Results 71 to 80 of about 2,923 (211)

Forecasting Wind–Photovoltaic Energy Production and Income with Traditional and ML Techniques

Econometrics
Hybrid production plants harness diverse climatic sources for electricity generation, playing a crucial role in the transition to renewable energies. This study aims to forecast the profitability of a combined wind–photovoltaic energy system.
Giovanni Masala, Amelie Schischke
doaj   +1 more source

Data‐Driven Energy Planning in Developing Countries: An Integrated LEAP‐Machine Learning Approach

Journal of Engineering, Volume 2026, Issue 1, 2026.
Developing countries encounter substantial obstacles in regional energy planning stemming from scarce historical data and insufficient forecasting methodologies, thereby impeding the formulation of effective sustainable energy transition strategies.
Wahab Musa, Wrastawa Ridwan, Asad Ali Zaidi   +2 more
wiley   +1 more source

Data Driven Investment Strategies Using Bayesian Inference in Regime‐Switching Models

Applied Stochastic Models in Business and Industry, Volume 41, Issue 6, November/December 2025.
ABSTRACT This article presents the benefits of using Bayesian algorithms to fit regime‐switching models to daily financial returns data in order to design trading strategies. Our study focuses on a Gaussian hidden Markov model (HMM). We show how the application of a simple smoothing technique preserves the hidden Markov structure and facilitates regime
Eléonore Blanchard, Pierre‐Olivier Goffard   +1 more
wiley   +1 more source

On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles

Risks, 2018
This article reviews two leading measures of financial risk and an emerging alternative. Embraced by the Basel accords, value-at-risk and expected shortfall are the leading measures of financial risk.
James Ming Chen
doaj   +1 more source

Trading Games: Beating Passive Strategies in the Bullish Crypto Market

Journal of Futures Markets, Volume 45, Issue 11, Page 1911-1933, November 2025.
ABSTRACT This study examines the effectiveness of cointegrated pairs trading in cryptocurrency markets, introducing systematic parameter optimization within the trading framework. The analysis is conducted using a dataset comprising ten major cryptocurrencies, selected based on market capitalization and consensus mechanism, spanning the period from ...
Rafael Baptista Palazzi
wiley   +1 more source

Validating the backtests of risk measures

, 2007
Paper presented at INFINITI Conference on International Finance 11-12 June 2007, Trinity College Dublin. Also presented at Financial Management Association Annual Meeting, Orlando, Florida , 18-20 October 2007Financial risk model evaluation or ...
Cotter, John, Zhong, Yan Ping
core  

Asymmetric stable stochastic volatility models: estimation, filtering, and forecasting

Journal of Time Series Analysis, Volume 46, Issue 6, Page 1098-1124, November 2025.
This article considers a stochastic volatility model featuring an asymmetric stable error distribution and a novel way of accounting for the leverage effect. We adopt simulation‐based methods to address key challenges in parameter estimation, the filtering of time‐varying volatility, and volatility forecasting.
Francisco Blasques, Siem Jan Koopman, Karim Moussa   +2 more
wiley   +1 more source

Measuring Traded Market Risk: Value-at-risk and Backtesting Techniques [PDF]

The proposed market-risk capital-adequacy framework, to be implemented at the end of 1997, requires Australian banks to hold capital against market risk.
Colleen Cassidy, Marianne Gizycki
core  

Estimation and Inference for Higher‐Order Stochastic Volatility Models With Leverage

Journal of Time Series Analysis, Volume 46, Issue 6, Page 1064-1084, November 2025.
ABSTRACT Statistical inference—estimation and testing—for stochastic volatility models is challenging and computationally expensive. This problem is compounded when leverage effects are allowed. We propose efficient, simple estimators for higher‐order stochastic volatility models with leverage [SVL(p)$$ (p) $$], based on a small number of moment ...
Md. Nazmul Ahsan, Jean‐Marie Dufour, Gabriel Rodriguez‐Rondon   +2 more
wiley   +1 more source

The Sign RCA Models: Comparing Predictive Accuracy of VaR Measures [PDF]

Evaluating Value at Risk (VaR) methods of predictive accuracy in an objective and effective framework is important for both efficient capital allocation and loss prediction.
Joanna Górka
core