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Accurate household electricity short-term load forecasting (STLF) is key to future and sustainable energy systems. While various studies have analyzed statistical, machine learning, or deep learning approaches for household electricity…

Computational Engineering, Finance, and Science · Computer Science 2026-01-09 Marcel Meyer , David Zapata , Sascha Kaltenpoth , Oliver Müller

Overwhelming majority of econometric models applied on a long term basis in the financial forex market do not work sufficiently well. The reason is that transaction costs and arbitrage opportunity are not included, as this does not simulate…

Statistical Finance · Quantitative Finance 2015-11-23 Richard Pinčák , Erik Bartoš

In the peer to peer (P2P) lending platform, investors hope to maximize their return while minimizing the risk through a comprehensive understanding of the P2P market. A low and stable average default rate across all the borrowers denotes a…

Machine Learning · Computer Science 2020-09-11 Yan Wang , Xuelei Sherry Ni

In this paper, we propose a Network-Weighted Functional Regression (NWFR) model, an extension of Spatially Weighted Functional Regression (SWFR) to functional data defined on network-structured settings. To asses predictive uncertainity, we…

Methodology · Statistics 2025-06-02 Elvira Romano , Antonio Irpino , Claire Miller

Electricity market prices exhibit extreme volatility, nonlinearity, and non-stationarity, making accurate forecasting a significant challenge. While cutting-edge time series foundation models (TSFMs) effectively capture temporal…

Machine Learning · Computer Science 2026-03-10 Yunzhong Qiu , Binzhu Li , Hao Wei , Shenglin Weng , Chen Wang , Zhongyi Pei , Mingsheng Long , Jianmin Wang

With the widespread application of machine learning in financial risk management, conventional wisdom suggests that longer training periods and more feature variables contribute to improved model performance. This paper, focusing on…

Statistical Finance · Quantitative Finance 2025-01-03 Chengyue Huang , Yahe Yang

Process Model Forecasting (PMF) aims to predict how the control-flow structure of a process evolves over time by modeling the temporal dynamics of directly-follows (DF) relations, complementing predictive process monitoring that focuses on…

Machine Learning · Computer Science 2025-12-09 Yongbo Yu , Jari Peeperkorn , Johannes De Smedt , Jochen De Weerdt

Multifractal analysis is a forecasting technique used to study the scaling regularity properties of financial returns, to analyze the long-term memory and predictability of financial markets. In this paper, we propose a novel structural…

Statistical Finance · Quantitative Finance 2023-04-18 Foued Saâdaoui

Options with maturities below one week, hereafter "ultra-short-term" options, have seen a sharp increase in trading activity in recent years. Yet, these instruments are difficult to price jointly using classical pricing models due to the…

Mathematical Finance · Quantitative Finance 2026-04-01 Federico M. Bandi , Nicola Fusari , Guido Gazzani , Roberto Renò

The frequency response function (FRF) is an established way to describe the outcome of experiments in posture control literature. The FRF is an empirical transfer function between an input stimulus and the induced body segment sway profile,…

Applications · Statistics 2025-05-27 Vittorio Lippi

A precise estimation of the Rate of Change of Frequency (RoCoF) is crucial for secure power system operation. In fact, RoCoF is strictly related to the amount of the available physical and/or virtual inertia of the system and the severity…

Systems and Control · Electrical Eng. & Systems 2025-11-06 Gutierrez-Florensa , F. Sanniti , D. Tedeschi , L. Sigrist , A. Ortega , F. Milano

We present a detailed study of the performance of a trading rule that uses moving average of past returns to predict future returns on stock indexes. Our main goal is to link performance and the stochastic process of the traded asset. Our…

Statistical Finance · Quantitative Finance 2019-07-03 Fernando F. Ferreira , A. Christian Silva , Ju-Yi Yen

There are inefficiencies in financial markets, with unexploited patterns in price, volume, and cross-sectional relationships. While many approaches use large-scale transformers, we take a domain-focused path: feed-forward and recurrent…

Portfolio Management · Quantitative Finance 2025-10-15 Sid Ghatak , Arman Khaledian , Navid Parvini , Nariman Khaledian

The liquidity risk factor of security market plays an important role in the formulation of trading strategies. A more liquid stock market means that the securities can be bought or sold more easily. As a sound indicator of market liquidity,…

Computational Finance · Quantitative Finance 2021-01-11 Yong Shi , Wei Dai , Wen Long , Bo Li

Online testing procedures assume that hypotheses are observed in sequence, and allow the significance thresholds for upcoming tests to depend on the test statistics observed so far. Some of the most popular online methods include alpha…

Methodology · Statistics 2022-02-11 Aaron Fisher

We propose a multifractal model for short-term interest rates. The model is a version of the Markov-Switching Multifractal (MSM), which incorporates the well-known level effect observed in interest rates. Unlike previously suggested models,…

Statistical Finance · Quantitative Finance 2011-11-23 M. Rypdal , O. Løvsletten

US Yield curve has recently collapsed to its most flattened level since subprime crisis and is close to the inversion. This fact has gathered attention of investors around the world and revived the discussion of proper modeling and…

Statistical Finance · Quantitative Finance 2018-08-01 Jarek Duda , Małgorzata Snarska

The growth of the exhange-traded fund (ETF) industry has given rise to the trading of options written on ETFs and their leveraged counterparts {(LETFs)}. We study the relationship between the ETF and LETF implied volatility surfaces when…

Computational Finance · Quantitative Finance 2015-04-16 Tim Leung , Matthew Lorig , Andrea Pascucci

This paper quantifies the international spillovers of US interest rates by explicitly controlling for the "Fed Information Effect". I use multiple identification strategies that identify two components of monetary policy surprises around…

General Economics · Economics 2024-05-24 Santiago Camara

We study the role of co-jumps in the interest rate futures markets. To disentangle continuous part of quadratic covariation from co-jumps, we localize the co-jumps precisely through wavelet coefficients and identify statistically…

Statistical Finance · Quantitative Finance 2019-05-07 Jozef Barunik , Pavel Fiser