Frontrunning the signals: As arbitrage between sophisticates.
Ontology highlight
ABSTRACT:
SUBMITTER: Akerlof GA
PROVIDER: S-EPMC8020781 | biostudies-literature | 2021 Mar
REPOSITORIES: biostudies-literature
Publications
Frontrunning the signals: As arbitrage between sophisticates.
Akerlof George A GA Tong Hui H
Proceedings of the National Academy of Sciences of the United States of America 20210301 13
This paper presents a model in which some sophisticated investors do not wait for receipt of a signal before purchasing an asset. Its critical innovation is an arbitrage equation for frontrunning. Some sophisticates who will receive information in the next period arbitrage against similar sophisticates who will act on that information in that next period when the information is received. The costs of such frontrunning are borne totally by unsophisticated traders-with no gain or loss to sophistic ...[more]
Similar Datasets
Project description:In this article, we analyse optimal statistical arbitrage strategies from stochastic control and optimisation problems for multiple co-integrated stocks with eigenportfolios being factors. Optimal portfolio weights are found by solving a Hamilton-Jacobi-Bellman (HJB) partial differential equation, which we solve for both an unconstrained portfolio and a portfolio constrained to be market neutral. Our analyses demonstrate sufficient conditions on the model parameters to ensure long-term stability of the HJB solutions and stable growth rates for the optimal portfolios. To gauge how these optimal portfolios behave in practice, we perform backtests on historical stock prices of the S&P 500 constituents from year 2000 through year 2021. These backtests suggest three key conclusions: that the proposed co-integrated model with eigenportfolios being factors can generate a large number of co-integrated stocks over a long time horizon, that the optimal portfolios are sensitive to parameter estimation, and that the statistical arbitrage strategies are more profitable in periods when overall market volatilities are high.Supplementary informationThe online version contains supplementary material available at 10.1007/s00245-022-09838-3.
| S-EPMC9171503 | biostudies-literature
Project description:Bitcoin market's efficiency and liquidity questions are being comprehensively analyzed in scientific literature. This dataset serves academics for deeper analysis of these topics as well as it gives relevant information for spotting and evaluating risks in the market. Moreover, practitioners can benefit from the dataset and use it to identify patterns in the market, discover potential earning capabilities, and create effective arbitrage trading strategies. This is the first publicly available dataset that provides unique arbitrage data about pairs of cryptocurrency exchanges. The raw dataset was received by the Bitlocus LT, UAB. Using dplyr, reshape2, plyr packages in R we transformed dataset to show the amount of arbitrage which could be earned in 13 different cryptocurrency exchanges from 2019-01-01 to 2020-04-01. We used this dataset to create matrices for each day from 2019-01-01 to 2020-04-01 in order to perform network analysis on Bitcoin arbitrage opportunities (Bruzgė and Šapkauskienė [1]). However, this dataset is beneficial for other purposes such as the evaluation of market's seasonality and day of week effects. The dataset provides values in high-frequency intervals but it is possible to convert data to a suitable data format depending on the research question.
| S-EPMC8717421 | biostudies-literature
Project description:Arbitrage trading is a common quantitative trading strategy that leverages the long-term cointegration relationships between multiple related assets to conduct spread trading for profit. Specifically, when the cointegration relationship between two or more related series holds, it utilizes the stability and mean-reverting characteristics of their cointegration relationship for spread trading. However, in real quantitative trading, determining the cointegration relationship based on the Engle-Granger two-step method imposes stringent conditions for the cointegration to hold, which can easily be disrupted by price fluctuations or trend characteristics presented by the linear combination, leading to the failure of the arbitrage strategy and significant losses. To address this issue, this article proposes an optimized strategy based on long-short-term memory (LSTM), termed Dynamic-LSTM Arb (DLA), which can classify the trend movements of linear combinations between multiple assets. It assists the Engle-Granger two-step method in determining cointegration relationships when clear upward or downward non-stationary trend characteristics emerge, avoiding frequent strategy switches that lead to losses and the invalidation of arbitrage strategies due to obvious trend characteristics. Additionally, in mean-reversion arbitrage trading, to determine the optimal trading boundary, we have designed an optimized algorithm that dynamically updates the trading boundaries. Training results indicate that our proposed optimization model can successfully filter out unprofitable trades. Through trading tests on a backtesting platform, a theoretical return of 23% was achieved over a 10-day futures trading period at a 1-min level, significantly outperforming the benchmark strategy and the returns of the CSI 300 Index during the same period.
| S-EPMC11323094 | biostudies-literature
Project description:Foreign exchange rates movements exhibit significant cross-correlations even on very short time-scales. The effect of these statistical relationships become evident during extreme market events, such as flash crashes. Although a deep understanding of cross-currency correlations would be clearly beneficial for conceiving more stable and safer foreign exchange markets, the microscopic origins of these interdependencies have not been extensively investigated. This paper introduces an agent-based model which describes the emergence of cross-currency correlations from the interactions between market makers and an arbitrager. The model qualitatively replicates the time-scale vs. cross-correlation diagrams observed in real trading data, suggesting that triangular arbitrage plays a primary role in the entanglement of the dynamics of different foreign exchange rates. Furthermore, the model shows how the features of the cross-correlation function between two foreign exchange rates, such as its sign and value, emerge from the interplay between triangular arbitrage and trend-following strategies. In particular, the interaction of these trading strategies favors certain combinations of price trend signs across markets, thus altering the probability of observing two foreign exchange rates drifting in the same or opposite direction. Ultimately, this entangles the dynamics of foreign exchange rate pairs, leading to cross-correlation functions that resemble those observed in real trading data.
| S-EPMC7313750 | biostudies-literature
Project description:Although motor actions can profoundly affect the perceptual interpretation of sensory inputs, it is not known whether the combination of sensory and movement signals occurs only for sensory surfaces undergoing movement or whether it is a more general phenomenon. In the haptic modality, the independent movement of multiple sensory surfaces poses a challenge to the nervous system when combining the tactile and kinesthetic signals into a coherent percept. When exploring a stationary object, the tactile and kinesthetic signals come from the same hand. Here we probe the internal structure of haptic combination by directing the two signal streams to separate hands: one hand moves but receives no tactile stimulation, while the other hand feels the consequences of the first hand's movement but remains still. We find that both discrete and continuous tactile and kinesthetic signals are combined as if they came from the same hand. This combination proceeds by direct coupling or transfer of the kinesthetic signal from the moving to the feeling hand, rather than assuming the displacement of a mediating object. The combination of signals is due to perception rather than inference, because a small temporal offset between the signals significantly degrades performance. These results suggest that the brain simplifies the complex coordinate transformation task of remapping sensory inputs to take into account the movements of multiple body parts in haptic perception, and they show that the effects of action are not limited to moving sensors.
| S-EPMC4299183 | biostudies-other
Project description:Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.
| S-EPMC5720749 | biostudies-literature
Project description:The physics of active biological matter, such as bacterial colonies and bird flocks, exhibiting interesting self-organizing dynamical behavior has gained considerable importance in recent years. Current theoretical advances use techniques from hydrodynamics, kinetic theory, and non-equilibrium statistical physics. However, for biological agents, these approaches do not seem to recognize explicitly their critical feature: namely, the role of survival-driven purpose and the attendant pursuit of maximum utility. Here, we propose a game-theoretic framework, statistical teleodynamics, that demonstrates that the bird-like agents self-organize dynamically into flocks to approach a stable arbitrage equilibriumof equal effective utilities. This is essentially the invisible handmechanism of Adam Smith's in an ecological context. What we demonstrate is for ideal systems, similar to the ideal gas or Ising model in thermodynamics. The next steps would involve examining and learning how real swarms behave compared to their ideal versions. Our theory is not limited to just birds flocking but can be adapted for the self-organizing dynamics of other active matter systems.
| S-EPMC10378221 | biostudies-literature
Project description:Vestibular inputs are constantly processed and integrated with signals from other sensory modalities, such as vision and touch. The multiply-connected nature of vestibular cortical anatomy led us to investigate whether vestibular signals could participate in a multi-way interaction with visual and somatosensory perception. We used signal detection methods to identify whether vestibular stimulation might interact with both visual and somatosensory events in a detection task. Participants were instructed to detect near-threshold somatosensory stimuli that were delivered to the left index finger in one half of experimental trials. A visual signal occurred close to the finger in half of the trials, independent of somatosensory stimuli. A novel Near infrared caloric vestibular stimulus (NirCVS) was used to artificially activate the vestibular organs. Sham stimulations were used to control for non-specific effects of NirCVS. We found that both visual and vestibular events increased somatosensory sensitivity. Critically, we found no evidence for supra-additive multisensory enhancement when both visual and vestibular signals were administered together: in fact, we found a trend towards sub-additive interaction. The results are compatible with a vestibular role in somatosensory gain regulation.
| S-EPMC4395320 | biostudies-literature
Project description:Naturally occurring signals in audition and touch can be complex and marked by temporal variations in frequency and amplitude. Auditory frequency sweep processing has been studied extensively; however, much less is known about sweep processing in touch because studies have primarily focused on the perception of simple sinusoidal vibrations. Given the extensive interactions between audition and touch in the frequency processing of pure tone signals, we reasoned that these senses might also interact in the processing of higher-order frequency representations like sweeps. In a series of psychophysical experiments, we characterized the influence of auditory distractors on the ability of participants to discriminate tactile frequency sweeps. Auditory frequency sweeps systematically biased the tactile perception of sweep direction. Importantly, auditory cues exerted little influence on tactile sweep direction perception when the sounds and vibrations occupied different absolute frequency ranges or when the sounds consisted of intensity sweeps. Thus, audition and touch interact in frequency sweep perception in a frequency- and feature-specific manner. Our results demonstrate that audio-tactile interactions are not constrained to the processing of simple sinusoids. Because higher-order frequency representations may be synthesized from simpler representations, our findings imply that multisensory interactions in the temporal frequency domain span multiple hierarchical levels in sensory processing. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
| S-EPMC6472995 | biostudies-literature
Project description:Technological advances now allow us to record from large populations of neurons across multiple brain areas. These recordings may illuminate how communication between areas contributes to brain function, yet a substantial barrier remains: how do we disentangle the concurrent, bidirectional flow of signals between populations of neurons? We propose here a dimensionality reduction framework, delayed latents across groups (DLAG), that disentangles signals relayed in each direction, identifies how these signals are represented by each population and characterizes how they evolve within and across trials. We demonstrate that DLAG performs well on synthetic datasets similar in scale to current neurophysiological recordings. Then we study simultaneously recorded populations in primate visual areas V1 and V2, where DLAG reveals signatures of bidirectional yet selective communication. Our framework lays a foundation for dissecting the intricate flow of signals across populations of neurons, and how this signalling contributes to cortical computation.
| S-EPMC11442031 | biostudies-literature