Privacy-Preserving Methods for Sharing Financial Risk Exposures

Unlike other industries in which intellectual property is patentable, the financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the public. We develop methods for sharing and aggregating such risk exposures that protect the privacy of all parties involved and without the need for a trusted third party. Our approach employs secure multi-party computation techniques from cryptography in which multiple parties are able to compute joint functions without revealing their individual inputs. In our framework, individual financial institutions evaluate a protocol on their proprietary data which cannot be inverted, leading to secure computations of real-valued statistics such a concentration indexes, pairwise correlations, and other single- and multi-point statistics. The proposed protocols are computationally tractable on realistic sample sizes. Potential financial applications include: the construction of privacy-preserving real-time indexes of bank capital and leverage ratios; the monitoring of delegated portfolio investments; financial audits; and the publication of new indexes of proprietary trading strategies

WARNING: Physics Envy May Be Hazardous To Your Wealth!

The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems - and financial markets in particular - that are as predictive as those in physics. While this perspective has led to a number of important breakthroughs in economics, "physics envy" has also created a false sense of mathematical precision in some cases. We speculate on the origins of physics envy, and then describe an alternate perspective of economic behavior based on a new taxonomy of uncertainty. We illustrate the relevance of this taxonomy with two concrete examples: the classical harmonic oscillator with some new twists that make physics look more like economics, and a quantitative equity market-neutral strategy. We conclude by offering a new interpretation of tail events, proposing an "uncertainty checklist" with which our taxonomy can be implemented, and considering the role that quants played in the current financial crisis.Comment: v3 adds 2 reference

Associations between Tumor Vascularity, Vascular Endothelial Growth Factor Expression and PET/MRI Radiomic Signatures in Primary Clear-Cell–Renal-Cell-Carcinoma: Proof-of-Concept Study

Studies have shown that tumor angiogenesis is an essential process for tumor growth, proliferation and metastasis. Also, tumor angiogenesis is an important prognostic factor of clear cell renal cell carcinoma (ccRCC), as well as a factor in guiding treatment with antiangiogenic agents. Here, we attempted to find the associations between tumor angiogenesis and radiomic imaging features from PET/MRI. Specifically, sparse canonical correlation analysis was conducted on 3 feature datasets (i.e., radiomic imaging features, tumor microvascular density (MVD), and vascular endothelial growth factor (VEGF) expression) from 9 patients with primary ccRCC. In order to overcome the potential bias of intratumoral heterogeneity of angiogenesis, this study investigated the relationship between regional expressions of angiogenesis and VEGF, and localized radiomic features from different parts within the tumors. Our study highlighted the significant strong correlations between radiomic features and MVD, and also demonstrated that the spatiotemporal features extracted from DCE-MRI provided stronger radiomic correlation to MVD than the textural features extracted from Dixon sequences and FDG PET. Furthermore, PET/MRI, which takes advantage of the combined functional and structural information, had higher radiomics correlation to MVD than solely utilizing PET or MRI alone

Alternate Metabolic Programs Define Regional Variation of Relevant Biological Features in Renal Cell Carcinoma Progression

ccRCC has recently been redefined as a highly heterogeneous disease. In addition to genetic heterogeneity, the tumor displays risk variability for developing metastatic disease, therefore underscoring the urgent need for tissue-based prognostic strategies applicable to the clinical setting. We’ve recently employed the novel positron emission tomography/magnetic resonance (PET/MR) image modality to enrich our understanding of how tumor heterogeneity can relate to gene expression and tumor biology to assist in defining individualized treatment plans

Chemical Genetics Reveals Bacterial and Host Cell Functions Critical for Type IV Effector Translocation by Legionella pneumophila

Delivery of effector proteins is a process widely used by bacterial pathogens to subvert host cell functions and cause disease. Effector delivery is achieved by elaborate injection devices and can often be triggered by environmental stimuli. However, effector export by the L. pneumophila Icm/Dot Type IVB secretion system cannot be detected until the bacterium encounters a target host cell. We used chemical genetics, a perturbation strategy that utilizes small molecule inhibitors, to determine the mechanisms critical for L. pneumophila Icm/Dot activity. From a collection of more than 2,500 annotated molecules we identified specific inhibitors of effector translocation. We found that L. pneumophila effector translocation in macrophages requires host cell factors known to be involved in phagocytosis such as phosphoinositide 3-kinases, actin and tubulin. Moreover, we found that L. pneumophila phagocytosis and effector translocation also specifically require the receptor protein tyrosine phosphate phosphatases CD45 and CD148. We further show that phagocytosis is required to trigger effector delivery unless intimate contact between the bacteria and the host is artificially generated. In addition, real-time analysis of effector translocation suggests that effector export is rate-limited by phagocytosis. We propose a model in which L. pneumophila utilizes phagocytosis to initiate an intimate contact event required for the translocation of pre-synthesized effector molecules. We discuss the need for host cell participation in the initial step of the infection and its implications in the L. pneumophila lifestyle. Chemical genetic screening provides a novel approach to probe the host cell functions and factors involved in host–pathogen interactions

Interaction of microtubules and actin during the post-fusion phase of exocytosis

Exocytosis is the intracellular trafficking step where a secretory vesicle fuses with the plasma membrane to release vesicle content. Actin and microtubules both play a role in exocytosis; however, their interplay is not understood. Here we study the interaction of actin and microtubules during exocytosis in lung alveolar type II (ATII) cells that secrete surfactant from large secretory vesicles. Surfactant extrusion is facilitated by an actin coat that forms on the vesicle shortly after fusion pore opening. Actin coat compression allows hydrophobic surfactant to be released from the vesicle. We show that microtubules are localized close to actin coats and stay close to the coats during their compression. Inhibition of microtubule polymerization by colchicine and nocodazole affected the kinetics of actin coat formation and the extent of actin polymerisation on fused vesicles. In addition, microtubule and actin cross-linking protein IQGAP1 localized to fused secretory vesicles and IQGAP1 silencing influenced actin polymerisation after vesicle fusion. This study demonstrates that microtubules can influence actin coat formation and actin polymerization on secretory vesicles during exocytosis

Losing Track of the Asset Markets: The Case of Housing and Stock

This paper revisits the relationships among macroeconomic variables and asset returns. Based on recent developments in econometrics, we categorize competing models of asset returns into different "Equivalence Predictive Power Classes" (EPPC). During the pre-crisis period (1975-2005), some models that emphasize imperfect capital markets outperform an AR(1) for the forecast of housing returns. After 2006, a model that includes both an external finance premium (EFP) and the TED spread "learns and adjusts" faster than competing models. Models that encompass GDP experience a significant decay in predictive power. We also demonstrate that a simulation-based approach is complementary to the EPPC methodology