Lost in the crowd! Pricing carbon at the age of algorithms
A new study reveals systematic mispricing in the EU Emissions Trading System (EU ETS), driven by crowded high-frequency and algorithmic trading. Although each trade’s error is small, losses can reach 4 percent of total trading value, risking flash crashes and price spikes. The research shows these problems persist even with larger traders, challenging common beliefs. Current regulations like MiFID II only partly address the issue. The paper urges new speed monitoring rules to prevent market instability.
What it examines
This paper studies how high frequency and algorithmic trading affect carbon pricing in the EU Emissions Trading System. It uses empirical data to examine if crowded trading leads to mispricing, focusing on the role of algorithms and the effectiveness of current regulations like MiFID II.
What it concludes
The study finds persistent mispricing from crowded algorithmic trading, which can cause market failures like flash crashes. Current regulations only partly help. The research suggests monitoring trading speed is needed. These findings can help improve market rules and risk controls in carbon and other financial markets.
Evidence objects
New research reveals persistent mispricing in the EU Emissions Trading System, driven by crowded high-frequency and algorithmic trading, with losses accumulating to 4% of total trading valueposing risks of flash crashes.
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The study finds these market distortions are unique to algorithmic trading and remain even with increased capital, challenging the belief that larger players can stabilize the market and prevent sudden price spikes.
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Current regulations like MiFID II only partially address these risks; the paper calls for urgent speed monitoring measures, arguing transparency alone cannot prevent instability, and highlights the need for stronger oversight in carbon markets.
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This paper uniquely investigates systematic mispricing from algorithmic high-frequency trading in the EU ETS carbon market, a rarely studied context compared to equities or FX. Its novel findingspersistent mispricing unaffected by capital and insufficient transparencyoffer fresh regulatory insights, making it compelling for quantitative finance, risk management, and market microstructure research.
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Raw abstract and provenance
This work investigates crowdedness in (H)igh (F)requency (T)rading (HFT) in the EU ETS. The empirical findings report a systematic crowdedness-related mispricing, which is observed only in algorithmic trading. While this mispricing is relatively small on a per trade basis, it is persistent and it does not disappear with more capital. Consequently, it can accumulate rapidly, reaching up to 4 % of trading value and potentially leading to market failures such as flash crashes and price spikes. Existing regulatory measures, such as the MiFID II trading rules, mitigate this effect only partially. This suggests that transparency alone is not sufficient in mitigating the risk of market failures and that some kind of speed monitoring is needed.
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