We also discuss the asymptotic energy shift of fusion cross sections with respect to the potential model calculations, and show that it decreases with decreasing energies in the deep subbarrier region although it takes a constant value at subbarrier energies.Comment: 4 pages, 4 figure

Integrated waveguide and nanostructured sensor platform for surface-enhanced Raman spectroscopy

Limitations of current sensors include large dimensions, sometimes limited sensitivity and inherent single-parameter measurement capability. Surface-enhanced Raman spectroscopy can be utilized for environment and pharmaceutical applications with the intensity of the Raman scattering enhanced by a factor of 106. By fabricating and characterizing an integrated optical waveguide beneath a nanostructured precious metal coated surface a new surface-enhanced Raman spectroscopy sensing arrangement can be achieved. Nanostructured sensors can provide both multiparameter and high-resolution sensing. Using the slab waveguide core to interrogate the nanostructures at the base allows for the emission to reach discrete sensing areas effectively and should provide ideal parameters for maximum Raman interactions. Thin slab waveguide films of silicon oxynitride were etched and gold coated to create localized nanostructured sensing areas of various pitch, diameter, and shape. These were interrogated using a Ti:Sapphire laser tuned to 785-nm end coupled into the slab waveguide. The nanostructured sensors vertically projected a Raman signal, which was used to actively detect a thin layer of benzyl mercaptan attached to the sensors

Penentuan taburan terbaik daripada hujan maksimum bagi tempoh ribut yang panjang melebihi 48 Jam (MR) dan hujan maksimum tahunan (MT)

Kajian ini tertumpu kepada penentuan taburan terbaik untuk memodelkan siri data maksimum tahunan (MT) dan siri maksimum hujan dalam tempoh ribut yang melebihi 48 jam (MR). Data hujan setiap jam dari tahun 1970 hingga 2008 dari 4 stesen hujan di Semenanjung Malaysia telah digunakan dalam kajian ini. Kedua jenis data maksimum ini mempunyai kegunaan yang sangat baik bagi mengesan banjir di kawasan bandar terutama yang disebabkan oleh kegagalan sistem perparitan dalam menampung hujan lebat semasa tempoh ribut yang panjang, manakala kajian yang boleh meramalkan ketahanan empangan dalam masa 50 atau 100 tahun kehadapan sangat bergantung kepada penentuan taburan hujan maksimum tahunan. Pelbagai taburan yang sering digunakan bagi kajian pemodelan ekstrim digunakan untuk mendapatkan taburan yang terbaik bagi menerangkan taburan kedua jenis data hujan maksimum tersebut. Dua ujian kebagusan model telah digunakan iaitu kaedah bergraf dan kaedah PRKD. Hasil menunjukkan bahawa taburan Pearson Jenis 3 adalah yang terbaik untuk menerangkan taburan hujan maksimum tahunan pada kesemua stesen hujan yang digunakan pada kajian ini. Taburan Pareto dan Gama adalah taburan yang terbaik bagi menerangkan taburan hujan maksimum yang berlaku pada tempoh ribut yang panjang. Hasil kajian penentuan taburan terbaik bagi hujan maksimum tahunan di atas juga telah berjaya dalam meramalkan hujan maksimum yang akan berlaku untuk masa 50 dan 100 tahun yang akan datang

"Recursive Preferences,"

We summarize the class of recursive preferences. These preferences fit naturally with recursive solution methods and hold the promise of generating new insights into familiar problems. Portfolio choice is used as an example

A fine grained heuristic to capture web navigation patterns

In previous work we have proposed a statistical model to capture the user behaviour when browsing the web. The user navigation information obtained from web logs is modelled as a hypertext probabilistic grammar (HPG) which is within the class of regular probabilistic grammars. The set of highest probability strings generated by the grammar corresponds to the user preferred navigation trails. We have previously conducted experiments with a Breadth-First Search algorithm (BFS) to perform the exhaustive computation of all the strings with probability above a specified cut-point, which we call the rules. Although the algorithm’s running time varies linearly with the number of grammar states, it has the drawbacks of returning a large number of rules when the cut-point is small and a small set of very short rules when the cut-point is high. In this work, we present a new heuristic that implements an iterative deepening search wherein the set of rules is incrementally augmented by first exploring trails with high probability. A stopping parameter is provided which measures the distance between the current rule-set and its corresponding maximal set obtained by the BFS algorithm. When the stopping parameter takes the value zero the heuristic corresponds to the BFS algorithm and as the parameter takes values closer to one the number of rules obtained decreases accordingly. Experiments were conducted with both real and synthetic data and the results show that for a given cut-point the number of rules induced increases smoothly with the decrease of the stopping criterion. Therefore, by setting the value of the stopping criterion the analyst can determine the number and quality of rules to be induced; the quality of a rule is measured by both its length and probability

Model Uncertainty and Liquidity

We investigate the dynamic portfolio problem of a market-maker for a derivative security whose preferences exhibit uncertainty aversion (Knightian uncertainty). The Choquet-expected utility implied by such preference is used to capture the feature that the trader is uncertain about which model should be used. The prices that emerge from the model are similar to standard models and have the feature that as uncertainty is removed, the derivative prices converge to standard prices. However, the optimal changes in the agent's portfolio that results from the option position are quite different than the standard hedge position. It is this feature that links uncertainty with market liquidity.