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arXiv research

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.

169,051 papers · 148 categories

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0.3%0.5%0.8%0.3% · Mar 201219922001200920172026
7 results for non-storability

A new model uses sparse Gaussian processes to hedge electricity market risks.

problem Risk minimization in electricity markets due to non-storability and volatility.
method Coregionalized sparse Gaussian processes to model price and load correlations.
result The model outperforms traditional average-load strategies in hedging.

In this paper analytic formulas for electricity derivatives are calculated. To this end, we assume that electricity spot prices follow a 3-regime Markov regime-switching model with independent spikes and drops and periodic transition matrix. Since the classical derivatives pricing methodology cannot be used in case of …

2012-03-24abs ↗pdf ↗

We analyze long-term memory properties of hourly prices of electricity in the Czech Republic between 2009 and 2012. As the dynamics of the electricity prices is dominated by cycles -- mainly intraday and daily -- we opt for the detrended fluctuation analysis, which is well suited for such specific series. We find that …

2013-09-03abs ↗pdf ↗

Proposes a model for long-term electricity contracts with explicit computation and easy calibration.

problem Non-storability and poor liquidity in long-term electricity markets.
method Multi-factor polynomial framework for explicit computation of forwards, risk premium, and correlation.
result Calibrated model provides a risk-minimizing hedge for various time horizons.

Study improves electricity price forecasting accuracy using a hybrid model.

problem Accurate short-term electricity price forecasting is challenging due to social and natural factors.
method Hybrid model combining GARMA, G-GARCH, Wavelet, LLWNN, and optimization algorithms.
result The hybrid model outperforms other models in Nord Pool Electricity markets.

This research proposes a method to hedge freight rate risk in shipping markets under model uncertainty.

problem Managing freight risk in shipping markets under model uncertainty.
method The approach uses Wasserstein barycenter for modeling freight rates dynamics and optimal hedging strategy selection.
result The proposed method provides robust hedging strategies even in high noise cases.