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A Surya Pratap Singh Experience

  • About Me
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    • English Poetry
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Meta-Learning in Finance: Training Models That Learn to Trade Faster

Energy-Based Models for Forecasting Regime Transitions

Vision Transformers in Chart Pattern Mining at Scale

Deep RL for ESG Portfolio Construction under Dynamic Constraints

Self-Supervised Embeddings for Company Similarity Search in Investment Screening

Transformers for Risk-on/Risk-off Signal Prediction

Contrastive Learning for Market Regime Detection

Diffusion Models in Option Pricing: Beyond Black-Scholes

Agentic AI for Treasury Management: Automating Cash Flow Decisions

Zero-Shot Transfer of Trading Strategies Across Asset Classes

Friday, July 04, 2025

Capsule Networks in Order Book Analysis: 3D Views of Liquidity Walls

The world of finance is ever-evolving, and with it, the ways we analyze and interpret market data must also adapt. In recent years, machine learning has emerged as a game-changer … Read More

Building a Crypto Quant Fund with Deep RL Agents

In the ever-evolving world of cryptocurrencies, traditional finance strategies often fall flat in navigating the volatile landscape. This is where the allure of building a quant fund with Deep Reinforcement … Read More

Cross-Market Arbitrage with Multimodal AI: NLP + Price Action

In today’s fast-paced financial environment, staying ahead of the curve often requires innovative strategies and deep dives into vast amounts of data. One exciting approach that has gained significant traction … Read More

Risk Modeling with Diffusion Models: Replacing Monte Carlo with Generative AI

The financial landscape has always thrived on the accurate assessment of risks. This is especially true when it comes to Value at Risk (VaR) calculations, where precision and timeliness are … Read More

Anomaly Detection in Trading Volumes Using Self-Supervised Transformers

In the fast-paced world of trading, understanding fluctuations in trading volumes can prove essential for making informed decisions. Here, I want to explore a cutting-edge approach to anomaly detection in … Read More

Multi-Agent Reinforcement Learning in Market Simulations

Markets are chaotic, dynamic, and often unpredictable. Yet, within this apparent randomness lies an intricate web of behaviours, strategies, and interactions that can reveal valuable insights, especially when viewed through … Read More

RLHF in Finance: Using Human Feedback to Fine-Tune Trading Bots

In the ever-evolving landscape of finance and trading, traditional methods of algorithm development have transformed dramatically thanks to advancements in artificial intelligence (AI). One of the leading-edge approaches making waves … Read More

AutoML for Trading Strategy Discovery: Let the Machine Find the Alpha

In the ever-evolving world of finance, finding the next big trading strategy can feel like searching for a needle in a haystack. With markets moving faster than ever and traditional … Read More

Graph Neural Networks for Fraud Detection in Payment Networks

In the fast-evolving world of payment networks, the threat of fraud looms large, affecting businesses and consumers alike. Traditional methods of detecting fraudulent activity often fall short, grappling with the … Read More

Transformer Models for High-Frequency Tick Data Forecasting

In the ever-evolving world of finance, high-frequency trading (HFT) is at the forefront of innovation. The ability to predict price movements in real-time is paramount for traders looking to capitalize … Read More

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Recent Posts

  • Meta-Learning in Finance: Training Models That Learn to Trade Faster
  • Energy-Based Models for Forecasting Regime Transitions
  • Vision Transformers in Chart Pattern Mining at Scale
  • Deep RL for ESG Portfolio Construction under Dynamic Constraints
  • Self-Supervised Embeddings for Company Similarity Search in Investment Screening
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