A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
The paper characterizes contact 3-manifolds with closed Reeb orbits.
Study shows automorphisms of Markov surfaces share periodic points if they share a common iterate.
This paper reveals periodic behavior in neural network training with BN and weight decay.
This paper studies isotopies of periodic tangles in 3-manifolds using finite covers.
We give a sharp lower bound for the number of geometrically distinct contractible periodic orbits of dynamically convex Reeb flows on prequantizations of symplectic manifolds that are not aspherical. Several consequences of this result are obtained, like a new proof that every bumpy Finsler metric on carries at l…
Generative model captures repetitive industrial processes with varying durations and dynamics.
This study evaluates common trading models and finds moving averages crossovers outperforming others.
PQ-learning improves Q-learning by periodically updating target estimates.
Knot mosaic theory was introduced by Lomonaco and Kauffman in the paper on `Quantum knots and mosaics' to give a precise and workable definition of quantum knots, intended to represent an actual physical quantum system. A knot (m,n)-mosaic is an matrix whose entries are eleven mosaic tiles, represent…
This paper empirically analyses risk in the Euro relative to other currencies. Comparisons are made between a sub period encompassing the final transitional stage to full monetary union with a sub period prior to this. Stability in the face of speculative attack is examined using Extreme Value Theory to obtain estimate…
Study of common financial data patterns across stocks.
We analyse a period spanning 35 years of activity in the Sao Paulo Stock Exchange Index (IBOVESPA) and show that the Heston model with stochastic volatility is capable of explaining price fluctuations for time scales ranging from 5 minutes to 100 days with a single set of parameters. We also show that the Heston model …
A phenomenon of the financial log-periodicity is discussed and the characteristics that amplify its predictive potential are elaborated. The principal one is self-similarity that obeys across all the time scales. Furthermore the same preferred scaling factor appears to provide the most consistent description of the mar…
In this paper, we investigate the cooling-off effect (opposite to the magnet effect) from two aspects. Firstly, from the viewpoint of dynamics, we study the existence of the cooling-off effect by following the dynamical evolution of some financial variables over a period of time before the stock price hits its limit. S…
The study examines cross-border lending behavior from G7 countries, showing changes in driving factors after the 2008 financial crisis.
New algorithm uncovers causal relations in non-stationary time series.
This paper improves credit risk analysis by incorporating state-dependent recovery rates into a factor model.
For the first time, we apply the wavelet coherence methodology on biofuels (ethanol and biodiesel) and a wide range of related commodities (gasoline, diesel, crude oil, corn, wheat, soybeans, sugarcane and rapeseed oil). This way, we are able to investigate dynamics of correlations in time and across scales (frequencie…
The major study by Bordo and Helbing (2003) analyses the business cycle in Western economies 1881-2001. They examine four distinct periods in economic history, and conclude that there is a secular trend towards greater synchronisation for much of the 20th century. Their analysis, in common with the standard economic li…
We propose a novel methodology to define, analyze and forecast market states. In our approach market states are identified by a reference sparse precision matrix and a vector of expectation values. In our procedure, each multivariate observation is associated with a given market state accordingly to a minimization of a…
We have analyzed the Indices of Industrial Production (Seasonal Adjustment Index) for a long period of 240 months (January 1988 to December 2007) to develop a deeper understanding of the economic shocks. The angular frequencies estimated using the Hilbert transformation, are almost identical for the 16 industrial secto…
Deep RL algorithms can overfit to early experiences, leading to poor performance.
In this paper we provide a general solution for the dividend discount model in order to compute the intrinsic value of a common stock that allows for multiple stage growth rates of any predetermined number of periods. A mathematical proof is provided for the suggested general solution. A numerical application is also p…
Policy gradient methods with aggregated states can achieve better performance than approximate policy iteration.
Study confirms financial bubbles' common patterns in isolated markets.
Paper uses LSTM to predict inflation, finds it performs well over long periods.
New PFPPs based on rank-dependent utility for better performance control.
Machine learning detects epilepsy development from EEG before seizures.
SVM algorithm extracts digits from audio CAPTCHAs.
We tested 45 indices and common stocks traded in the South African stock market for the possible existence of a bubble over the period from Jan. 2003 to May 2006. A bubble is defined by a faster-than-exponential acceleration with significant log-periodic oscillations. The faster-than-exponential acceleration characteri…
Paper proposes SERT model for US stock pricing, outperforming standard models during market shocks.
Within the context of risk integration, we introduce in risk measurement stochastic holding period (SHP) models. This is done in order to obtain a `liquidity-adjusted risk measure' characterized by the absence of a fixed time horizon. The underlying assumption is that - due to changes on market liquidity conditions - o…
Paper analyzes electricity price and demand TSs using decomposition to detect cyber-attacks.
This work uses QPGPs to improve ILC performance in repetitive tasks.
Paper proposes a new model for multivariate risk measures using Wasserstein barycenters.
Meta-learning approach for spatial-temporal prediction across cities.
Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders' short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of pri…
We analyze cross-correlations between price fluctuations of different stocks using methods of random matrix theory (RMT). Using two large databases, we calculate cross-correlation matrices C of returns constructed from (i) 30-min returns of 1000 US stocks for the 2-yr period 1994--95 (ii) 30-min returns of 881 US stock…
Pairs trading strategy fails to outperform market benchmarks, but performs well during bear markets.
Paper uses RL to optimize daily step distribution for better health biomarkers.
This study examined how the correlation and network structure of 30 global indices and 145 local Korean indices belonging to the KOSPI 200 have changed during the 13-year period, 2000-2012. The correlations among the indices were calculated. The results showed that although the average correlations of the global indice…
Paper tests for time-varying entropy in stock prices, finding periods of inefficiency.
We consider the forecast aggregation problem in repeated settings, where the forecasts are done on a binary event. At each period multiple experts provide forecasts about an event. The goal of the aggregator is to aggregate those forecasts into a subjective accurate forecast. We assume that experts are Bayesian; namely…
Study examines financial market structure changes during the COVID-19 crash using a novel MI approach.
Performance of investment managers are evaluated in comparison with benchmarks, such as financial indices. Due to the operational constraint that most professional databases do not track the change of constitution of benchmark portfolios, standard tests of performance suffer from the "look-ahead benchmark bias," when t…
The paper proves periodic projections of alternating knots using Flyping theorem.
The paper finds linked periodic orbits in disc homeomorphisms using braids.
Paper proposes a robust framework for detecting multiple periodic components in time series.