On-device research index

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.

168,695 papers · 148 categories

Trend · papers per month

count % of corpus

6 results for “NIFTY50”

Decision Trees for Intuitive Intraday Trading Strategiesq-fin.ST

Decision trees improve intraday trading strategies for NIFTY50 stocks.

problem Creating optimal trading rules for individual stocks.

method Using decision trees to generate unique trading rules for each stock based on technical indicators.

result Decision tree strategies outperform simple buy-and-hold for many stocks.

decision trees intraday trading technical indicators NIFTY50 trading performance

2024-05-22abs ↗pdf ↗

Risk Analysis of Passive Portfoliosq-fin.ST

This study proposes an equal-weight portfolio strategy to reduce risk compared to traditional ETFs.

problem Risk of passive ETFs not matching optimal portfolio weights.

method Introduced an equal-weight portfolio strategy to reduce idiosyncratic risk.

result Equal-weight portfolio has lower risk than traditional ETFs, especially during idiosyncratic events.

passive investing portfolio optimization risk management equal-weight idiosyncratic risk

2024-07-11abs ↗pdf ↗

Analysis of the Impact of the Union Budget Announcements on the Indian Stock Market: A Fractal Perspectiveq-fin.ST

This study analyzes how the Indian stock market reacts to budget announcements using fractal methods.

problem Understanding the impact of Union Budget announcements on the Indian stock market.

method Utilizes fractal interpolation function and fractal dimensional analysis to study the NIFTY50 index over -15 to +15 days post-budget day.

result The budget announcements significantly affect the Indian stock market, as evidenced by average abnormal return and cumulative abnormal return.

Indian stock market Union Budget Fractal Analysis NIFTY50 AAR

2025-02-18abs ↗pdf ↗

A Comparative Analysis of Portfolio Optimization Using Mean-Variance, Hierarchical Risk Parity, and Reinforcement Learning Approaches on the Indian Stock Marketcs.LG

This study compares three portfolio optimization methods on Indian stocks.

problem Comparing portfolio optimization methods on Indian stocks.

method Mean-Variance, Hierarchical Risk Parity, and Reinforcement Learning approaches.

result Reinforcement Learning outperformed other methods in terms of Sharpe ratio.

portfolio optimization mean-variance reinforcement learning risk parity Indian stock market

2023-05-27abs ↗pdf ↗

Multi-Objective reward generalization: Improving performance of Deep Reinforcement Learning for applications in single-asset tradingcs.LG

The paper explores a Multi-Objective RL approach for trading that generalizes reward functions.

problem Improving performance in single-asset trading through adaptive reward functions.

method Developed a Multi-Objective Deep Reinforcement Learning algorithm to generalize reward functions and discount factors.

result The Multi-Objective algorithm demonstrates increased predictive stability and better performance in sparse reward scenarios.

Deep Reinforcement Learning Trading Multi-Objective Reward Generalization Predictive Stability

2022-03-09abs ↗pdf ↗

Forecasting Financial Market Structure from Network Features using Machine Learningq-fin.CP

Model forecasts market structure from financial networks using machine learning.

problem Predicting market correlation structure from financial networks.

method Dynamic Asset Graph (DAG), Dynamic Minimal Spanning Tree (DMST), Dynamic Threshold Networks (DTN).

result Model improves market structure forecasting by up to 40% over benchmarks.

Financial networks Machine learning Market structure Dynamic graphs Correlation forecasting

2021-10-22abs ↗pdf ↗