Intraday Momentum
Jan 24, 2025
The Quanted Round-up is a curated summary that covers relevant research on key topics in quantitative financial decision-making.
Highlights
This edition looks at the complex drivers of intraday momentum, revealing how liquidity dynamics, market structure, and behavioural factors shape return patterns. The findings provide a nuanced understanding of these mechanisms, offering practical insights for enhancing trading strategies and addressing inefficiencies across diverse financial markets.
How To Profitably Trade Bitcoin’s Overnight Sessions?
Radovan Vojtko & Dujava Cyril
As interest in cryptocurrencies continues to surge, driven by each new price rally, crypto assets have solidified their position as one of the main asset classes in global markets. Unlike traditional assets, which primarily trade during standard working hours, cryptocurrencies trade 24/7, presenting a unique landscape of liquidity and volatility. This continuous trading environment has prompted us to investigate how Bitcoin, the flagship cryptocurrency, behaves across intraday and overnight periods. With Bitcoin’s growing availability to both retail and institutional investors through ETFs and other investment vehicles, we hypothesized that trading activity in these distinct timeframes could reveal patterns similar to those seen in traditional markets, where returns are often impacted by liquidity shifts during off-peak hours.
What Drives Momentum and Reversal? Evidence from Day and Night Signals
Yashar Barardehi, Vincent Bogousslavsky & Dmitriy Muravyev
Trading is concentrated intraday, which has remained remarkably stable over time. We use this fact to test theories of momentum and reversal with a sample of intraday and overnight returns from 1926 to 2019. Portfolios formed on past intraday returns display short-term reversal and momentum without long-term reversal. In contrast, portfolios formed on past overnight returns display no short-term reversal or momentum but long-term reversal. These results are consistent with underreaction theories of momentum, in which investors underreact to the information conveyed by the trades of other investors.
Improvements to Intraday Momentum Strategies Using Parameter Optimisation and Different Exit Strategies
Ákos Maróy
Building on the results of Zarattini, C., Aziz, A., & Barbon, A. (2024). Beat the market: An effective intraday momentum strategy for S&P500 ETF (SPY), we explore improvements to noise boundary based intraday momentum strategies by investigating different exit strategies and applying parameter optimisation to all parameters of the strategies. We show that the returns of the momentum strategy can be significantly improved by such an approach. The best results are achieved with exits based on VWAP, VWAP & Ladder and Ladder exit strategies, with Sharpe ratios over 3.0 and annualised returns of over 50%, which are significant improvements against the baseline strategy.
Intraday Time Series Momentum: Global Evidence and Links to Market Characteristics
Zeming Li, Athanasios Sakkas & Andrew Urquhart
We examine intraday time series momentum (ITSM) in an international setting by employing high-frequency data of 16 developed markets. We show that ITSM is economically sizable and statistically significant both in- and out-of- sample in most countries. Based on theories of investor behavior, we propose and test four hypotheses to reveal the source of ITSM profitability. We document both in the cross- section and time series dimension that ITSM is stronger when liquidity is low, volatility is high, and new information is discrete. Overall, our results suggest that the ITSM is driven by both market microstructure and behavioral factors.
Hedging Demand and Market Intraday Momentum
Guido Baltussen, Zhi Da, Sten Lammers & Martin Martens
Hedging short gamma exposure requires trading in the direction of price movements, thereby creating price momentum. Using intraday returns on over 60 futures on equities, bonds, commodities, and currencies between 1974 and 2020, we document strong “marketintraday momentum” everywhere. The return during the last 30 minutes before the marketclose is positively predicted by the return during the rest of the day (from previous marketclose to the last 30 minutes). The predictive power is economically and statistically highlysignificant, and reverts over the next days. We provide novel evidence that links marketintraday momentum to the gamma hedging demand from market participants such as marketmakers of options and leveraged ETFs.
End-of-Day Reversal
Amar Soebhag, Guido Baltussen & Zhi Da
Individual stocks experience sharp intraday return reversals in the cross-section during the last 30 minutes of the trading day. This "end-of-day reversal" pattern is economically and statistically highly significant, is distinct from market intraday momentum, and primarily comes from positive price pressure on intraday losers. The effect cannot be explained by liquidity or gamma hedging effects. Instead, two novel channels related to the attention-induced retail purchases and risk management by short-sellers at the end of the day are driving the effect.
Gamma Fragility
Andrea Barbon & Andrea Buraschi
We document a link between large aggregate dealers' gamma imbalances and intraday momentum/reversal of stock returns, arising from the potential feedback effects of delta-hedging in derivative markets on the underlying market. This channel relies on limited liquidity of the underlying market, but it is distinct from information frictions (adverse selection and private information) and funding liquidity frictions (margin requirement shocks). We test our joint hypothesis using a large panel of equity options that we use to compute a proxy of stock-level gamma imbalance. We find supporting evidence that intra-day momentum (reversal) is explained by the interaction of negative (positive) ex-ante gamma imbalance and and illiquidity. The effect is stronger for the least liquid underlying securities. Our results help to explain both intra-day volatility and autocorrelation of returns. Moreover, we find that gamma imbalance is related to the frequency and the magnitude of flash crash events.
Stock Market’s responses to intraday investor sentiment
Sang Seok, Hoon Cho & Doojin Ryu
We investigate the effect of intraday sentiment on subsequent stock returns. Mispricing caused by intraday sentiment is not corrected immediately; rather, it lasts for about 30 min. After 30 min, however, investor sentiment negatively affects stock returns, suggesting that mispriced stocks are at least partially but not entirely adjusted back to their fundamental values. We also show that the effect of intraday sentiment depends on the degree of arbitrage. Intraday sentiment has little effect on firms that are easy to arbitrage. For these firms, the difference in the one-minute returns of firms with high and low sentiment is nearly zero, implying that any mispricing caused by intraday sentiment is immediately corrected for this group of firms. In contrast, among firms that are hard to arbitrage, the difference in the returns of firms with high and low sentiment lasts for about half an hour. This difference in the effect of intraday sentiment is not caused by the firms’ liquidities.
References
End-of-Day Reversal. November 2024. Soebhag, A.; Baltussen, G. and Da, Z. Available at
Gamma Fragility. November 2020. Barbon, A and Buraschi, A. University of St.Gallen,
School of Finance Research Paper. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3725454
Hedging Demand and Market Intraday Momentum. January 2021. Baltussen, G.; Da, Z.;
Lammers, S. and Martens, M. Journal of Financial Economics (JFE), Volume 142, Issue 1,
October 2021, Pages 377-403. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3760365
How To Profitably Trade Bitcoin’s Overnight Sessions? January 2025. Vojtko, R. and
Cyril, D. Available at SSRN: http://dx.doi.org/10.2139/ssrn.5021138
Improvements to Intraday Momentum Strategies Using Parameter Optimization and
Different Exit Strategies. January 2025. Maróy, A. Available at SSRN: http://dx.doi.org/10.2139/ssrn.5095349
Intraday time series momentum: Global evidence and links to market characteristics.
January 2022. Li, Z.; Sakkas, A. and Urquhart, A. Journal of Financial Markets, Volume 57.
Available at Elsevier: https://doi.org/10.1016/j.finmar.2021.100619
Stock Market’s responses to intraday investor sentiment. November 2021.
Cho, H. and Ryu, D. The North American Journal of Economics and Finance, Volume 58.
Available at Elsevier: https://doi.org/10.1016/j.najef.2021.101516
The Quanted Round-up is a curated summary that covers relevant research on key topics in quantitative financial decision-making.
Highlights
This edition looks at the complex drivers of intraday momentum, revealing how liquidity dynamics, market structure, and behavioural factors shape return patterns. The findings provide a nuanced understanding of these mechanisms, offering practical insights for enhancing trading strategies and addressing inefficiencies across diverse financial markets.
How To Profitably Trade Bitcoin’s Overnight Sessions?
Radovan Vojtko & Dujava Cyril
As interest in cryptocurrencies continues to surge, driven by each new price rally, crypto assets have solidified their position as one of the main asset classes in global markets. Unlike traditional assets, which primarily trade during standard working hours, cryptocurrencies trade 24/7, presenting a unique landscape of liquidity and volatility. This continuous trading environment has prompted us to investigate how Bitcoin, the flagship cryptocurrency, behaves across intraday and overnight periods. With Bitcoin’s growing availability to both retail and institutional investors through ETFs and other investment vehicles, we hypothesized that trading activity in these distinct timeframes could reveal patterns similar to those seen in traditional markets, where returns are often impacted by liquidity shifts during off-peak hours.
What Drives Momentum and Reversal? Evidence from Day and Night Signals
Yashar Barardehi, Vincent Bogousslavsky & Dmitriy Muravyev
Trading is concentrated intraday, which has remained remarkably stable over time. We use this fact to test theories of momentum and reversal with a sample of intraday and overnight returns from 1926 to 2019. Portfolios formed on past intraday returns display short-term reversal and momentum without long-term reversal. In contrast, portfolios formed on past overnight returns display no short-term reversal or momentum but long-term reversal. These results are consistent with underreaction theories of momentum, in which investors underreact to the information conveyed by the trades of other investors.
Improvements to Intraday Momentum Strategies Using Parameter Optimisation and Different Exit Strategies
Ákos Maróy
Building on the results of Zarattini, C., Aziz, A., & Barbon, A. (2024). Beat the market: An effective intraday momentum strategy for S&P500 ETF (SPY), we explore improvements to noise boundary based intraday momentum strategies by investigating different exit strategies and applying parameter optimisation to all parameters of the strategies. We show that the returns of the momentum strategy can be significantly improved by such an approach. The best results are achieved with exits based on VWAP, VWAP & Ladder and Ladder exit strategies, with Sharpe ratios over 3.0 and annualised returns of over 50%, which are significant improvements against the baseline strategy.
Intraday Time Series Momentum: Global Evidence and Links to Market Characteristics
Zeming Li, Athanasios Sakkas & Andrew Urquhart
We examine intraday time series momentum (ITSM) in an international setting by employing high-frequency data of 16 developed markets. We show that ITSM is economically sizable and statistically significant both in- and out-of- sample in most countries. Based on theories of investor behavior, we propose and test four hypotheses to reveal the source of ITSM profitability. We document both in the cross- section and time series dimension that ITSM is stronger when liquidity is low, volatility is high, and new information is discrete. Overall, our results suggest that the ITSM is driven by both market microstructure and behavioral factors.
Hedging Demand and Market Intraday Momentum
Guido Baltussen, Zhi Da, Sten Lammers & Martin Martens
Hedging short gamma exposure requires trading in the direction of price movements, thereby creating price momentum. Using intraday returns on over 60 futures on equities, bonds, commodities, and currencies between 1974 and 2020, we document strong “marketintraday momentum” everywhere. The return during the last 30 minutes before the marketclose is positively predicted by the return during the rest of the day (from previous marketclose to the last 30 minutes). The predictive power is economically and statistically highlysignificant, and reverts over the next days. We provide novel evidence that links marketintraday momentum to the gamma hedging demand from market participants such as marketmakers of options and leveraged ETFs.
End-of-Day Reversal
Amar Soebhag, Guido Baltussen & Zhi Da
Individual stocks experience sharp intraday return reversals in the cross-section during the last 30 minutes of the trading day. This "end-of-day reversal" pattern is economically and statistically highly significant, is distinct from market intraday momentum, and primarily comes from positive price pressure on intraday losers. The effect cannot be explained by liquidity or gamma hedging effects. Instead, two novel channels related to the attention-induced retail purchases and risk management by short-sellers at the end of the day are driving the effect.
Gamma Fragility
Andrea Barbon & Andrea Buraschi
We document a link between large aggregate dealers' gamma imbalances and intraday momentum/reversal of stock returns, arising from the potential feedback effects of delta-hedging in derivative markets on the underlying market. This channel relies on limited liquidity of the underlying market, but it is distinct from information frictions (adverse selection and private information) and funding liquidity frictions (margin requirement shocks). We test our joint hypothesis using a large panel of equity options that we use to compute a proxy of stock-level gamma imbalance. We find supporting evidence that intra-day momentum (reversal) is explained by the interaction of negative (positive) ex-ante gamma imbalance and and illiquidity. The effect is stronger for the least liquid underlying securities. Our results help to explain both intra-day volatility and autocorrelation of returns. Moreover, we find that gamma imbalance is related to the frequency and the magnitude of flash crash events.
Stock Market’s responses to intraday investor sentiment
Sang Seok, Hoon Cho & Doojin Ryu
We investigate the effect of intraday sentiment on subsequent stock returns. Mispricing caused by intraday sentiment is not corrected immediately; rather, it lasts for about 30 min. After 30 min, however, investor sentiment negatively affects stock returns, suggesting that mispriced stocks are at least partially but not entirely adjusted back to their fundamental values. We also show that the effect of intraday sentiment depends on the degree of arbitrage. Intraday sentiment has little effect on firms that are easy to arbitrage. For these firms, the difference in the one-minute returns of firms with high and low sentiment is nearly zero, implying that any mispricing caused by intraday sentiment is immediately corrected for this group of firms. In contrast, among firms that are hard to arbitrage, the difference in the returns of firms with high and low sentiment lasts for about half an hour. This difference in the effect of intraday sentiment is not caused by the firms’ liquidities.
References
End-of-Day Reversal. November 2024. Soebhag, A.; Baltussen, G. and Da, Z. Available at
Gamma Fragility. November 2020. Barbon, A and Buraschi, A. University of St.Gallen,
School of Finance Research Paper. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3725454
Hedging Demand and Market Intraday Momentum. January 2021. Baltussen, G.; Da, Z.;
Lammers, S. and Martens, M. Journal of Financial Economics (JFE), Volume 142, Issue 1,
October 2021, Pages 377-403. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3760365
How To Profitably Trade Bitcoin’s Overnight Sessions? January 2025. Vojtko, R. and
Cyril, D. Available at SSRN: http://dx.doi.org/10.2139/ssrn.5021138
Improvements to Intraday Momentum Strategies Using Parameter Optimization and
Different Exit Strategies. January 2025. Maróy, A. Available at SSRN: http://dx.doi.org/10.2139/ssrn.5095349
Intraday time series momentum: Global evidence and links to market characteristics.
January 2022. Li, Z.; Sakkas, A. and Urquhart, A. Journal of Financial Markets, Volume 57.
Available at Elsevier: https://doi.org/10.1016/j.finmar.2021.100619
Stock Market’s responses to intraday investor sentiment. November 2021.
Cho, H. and Ryu, D. The North American Journal of Economics and Finance, Volume 58.
Available at Elsevier: https://doi.org/10.1016/j.najef.2021.101516
The Quanted Round-up is a curated summary that covers relevant research on key topics in quantitative financial decision-making.
Highlights
This edition looks at the complex drivers of intraday momentum, revealing how liquidity dynamics, market structure, and behavioural factors shape return patterns. The findings provide a nuanced understanding of these mechanisms, offering practical insights for enhancing trading strategies and addressing inefficiencies across diverse financial markets.
How To Profitably Trade Bitcoin’s Overnight Sessions?
Radovan Vojtko & Dujava Cyril
As interest in cryptocurrencies continues to surge, driven by each new price rally, crypto assets have solidified their position as one of the main asset classes in global markets. Unlike traditional assets, which primarily trade during standard working hours, cryptocurrencies trade 24/7, presenting a unique landscape of liquidity and volatility. This continuous trading environment has prompted us to investigate how Bitcoin, the flagship cryptocurrency, behaves across intraday and overnight periods. With Bitcoin’s growing availability to both retail and institutional investors through ETFs and other investment vehicles, we hypothesized that trading activity in these distinct timeframes could reveal patterns similar to those seen in traditional markets, where returns are often impacted by liquidity shifts during off-peak hours.
What Drives Momentum and Reversal? Evidence from Day and Night Signals
Yashar Barardehi, Vincent Bogousslavsky & Dmitriy Muravyev
Trading is concentrated intraday, which has remained remarkably stable over time. We use this fact to test theories of momentum and reversal with a sample of intraday and overnight returns from 1926 to 2019. Portfolios formed on past intraday returns display short-term reversal and momentum without long-term reversal. In contrast, portfolios formed on past overnight returns display no short-term reversal or momentum but long-term reversal. These results are consistent with underreaction theories of momentum, in which investors underreact to the information conveyed by the trades of other investors.
Improvements to Intraday Momentum Strategies Using Parameter Optimisation and Different Exit Strategies
Ákos Maróy
Building on the results of Zarattini, C., Aziz, A., & Barbon, A. (2024). Beat the market: An effective intraday momentum strategy for S&P500 ETF (SPY), we explore improvements to noise boundary based intraday momentum strategies by investigating different exit strategies and applying parameter optimisation to all parameters of the strategies. We show that the returns of the momentum strategy can be significantly improved by such an approach. The best results are achieved with exits based on VWAP, VWAP & Ladder and Ladder exit strategies, with Sharpe ratios over 3.0 and annualised returns of over 50%, which are significant improvements against the baseline strategy.
Intraday Time Series Momentum: Global Evidence and Links to Market Characteristics
Zeming Li, Athanasios Sakkas & Andrew Urquhart
We examine intraday time series momentum (ITSM) in an international setting by employing high-frequency data of 16 developed markets. We show that ITSM is economically sizable and statistically significant both in- and out-of- sample in most countries. Based on theories of investor behavior, we propose and test four hypotheses to reveal the source of ITSM profitability. We document both in the cross- section and time series dimension that ITSM is stronger when liquidity is low, volatility is high, and new information is discrete. Overall, our results suggest that the ITSM is driven by both market microstructure and behavioral factors.
Hedging Demand and Market Intraday Momentum
Guido Baltussen, Zhi Da, Sten Lammers & Martin Martens
Hedging short gamma exposure requires trading in the direction of price movements, thereby creating price momentum. Using intraday returns on over 60 futures on equities, bonds, commodities, and currencies between 1974 and 2020, we document strong “marketintraday momentum” everywhere. The return during the last 30 minutes before the marketclose is positively predicted by the return during the rest of the day (from previous marketclose to the last 30 minutes). The predictive power is economically and statistically highlysignificant, and reverts over the next days. We provide novel evidence that links marketintraday momentum to the gamma hedging demand from market participants such as marketmakers of options and leveraged ETFs.
End-of-Day Reversal
Amar Soebhag, Guido Baltussen & Zhi Da
Individual stocks experience sharp intraday return reversals in the cross-section during the last 30 minutes of the trading day. This "end-of-day reversal" pattern is economically and statistically highly significant, is distinct from market intraday momentum, and primarily comes from positive price pressure on intraday losers. The effect cannot be explained by liquidity or gamma hedging effects. Instead, two novel channels related to the attention-induced retail purchases and risk management by short-sellers at the end of the day are driving the effect.
Gamma Fragility
Andrea Barbon & Andrea Buraschi
We document a link between large aggregate dealers' gamma imbalances and intraday momentum/reversal of stock returns, arising from the potential feedback effects of delta-hedging in derivative markets on the underlying market. This channel relies on limited liquidity of the underlying market, but it is distinct from information frictions (adverse selection and private information) and funding liquidity frictions (margin requirement shocks). We test our joint hypothesis using a large panel of equity options that we use to compute a proxy of stock-level gamma imbalance. We find supporting evidence that intra-day momentum (reversal) is explained by the interaction of negative (positive) ex-ante gamma imbalance and and illiquidity. The effect is stronger for the least liquid underlying securities. Our results help to explain both intra-day volatility and autocorrelation of returns. Moreover, we find that gamma imbalance is related to the frequency and the magnitude of flash crash events.
Stock Market’s responses to intraday investor sentiment
Sang Seok, Hoon Cho & Doojin Ryu
We investigate the effect of intraday sentiment on subsequent stock returns. Mispricing caused by intraday sentiment is not corrected immediately; rather, it lasts for about 30 min. After 30 min, however, investor sentiment negatively affects stock returns, suggesting that mispriced stocks are at least partially but not entirely adjusted back to their fundamental values. We also show that the effect of intraday sentiment depends on the degree of arbitrage. Intraday sentiment has little effect on firms that are easy to arbitrage. For these firms, the difference in the one-minute returns of firms with high and low sentiment is nearly zero, implying that any mispricing caused by intraday sentiment is immediately corrected for this group of firms. In contrast, among firms that are hard to arbitrage, the difference in the returns of firms with high and low sentiment lasts for about half an hour. This difference in the effect of intraday sentiment is not caused by the firms’ liquidities.
References
End-of-Day Reversal. November 2024. Soebhag, A.; Baltussen, G. and Da, Z. Available at
Gamma Fragility. November 2020. Barbon, A and Buraschi, A. University of St.Gallen,
School of Finance Research Paper. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3725454
Hedging Demand and Market Intraday Momentum. January 2021. Baltussen, G.; Da, Z.;
Lammers, S. and Martens, M. Journal of Financial Economics (JFE), Volume 142, Issue 1,
October 2021, Pages 377-403. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3760365
How To Profitably Trade Bitcoin’s Overnight Sessions? January 2025. Vojtko, R. and
Cyril, D. Available at SSRN: http://dx.doi.org/10.2139/ssrn.5021138
Improvements to Intraday Momentum Strategies Using Parameter Optimization and
Different Exit Strategies. January 2025. Maróy, A. Available at SSRN: http://dx.doi.org/10.2139/ssrn.5095349
Intraday time series momentum: Global evidence and links to market characteristics.
January 2022. Li, Z.; Sakkas, A. and Urquhart, A. Journal of Financial Markets, Volume 57.
Available at Elsevier: https://doi.org/10.1016/j.finmar.2021.100619
Stock Market’s responses to intraday investor sentiment. November 2021.
Cho, H. and Ryu, D. The North American Journal of Economics and Finance, Volume 58.
Available at Elsevier: https://doi.org/10.1016/j.najef.2021.101516
