Multiscaled Cross-Correlation Dynamics in Financial Time-Series

The cross correlation matrix between equities comprises multiple interactions between traders with varying strategies and time horizons. In this paper, we use the Maximum Overlap Discrete Wavelet Transform to calculate correlation matrices over different timescales and then explore the eigenvalue spectrum over sliding time windows. The dynamics of the eigenvalue spectrum at different times and scales provides insight into the interactions between the numerous constituents involved. Eigenvalue dynamics are examined for both medium and high-frequency equity returns, with the associated correlation structure shown to be dependent on both time and scale. Additionally, the Epps effect is established using this multivariate method and analyzed at longer scales than previously studied. A partition of the eigenvalue time-series demonstrates, at very short scales, the emergence of negative returns when the largest eigenvalue is greatest. Finally, a portfolio optimization shows the importance of timescale information in the context of risk management

Rotor-Rotor Interactions in the Design of Unmanned Aerial Systems

This dissertation investigates the impact of rotor-rotor interactions on small Unmanned Aerial System (UAS) design. This work explores the aerodynamic effects of two rotor configurations, the first being non-coplanar overlapping rotors, tandem-rotors, and the second being the semi-coaxial rotor configuration, which is an adaptation of the traditional coaxial rotor configuration. This work is motivated by three UAS, two of which, the Tetracopter and the Dodecacopter, are designed and developed as a part of the work presented in this dissertation. The Tetracopter and Dodecacopter are multi-agent vehicles that implement multiple layers of non-coplanar overlapping rotors. The goal of these two vehicles is to implement a design where a multi-agent UAS can have the structural rigidity to withstand carrying payloads, whether the payload is carried above or below the vehicle while being as efficient as a multi-agent aircraft with coplanar rotors. The goal of the Y6sC is to show that the semi-coaxial rotor configuration allows a vehicle to be more efficient in hover than a traditional coaxial rotor configuration and that the semi-coaxial rotor configuration grants the vehicle more maneuverability than a traditional coaxial rotor configuration. This dissertation can be separated into two halves; the first half begins with the presentation of a thrust stand fabricated to collect data on both rotor configurations. This half also discusses the methods used to conduct these thrust stand experiments, the methods used to analyze the data, and discussions about the results and their comparison to established theories that predict the performance of these rotor configurations. A rotor configuration performance estimation method that is based on the empirical data collected is also presented, and the accuracy of this estimation method is validated. This estimation method is then used to estimate the optimal design of the Tetracopter and Dodecacopter, which accounts for the vehicle's weight and the performance of the vehicle's rotors which may be impacted by rotor-rotor interactions. The latter half of this dissertation discusses the design of the Dodecacopter along with the methods used to flight test the vehicle. The data produced from the flight tests are discussed, and estimations of the degradation in the vehicle's performance due to the rotor-rotor interactions are presented and discussed. The dissertation concludes with a brief discussion on the design implications derived from the results of the work presented.Ph.D

Emergence of time-horizon invariant correlation structure in financial returns by subtraction of the market mode

We investigate the emergence of a structure in the correlation matrix of assets' returns as the time-horizon over which returns are computed increases from the minutes to the daily scale. We analyze data from different stock markets (New York, Paris, London, Milano) and with different methods. Result crucially depends on whether the data is restricted to the ``internal'' dynamics of the market, where the ``center of mass'' motion (the market mode) is removed or not. If the market mode is not removed, we find that the structure emerges, as the time-horizon increases, from splitting a single large cluster. In NYSE we find that when the market mode is removed, the structure of correlation at the daily scale is already well defined at the 5 minutes time-horizon, and this structure accounts for 80 % of the classification of stocks in economic sectors. Similar results, though less sharp, are found for the other markets. We also find that the structure of correlations in the overnight returns is markedly different from that of intraday activity.Comment: 12 pages, 17 figure

Very Isolated Early-Type Galaxies

We use the Karachentseva (1973) ``Catalogue of Very Isolated Galaxies'' to investigate a candidate list of >100 very isolated early-type galaxies. Broad-band imaging and low resolution spectroscopy are available for a large fraction of these candidates and result in a sample of 102 very isolated early-type galaxies, including 65 ellipticals and 37 S0 galaxies. Many of these systems are quite luminous and the resulting optical luminosity functions of the Es and early-types (E+S0s) show no statistical differences when compared to luminosity functions dominated by group and cluster galaxies. However, whereas S0s outnumber Es 4:1 in the CfA survey, isolated Es outnumber S0s by nearly 2:1. We conclude that very isolated elliptical galaxies show no evidence for a different formation and/or evolution process compared to Es formed in groups or clusters, but that most S0s are formed by a mechanism (e.g., gas stripping) that occurs only in groups and rich clusters. Our luminosity function results for ellipticals are consistent with very isolated ellipticals being formed by merger events, in which no companions remain. CHANDRA observations were proposed to test specifically the merger hypothesis for isolated ellipticals. However, this program has resulted in the observation of only one isolated early-type galaxy, the S0 KIG 284, which was not detected at a limit well below that expected for a remnant group of galaxies. Therefore, the hypothesis remains untested that very isolated elliptical galaxies are the remains of a compact group of galaxies which completely merged.Comment: 19 pages, 3 figures; AJ in pres

Wavelet multiscale analysis for hedge funds: scaling and strategies

The wide acceptance of Hedge Funds by Institutional Investors and Pension Funds has led to an explosive growth in assets under management. These investors are drawn to Hedge Funds due to the seemingly low correlation with traditional investments and the attractive returns. The correlations and market risk (the Beta in the Capital Asset Pricing Model) of Hedge Funds are generally calculated using monthly returns data, which may produce misleading results as Hedge Funds often hold illiquid exchange-traded securities or difficult to price over-the- counter securities. In this paper, the Maximum Overlap Discrete Wavelet Transform (MODWT) is applied to measure the scaling properties of Hedge Fund correlation and market risk with respect to the S&P 500. It is found that the level of correlation and market risk varies greatly according to the strategy studied and the time scale examined. Finally, the effects of scaling properties on the risk profile of a portfolio made up of Hedge Funds is studied using correlation matrices calculated over different time horizons

Local Extinction and Unintentional Rewilding of Bighorn Sheep (Ovis canadensis) on a Desert Island

Bighorn sheep ( Ovis canadensis) were not known to live on Tiburón Island, the largest island in the Gulf of California and Mexico, prior to the surprisingly successful introduction of 20 individuals as a conservation measure in 1975. Today, a stable island population of ∼500 sheep supports limited big game hunting and restocking of depleted areas on the Mexican mainland. We discovered fossil dung morphologically similar to that of bighorn sheep in a dung mat deposit from Mojet Cave, in the mountains of Tiburón Island. To determine the origin of this cave deposit we compared pellet shape to fecal pellets of other large mammals, and extracted DNA to sequence mitochondrial DNA fragments at the 12S ribosomal RNA and control regions. The fossil dung was 14C-dated to 1476-1632 calendar years before present and was confirmed as bighorn sheep by morphological and ancient DNA (aDNA) analysis. 12S sequences closely or exactly matched known bighorn sheep sequences; control region sequences exactly matched a haplotype described in desert bighorn sheep populations in southwest Arizona and southern California and showed subtle differentiation from the extant Tiburón population. Native desert bighorn sheep previously colonized this land-bridge island, most likely during the Pleistocene, when lower sea levels connected Tiburón to the mainland. They were extirpated sometime in the last ∼1500 years, probably due to inherent dynamics of isolated populations, prolonged drought, and (or) human overkill. The reintroduced population is vulnerable to similar extinction risks. The discovery presented here refutes conventional wisdom that bighorn sheep are not native to Tiburón Island, and establishes its recent introduction as an example of unintentional rewilding, defined here as the introduction of a species without knowledge that it was once native and has since gone locally extinct

Correlation based networks of equity returns sampled at different time horizons

We investigate the planar maximally filtered graphs of the portfolio of the 300 most capitalized stocks traded at the New York Stock Exchange during the time period 2001-2003. Topological properties such as the average length of shortest paths, the betweenness and the degree are computed on different planar maximally filtered graphs generated by sampling the returns at different time horizons ranging from 5 min up to one trading day. This analysis confirms that the selected stocks compose a hierarchical system progressively structuring as the sampling time horizon increases. Finally, a cluster formation, associated to economic sectors, is quantitatively investigated.Comment: 9 pages, 8 figure

Tick size and price diffusion

A tick size is the smallest increment of a security price. It is clear that at the shortest time scale on which individual orders are placed the tick size has a major role which affects where limit orders can be placed, the bid-ask spread, etc. This is the realm of market microstructure and there is a vast literature on the role of tick size on market microstructure. However, tick size can also affect price properties at longer time scales, and relatively less is known about the effect of tick size on the statistical properties of prices. The present paper is divided in two parts. In the first we review the effect of tick size change on the market microstructure and the diffusion properties of prices. The second part presents original results obtained by investigating the tick size changes occurring at the New York Stock Exchange (NYSE). We show that tick size change has three effects on price diffusion. First, as already shown in the literature, tick size affects price return distribution at an aggregate time scale. Second, reducing the tick size typically leads to an increase of volatility clustering. We give a possible mechanistic explanation for this effect, but clearly more investigation is needed to understand the origin of this relation. Third, we explicitly show that the ability of the subordination hypothesis in explaining fat tails of returns and volatility clustering is strongly dependent on tick size. While for large tick sizes the subordination hypothesis has significant explanatory power, for small tick sizes we show that subordination is not the main driver of these two important stylized facts of financial market.Comment: To be published in the "Proceedings of Econophys-Kolkata V International Workshop on "Econophysics of Order-driven Markets" March 9-13, 2010, The New Economic Windows series of Springer-Verlag Italia

Long-lived Memory T Lymphocyte Responses After Hantavirus Infection

Puumala virus (PUUV) is a hantavirus that causes hemorrhagic fever with renal syndrome (HFRS), which is an important public health problem in large parts of Europe. We examined the memory cytolytic T lymphocyte (CTL) responses in 13 Finnish individuals who had HFRS between 1984 and 1995. In seven of these donors, we detected virus-specific CTL responses against the PUUV nucleocapsid (N) protein after in vitro stimulation with PUUV. Six novel CD8+ CTL epitopes were defined on the N protein and were found to be restricted by various HLA alleles including A2, A28, B7, and B8. This is the first demonstration of PUUV-specific CTL responses in humans, and the first identification of CTL epitopes on PUUV. In addition, this study provides one of the few characterizations of a human antiviral memory T cell response, without the complicating issues of virus persistence or reinfection. Interferon (IFN)-γ ELISPOT analysis showed that memory CTL specific for these epitopes were present at high frequency in PUUV-immune individuals many years after acute infection in the absence of detectable viral RNA. The frequencies of PUUV-specific CTL were comparable to or exceeded those found in other viral systems including influenza, EBV and HIV, in which CTL responses may be boosted by periodic reinfection or virus persistence

Investigating word affect features and fusion of probabilistic predictions incorporating uncertainty in AVEC 2017

© 2017 Association for Computing Machinery. Predicting emotion intensity and severity of depression are both challenging and important problems within the broader field of affective computing. As part of the AVEC 2017, we developed a number of systems to accomplish these tasks. In particular, word affect features, which derive human affect ratings (e.g. arousal and valence) from transcripts, were investigated for predicting depression severity and liking, showing great promise. A simple system based on the word affect features achieved an RMSE of 6.02 on the test set, yielding a relative improvement of 13.6% over the baseline. For the emotion prediction sub-challenge, we investigated multimodal fusion, which incorporated a measure of uncertainty associated with each prediction within an Output-Associative fusion framework for arousal and valence prediction, whilst liking prediction systems mainly focused on text-based features. Our best emotion prediction systems provided significant relative improvements over the baseline on the test set of 39.5%, 17.6%, and 29.3% for arousal, valence, and liking. Of particular note is that consistent improvements were observed when incorporating prediction uncertainty across various system configurations for predicting arousal and valence, suggesting the importance of taking into consideration prediction uncertainty for fusion and more broadly the advantages of probabilistic predictions