---
title: Feedback Trading in India
url: https://www.ml-quant.com/papers/repec/sae-emffin-v-23-y-2024-i-2-p-246-270/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:sae:emffin:v:23:y:2024:i:2:p:246-270
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fjournals.sagepub.com%2Fdoi%2F10.1177%2F09726527231215541%3Bh%3Drepec%3Asae%3Aemffin%3Av%3A23%3Ay%3A2024%3Ai%3A2%3Ap%3A246-270
featured: 2024-05-08
citations: unknown
topic: Trading, Microstructure & Execution
---


# Feedback Trading in India

The study investigates the effect of feedback trading on India's market volatility during the COVID-19 pandemic, revealing that foreign institutional investors' positive feedback trading results in negative autocorrelation in market returns.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fjournals.sagepub.com%2Fdoi%2F10.1177%2F09726527231215541%3Bh%3Drepec%3Asae%3Aemffin%3Av%3A23%3Ay%3A2024%3Ai%3A2%3Ap%3A246-270
- Identifier: RePEc:sae:emffin:v:23:y:2024:i:2:p:246-270
- Released: 2024-05-08
- First featured: Quant Letter No. 48 (2024-05-08): https://www.ml-quant.com/issues/2024-05-08/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Trading, Microstructure & Execution

## Related

- [FAST: Efficient Action Tokenization for Vision-Language-Action Models](https://www.ml-quant.com/papers/arxiv/2501.09747/): A new tokenization scheme, Frequency-space Action Sequence Tokenization (FAST), has been proposed for robot actions, facilitating the training of vision-language action policies for complex and high-frequency tasks.
- [Deep Reinforcement Learning for Active High Frequency Trading](https://www.ml-quant.com/papers/arxiv/2101.07107/): A new Deep Reinforcement Learning framework has been developed for high frequency stock trading, showing potential for profitable long-term strategies.
- [Price-Aware Automated Market Makers: Models Beyond Brownian Prices and Static Liquidity](https://www.ml-quant.com/papers/arxiv/2405.03496/): Advanced Models: The article presents models for improving quotes in automated market making platforms, considering complex price changes and demand fluctuations.
- [Multiblock MEV opportunities&protections in dynamic AMMs](https://www.ml-quant.com/papers/arxiv/2404.15489/): The study investigates the risk of multi-block MEV attacks in dynamic weight market making, proposing new protections supported by numerous simulations.
- [Market Making in Spot Precious Metals](https://www.ml-quant.com/papers/arxiv/2404.15478/): A new framework is presented for modeling the EFP spread in spot precious metals market making, using a nested Ornstein-Uhlenbeck process to balance profit and inventory risk.
- [Inflation and Trading](https://www.ml-quant.com/papers/ssrn/4822700/): Research indicates that investors often hold unrealistic expectations about stock returns during high inflation, and lack knowledge about inflation-hedging strategies, affecting their trading decisions.
