Market Failures and Regulatory Failures: Lessons from Past and Present Financial Crises

The paper analyzes the financial crisis of 2007–2009 through the lens of market failures and regulatory failures and presents a case that there were four primary failures contributing to the crisis: excessive risk-taking in the financial sector due to mispriced government guarantees; regulatory focus on individual institution risk rather than systemic risk; opacity of positions in financial derivatives that produced externalities from individual firm failures; and runs on the unregulated banking sector that eventually threatened to bring down the entire financial sector. In emphasizing the role of regulatory failures, the paper provides a description of regulatory evolution in response to the panic of 1907 and the Great Depression, why the regulation put in place then was successful in addressing market failures, but how, over time, especially around the resolutions of Continental Illinois, Savings and Loans crisis and the Long-Term Capital Management, expectations of too-big-to-fail status got anchored. The paper proposes specific reforms to address the four market and regulatory failures we identify, and we conclude with some lessons for emerging markets.global financial crisis; LTCM; market failures; regulation; emerging markets

Measuring systemic risk

We present a simple model of systemic risk and show how each financial institution’s contribution to systemic risk can be measured and priced. An institution’s contribution, denoted systemic expected shortfall (SES), is its propensity to be undercapitalized when the system as a whole is undercapitalized, which increases in its leverage, volatility, correlation, and tail-dependence. Institutions internalize their externality if they are “taxed” based on their SES. Through several examples, we demonstrate empirically the ability of components of SES to predict emerging systemic risk during the nancial crisis of 2007-2009.Systemic risk ; Risk

Dislocation motion and instability

The Peach-Koehler expression for the stress generated by a single (non-planar) curvilinear dislocation is evaluated to calculate the dislocation self stress. This is combined with a law of motion to give the self-induced motion of a general dislocation curve. A stability analysis of a rectilinear, uniformly translating dislocation is then performed. The dislocation is found to be susceptible to a helical instability, with the maximum growth rate occurring when the dislocation is almost, but not exactly, pure screw. The non-linear evolution of the instability is determined numerically, and implications for slip band formation and non-Schmid behaviour in yielding discussed

A novel image compression algorithm for high resolution 3D reconstruction

This research presents a novel algorithm to compress high-resolution images for accurate structured light 3D reconstruction. Structured light images contain a pattern of light and shadows projected on the surface of the object, which are captured by the sensor at very high resolutions. Our algorithm is concerned with compressing such images to a high degree with minimum loss without adversely affecting 3D reconstruction. The Compression Algorithm starts with a single level discrete wavelet transform (DWT) for decomposing an image into four sub-bands. The sub-band LL is transformed by DCT yielding a DC-matrix and an AC-matrix. The Minimize-Matrix-Size Algorithm is used to compress the AC-matrix while a DWT is applied again to the DC-matrix resulting in LL2, HL2, LH2 and HH2 sub-bands. The LL2 sub-band is transformed by DCT, while the Minimize-Matrix-Size Algorithm is applied to the other sub-bands. The proposed algorithm has been tested with images of different sizes within a 3D reconstruction scenario. The algorithm is demonstrated to be more effective than JPEG2000 and JPEG concerning higher compression rates with equivalent perceived quality and the ability to more accurately reconstruct the 3D models

A novel 2D image compression algorithm based on two levels DWT and DCT transforms with enhanced minimize-matrix-size algorithm for high resolution structured light 3D surface reconstruction

Image compression techniques are widely used in 2D and 3D image and video sequences. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level Discrete Wavelet Transform (DWT) and a two level Discrete Cosine Transform (DCT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of 4 steps: 1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix respectively; 2) apply a second level DCT to the DC-Matrix to generate two arrays, namely nonzero-array and zero-array; 3) apply the Minimize-Matrix-Size (MMS) algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT; 4) apply arithmetic coding to the output of previous steps. A novel Fast-Match-Search (FMS) decompression algorithm is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined into one matrix followed by inverse two level DCT with two level DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D RMSE following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D

Veterinary Considerations for the Theoretical Resurrection of Extinct Species

The de-extinction of the dinosaur is a dubious possibility but its consideration brings forth some issues that are at least worthy of scientific discussion. In this review, we discuss two distinct issues that have implications for a de-extinct species such as a dinosaur: the ability, or lack thereof, to safely sedate a rare and potentially fractious animal capable of harming the veterinary staff tasked with its care; and, disease risks associated with a species that has been extinct for millions of years. To identify potential sedatives, comparative pharmacology will be needed to uncover the links between receptor pharmacology and the desired clinical outcomes of activating established alpha-2 adrenergic, opioid, and benzodiazepine receptors. Specific to disease control, it will be necessary to understand the unique susceptibility of the new species to current diseases as well as predicting their reservoir capacity for potential human and veterinary pandemic diseases. While the topics presented herein are not exhaustive, this review highlights some of the foremost research that should be conducted in order to serve the unique veterinary needs of a de-extinct species using the dinosaur as a paradigm. Addressing these issues should be considered if an intact dinosaur genome becomes available, regardless of the feasibility of dinosaur resurrection