arXiv research

We point out a stunning time asymmetry in the short time cross correlations between intra-day and overnight volatilities (absolute values of log-returns of stock prices). While overnight volatility is significantly (and positively) correlated with the intra-day volatility during the \textit{following} day (allowing thu…

We decompose, within an ARCH framework, the daily volatility of stocks into overnight and intra-day contributions. We find, as perhaps expected, that the overnight and intra-day returns behave completely differently. For example, while past intra-day returns affect equally the future intra-day and overnight volatilitie…

New study finds day-of-the-week effects in stock market returns using multifractal analysis.

Study local sensitivity of HDD and CDD temperature derivatives prices.

Study examines crypto-backed stable derivatives in DeFi, focusing on DAI.

This paper questions some current ideas about the practice of specific capital market operations - the so-called day trading operations. The text advanced from theoretical propositions to a detailed analysis of the study entitled "Is it possible to live by day-trading?" (CHAGUE and GIOVANNETTI, 2019), to which it offer…

We select the $n$ stocks traded in the New York Stock Exchange and we form a statistical ensemble of daily stock returns for each of the $k$ trading days of our database from the stock price time series. We study the ensemble return distribution for each trading day and we find that the symmetry properties of the ensem…

In this paper, we study the dynamics of absolute return, trading volume and bid-ask spread after the trading halts using high-frequency data from the Shanghai Stock Exchange. We deal with all three types of trading halts, namely intraday halts, one-day halts and inter-day halts, of 203 stocks in Shanghai Stock Exchange…

Study analyzes Airbnb lead-time distributions for Nights Booked and Gross Booking Value, finding divergent shapes and tail behavior.

The daily volume of transaction on the New York Stock Exchange and its day-to-day fluctuations are analysed with respect to power-law tails as well long-term trends. We also model the transition to a Gaussian distribution for longer time intervals, like months instead of days.

Study provides long-term EMG data for multi-day biometric authentication.

Improves stock market predictions on Election Day.

In this paper we perform a statistical analysis over the returns and relative prices of the CAC $40$ and the S\&P $500$ with the purpose of analyzing the intra-day seasonalities of single and cross-sectional stock dynamics. In order to do that, we characterized the dynamics of a stock (or a set of stocks) by the evolut…

Paper predicts cryptocurrency bull and bear phases using Bitcoin's moving averages.

DAIS minimizes symmetrized KL divergence between initial and target distributions.

This paper examines the intra-day seasonality of transacted limit and market orders in the DEM/USD foreign exchange market. Empirical analysis of completed transactions data based on the Dealing 2000-2 electronic inter-dealer broking system indicates significant evidence of intraday seasonality in returns and return vo…

Analyzes multi-day stock returns, showing linear volatility and mean dependence.

Intra-day price spreads are of interest to electricity traders, storage and electric vehicle operators. This paper formulates dynamic density functions, based upon skewed-t and similar representations, to model and forecast the German electricity price spreads between different hours of the day, as revealed in the day-…

We describe the impact of the intra-day activity pattern on the autocorrelation function estimator. We obtain an exact formula relating estimators of the autocorrelation functions of non-stationary process to its stationary counterpart. Hence, we proved that the day seasonality of inter-transaction times extends the me…

Our paper aims to model supply and demand curves of electricity day-ahead auction in a parsimonious way. Our main task is to build an appropriate algorithm to present the information about electricity prices and demands with far less parameters than the original one. We represent each curve using mesh-free interpolatio…

Predicts morning traffic congestion using social media data from the previous evening.

We establish several new stylised facts concerning the intra-day seasonalities of stock dynamics. Beyond the well known U-shaped pattern of the volatility, we find that the average correlation between stocks increases throughout the day, leading to a smaller relative dispersion between stocks. Somewhat paradoxically, t…

Accumulated stock returns exhibit tempered skew t-distribution.

Study finds CRPS learning doesn't improve day-ahead bidding profits despite better accuracy.

DAIS improves AIS by resampling, avoiding gradient issues.

A winning method for day-ahead electricity demand forecasting during and after the COVID-19 pandemic.

Using publicly available traffic camera data in New York City, we quantify time-dependent patterns in aggregate pedestrian foot traffic. These patterns exhibit repeatable diurnal behaviors that differ for weekdays and weekends but are broadly consistent across neighborhoods in the borough of Manhattan. Weekday patterns…

DAIS improves AIS for differentiable marginal likelihood estimation.

We present an empirical study of price reversion after the executed metaorders. We use a data set with more than 8 million metaorders executed by institutional investors in the US equity market. We show that relaxation takes place as soon as the metaorder ends:{while at the end of the same day it is on average $\approx…

We consider a statistical model for pairs of traded assets, based on a Cointegrated Vector Auto Regression (CVAR) Model. We extend standard CVAR models to incorporate estimation of model parameters in the presence of price series level shifts which are not accurately modeled in the standard Gaussian error correction mo…

Study reveals how illiquidity network signals Chinese stock market crashes.

Novel approach predicts long-term seasonal component of electricity prices for improved forecasting.

In our paper we analyze the relationship between the day-ahead electricity price of the Energy Exchange Austria (EXAA) and other day-ahead electricity prices in Europe. We focus on markets, which settle their prices after the EXAA, which enables traders to include the EXAA price into their calculations. For each market…

Statistical depth metrics help identify risky power grid scenarios.

We study the price dynamics of stocks traded in a financial market by considering the statistical properties both of a single time series and of an ensemble of stocks traded simultaneously. We use the $n$ stocks traded in the New York Stock Exchange to form a statistical ensemble of daily stock returns. For each tradin…

In this work we investigate intra-day patterns of activity on a population of 7,261 users of mobile health wearable devices and apps. We show that: (1) using intra-day step and sleep data recorded from passive trackers significantly improves classification performance on self-reported chronic conditions related to ment…

We investigate the herd behavior of returns for the yen-dollar exchange rate in the Japanese financial market. It is obtained that the probability distribution $P(R)$ of returns $R$ satisfies the power-law behavior $P(R) \simeq R^{-β}$ with the exponents $β=3.11$(the time interval $τ=$ one minute) and 3.36($τ=$ one da…

The paper analyzes profitable bidding strategies for BESS in day-ahead and intraday markets.

XGB-Chiarella model generates realistic intra-day financial price data using agent-based models.

Study predicts price predictability in ultra-high frequency financial data using entropy tests.

Machine learning and data mining techniques have been used extensively in order to detect credit card frauds. However purchase behaviour and fraudster strategies may change over time. This phenomenon is named dataset shift or concept drift in the domain of fraud detection. In this paper, we present a method to quantify…

We considered observational data available from the MIMIC-III open-access ICU database and collected within a study period between year 2002 up to 2011. If a patient had multiple admissions to the ICU during the 30 days before death, only the first stay was analyzed, leading to a final set of 6,436 unique ICU admission…

Study algebraic obstructions to knot-like complex realizability.

The paper models financial correlation matrices using permutation invariant Gaussian models and predicts market anomalies.

We study the space of L^2 harmonic forms on complete manifolds with metrics of fibred boundary or fibred cusp type. These metrics generalize the geometric structures at infinity of several different well-known classes of metrics, including asymptotically locally Euclidean manifolds, the (known types of) gravitational i…

Study finds monthly SIPs outperform first-day SIPs in Nifty 50 by 0.5-2.5% annually.

Study confirms USD/JPY rises at Gotobi days, suggesting trading strategy.

Neural networks outperform single-hour models in day-ahead electricity price forecasting.