Currency volatility shocks predict lower excess returns, and buying weak transmitters outperforms selling strong ones.
problem Predicting currency returns using volatility shocks.
method Constructed a dynamic, directed network of volatility connections using option-implied volatilities.
result Currencies that transmit more volatility shocks earn lower excess returns.
Oil markets profoundly influence world economies through determination of prices of energy and transports. Using novel methodology devised in frequency domain, we study the information transmission mechanisms in oil-based commodity markets. Taking crude oil as a supply-side benchmark and heating oil and gasoline as dem…
Asymmetries in volatility spillovers are highly relevant to risk valuation and portfolio diversification strategies in financial markets. Yet, the large literature studying information transmission mechanisms ignores the fact that bad and good volatility may spill over at different magnitudes. This paper fills this gap…
Mutual info trees show higher risk in Brazilian equity network during transition.
problem Identifying nonlinear dependencies in Brazilian equity network.
method Used mutual information minimum spanning trees to compare with linear correlation.
result Mutual info trees indicate higher risk and power law tail in volatility transmission.
Study reveals how investor flows impact stock prices, especially during herding episodes.
problem Understanding how information transmits through prices and why it breaks down.
method Combining regularized deconvolution with Hawkes process analysis.
result Institutional price impact deteriorates sharply during herding episodes in small-cap stocks, while large-cap stocks maintain resilience.
In this paper, we analyse the South African implied volatility in various setting. We assess the information content in SAVI implied volatility using daily markets data. Our empirical application is focused on the FTSE/JSE Top 40 index and we emphasize our models performance in distinct sub-periods. Our results are com…
We detect and quantify asymmetries in volatility spillovers using the realized semivariances of petroleum commodities: crude oil, gasoline, and heating oil. During the 1987--2014 period we document increasing spillovers from volatility among petroleum commodities that substantially change after the 2008 financial crisi…
Study finds Binance's tether-margined contracts significantly impact bitcoin volatility.
problem Understanding volatility transmission in the crypto market, especially through Binance.
method Analyzing high-frequency realised volatility dynamics and spillovers in bitcoin market pairs.
result Binance's tether-margined contracts are the primary source of volatility and transmit strong flows.
Study examines dependence of extreme electricity prices in Australian markets.
problem Understanding and managing risks of extreme price outcomes in Australian electricity markets.
method Examined extremal dependence using extremograms for 5-minute and 30-minute price data.
result Persistence and dependence of extreme prices are influenced by market structure and renewable energy share.
Study reveals risk transmission channels among Chinese sectors.
problem Understanding risk transmission within Chinese economic sectors.
method Volatility spillovers analysis using VAR model and rolling window approach.
result 17 sectors are risk transmitters and 11 are risk takers.
Assuming that price of the underlying stock is moving in range bound, the Black-Scholes formula for options pricing supports a separation of variables. The resulting time-independent equation is solved employing different behavior of the option price function and three significant results are deduced. The first is the …
New method learns transmission matrices from input-output data.
problem Recovering transmission matrices from input-output data in random media.
method Statistical mechanical formulation and pseudolikelihood maximization.
result Inference protocols can learn transmission couplings.
Changes in collateralization have been implicated in significant default (or near-default) events during the financial crisis, most notably with AIG. We have developed a framework for quantifying this effect based on moving between Merton-type and Black-Cox-type structural default models. Our framework leads to a singl…
This paper uses deep reinforcement learning to automate electric transmission voltage control.
problem Automating voltage control in electric transmission systems.
method Deep reinforcement learning (DRL) applied to voltage control, with a novel DQN modification.
result DRL can automate voltage control at scale, but more research is needed.
New method shows cultural transmission improves language compositionality.
problem How cultural transmission affects language emergence and compositionality.
method Introduced cultural evolutionary dynamics into language emergence by periodically replacing agents in a population.
result Languages emerge with better compositional generalization due to implicit cultural transmission.
Researchers use statistical methods to infer transmission matrices in complex media.
problem Comprehending and exploiting photon scattering through disordered media.
method Pseudolikelihood decimation to learn the coupling matrix via random sampling.
result Transmission matrices can be inferred and used like normal optical elements.
New framework analyzes belief evolution in social networks.
problem Analyzing belief evolution in social networks.
method Proposes a new theoretical framework using Markov chain theory for horizontal and vertical transmission.
result Homophily-based networks do not converge to a single set of beliefs.
Optimizes data transmission timing to minimize user information age.
problem Minimizing long-term average age of information in multi-user networks.
method Reinforcement learning applied to scheduling decisions without channel state information.
result RL approach effectively reduces AoI compared to traditional ARQ and HARQ.
This paper considers a transmission control problem in network-coded two-way relay channels (NC-TWRC), where the relay buffers random symbol arrivals from two users, and the channels are assumed to be fading. The problem is modeled by a discounted infinite horizon Markov decision process (MDP). The objective is to find…
This work interprets GELU and related activations via a first-order loss function.
problem Understanding and optimizing activation functions in neural networks.
method Complementary interpretation using the Gaussian first-order loss function.
result Calibrated or learned uniform-threshold gates are competitive and often outperform GELU, ReLU, and SiLU/Swish.
A deep learning approach for efficient power control in wireless video transmissions.
problem Optimizing power control for real-time wireless video transmissions with quality constraints.
method Proposes a learning-based approach using a deep neural network to solve the non-convex power control problem.
result The deep neural network can quickly provide optimal power levels for given channel conditions.
Anomaly detection identifies unusual malaria transmission patterns in Ghana.
problem Identifying atypical malaria transmission patterns in Ghana's spatiotemporal surveillance data.
method Consensus-based anomaly detection framework applied to monthly malaria surveillance data.
result High-burden areas are not necessarily those with the most frequent anomalous transmission.
In this note, we present some interesting observations on the Schiffer's conjecture, interior transmission eigenvalue problem and their connections to singular and nonsingular invisibility cloaking problems of acoustic waves.
Transmission imaging, as an important imaging technique widely used in astronomy, medical diagnosis, and biology science, has been shown in [49] quite different from reflection imaging used in our everyday life. Understanding the structures of images (the prior information) is important for designing, testing, and choo…
Traders and investors involved in an option contract having the underlying stock in range bound are likely to lose their initial investment. Timing in buying an option contract is of capital importance. In a recent article [1] the hypothesis of range bound market is used in conjunction to Black-Scholes equation to find…
DeepJSCC-f uses feedback to improve image transmission quality.
problem Improve image transmission quality in feedback channels.
method Autoencoder-based joint source-channel coding (DeepJSCC-f) exploiting feedback.
result Improves reconstruction quality for fixed-length or variable-length transmission.
Mathematical framework for cooperative communication explains belief transmission.
problem Lack of understanding why cooperation enables effective belief transmission.
method Connection to optimal transport theory, deriving prior models, statistical interpretations, proofs of robustness and instability.
result Cooperative communication provably enables effective, robust belief transmission.
In agreement with the recent research findings in the econophysics, we propose that the nonlinear dynamic chaos can be generated by the turbulent capital flows in both the quantitative easing transmission channels and the transaction networks channels, when there are the laminar turbulent capital flows transitions in t…
Deep JSCC maps images directly to channel symbols for wireless transmission.
problem Efficient image transmission in noisy wireless channels.
method Joint source and channel coding using CNNs trained jointly.
result Deep JSCC outperforms traditional JPEG/2000 + channel codes at low SNR.
Study forecasts cholera outbreaks in Malawi using dynamic models.
problem Cholera transmission forecasting in developing countries.
method Qualitative dynamics, Monte Carlo Markov Chain, sensitivity analysis, machine learning.
result Enhanced cholera forecasting models improve future trends prediction.
Model for cross-border markets with limited transmission capacities.
problem Limited transmission capacities between two countries' markets.
method Developed a regime-switching process model with high-frequency approximation.
result Analytic tractability allows computation of key market quantities.
Novel method detects faults in helicopter transmissions using healthy data only.
problem Detecting faults in rare events in helicopter transmissions.
method Probabilistic anomaly detection using Bayesian measures.
result Method achieves competitive detection performance in real-world and benchmark applications.
A new method for energy-efficient file delivery in small cell networks.
problem Efficient resource management in femto-caching with time-variant statistical properties.
method Formulates a resource allocation problem as a stochastic knapsack problem and a multi-armed bandit problem, developing solutions for each.
result The proposed method maximizes the accumulated utility over the horizon, especially suitable for networks with time-variant statistical properties.
Study investigates FL performance over a noisy downlink, showing analog approach outperforms digital.
problem Impact of bandwidth-limited downlink on federated learning performance.
method Modelled downlink and uplink channels; proposed digital and analog downlink approaches; analyzed convergence behavior.
result Analog downlink approach provides significant improvement over digital approach, especially with biased data distribution.
This paper proposes a submodular load clustering method for transmission-level load areas.
problem Traditional load analysis challenges with new electricity usage patterns.
method Robust Principal Component Analysis (R-PCA) and submodular cluster center selection.
result The proposed method efficiently clusters load areas and demonstrates effectiveness in PJM load data.
Stochastic models analyze traffic network performance.
problem Evaluate traffic system performance.
method Stochastic cell transmission models, preference functionals, Gaussian process regression.
result Illustrated in two case studies.
New framework for distributed nonparametric estimation under slow communication.
problem Efficiently estimate nonparametric models across multiple nodes with limited communication.
method Developed a general framework for nonparametric estimation under communication constraints.
result Derived minimax lower and upper bounds for various models.
Spreading processes are often modelled as a stochastic dynamics occurring on top of a given network with edge weights corresponding to the transmission probabilities. Knowledge of veracious transmission probabilities is essential for prediction, optimization, and control of diffusion dynamics. Unfortunately, in most ca…
This study examines financial spillovers in critical minerals investing, revealing ESG scores impact and role of energy and carbon markets.
problem Investment risks in critical minerals and their spillovers to energy and carbon markets.
method Time-varying parameter vector autoregression (TVP-VAR) model, split data into pre- and post-COVID-19 samples.
result ESG scores significantly impact spillovers, and specific ETFs act as net givers or receivers of volatility.
Modeling infection hotspots to quantify effects of contact tracing and testing.
problem Capturing the role of infection hotspots in disease transmission.
method Temporal point process modeling framework to represent visits and disease transmission.
result Estimation of transmission rates at sites and households using Bayesian optimization.
Reconstructs power grid dynamics from PMU measurements.
problem Reconstructing dynamic state matrix of power transmission grids.
method Maximum likelihood based convex estimators adapting to prior information.
result Fully data-driven method that works in near real-time.
This paper determines gear geometries for specific transmission functions.
problem Determining the geometry of noncircular gears for a given transmission function.
method Complex algebra and an external product method are used to derive tooth geometries.
result Effective algorithm for calculating tooth geometries with minimal numerical integrations.
Optimizes variational autoencoder for detecting missing data in Mars rover transmissions.
problem Detecting missing data in Mars rover transmissions to prevent volume loss and corruption.
method Applies derivative-free optimization to tune variational autoencoder.
result Improves variational autoencoder's ability to detect missing data, aiding GDSA team.
Reproductive success and survival are influenced by wealth in human populations. Wealth is transmitted to offsprings and strategies of transmission vary over time and among populations, the main variation being how equally wealth is transmitted to children. Here we propose a model where we simulate both the dynamics of…
New method reconstructs strain and lattice spacing from neutron data.
problem Jointly reconstructing strain and lattice spacing from neutron data.
method Solves non-linear problem ensuring strain field equilibrium with knowledge of boundary conditions.
result Demonstrates ability to jointly reconstruct strain and lattice spacing from simulated data.
Study examines robustness of NPI effectiveness models against COVID-19.
problem How do NPI effectiveness estimates vary with model assumptions and data?
method Investigated 2 NPI effectiveness models and 6 variants, evaluated robustness to unseen countries, parameters, and data.
result NPI effectiveness estimates are remarkably robust to different variables.
Multiplex Network Hawkes model for systemic risk measurement
problem Investigate how contagion in financial networks is affected by different transmission channels
method Multiplex Network Hawkes model
result Sparse contagion pathways, with systemic-risk transmission concentrated in outward flows from a small number of influential institutions
New pricing framework allocates costs of operating reserves and transmission.
problem Allocating costs of operating reserves and transmission efficiently.
method Causation-based framework using contingency-constrained scheduling models.
result More comprehensive and efficient cost-reflective market operations.