Hashbrown Systems Private Limited.

Financial Services

Software Engineering & Quantitative Services for Trade Automation & Risk Management

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Redefine Market Performance with a Team of Experienced Mathematicians, Statisticians, and Data Scientists.

Partner with a Team of Seasoned Professionals in Data Science, Statistical Modelling, and Advanced Analytics to Strengthen Your Trade Execution, Manage Market Risk, and Optimize Portfolio Strategies.

We provide financial institutions, market advisories, and asset managers with direct access to a team of data scientists, developers, and analysts who have worked on mission-critical problems in trade automation across NASDAQ, NSE, and NYSE. Our expertise spans pre-trade, at-trade, and post-trade risk management, helping firms navigate complex financial markets with confidence.

Team

What We Do

Our primary work focuses on risk management, data validation, and trade execution analytics, delivering precise real-time signals and indicators.

Implementing real-time validation checks to mitigate execution risks.

Cleaning and structuring large datasets from multiple sources.

Developing algorithms that adapt to market conditions.

Providing tools to assess and adjust asset allocations dynamically.

Offering a holistic view of risk across markets and asset classes.

What We Do

Gaussian Mixture Model (GMM):

Identifies clusters in financial data, helps to determine market regimes and calculate threshold levels for indicators.

GMM

Hidden Markov Model (HMM):

Uncovers hidden market states (e.g., bull/bear trends) and models time-series dependencies in stock prices.

HMM

Smooth Splines Regression:

Handles noisy market data by smoothing fluctuations and capturing long-term trends for better decision-making.

Regression

Quantitative Models for Risk Management

We leverage a range of statistical and machine learning models to analyze market conditions, improve trade execution, and optimize risk management strategies.

Some of the core models we employ include:

Monte Carlo Simulations:

Used for portfolio risk estimation and stress testing by simulating various market conditions and asset price movements.

Simulations

Bayesian Networks:

Models dependencies between financial variables to assess risk scenarios and update probabilities dynamically.

Networks

GARCH (Generalized Autoregressive Conditional Heteroskedasticity):

Measures volatility clustering to estimate future market risk.

GARCH

PCA (Principal Component Analysis):

Reduces dimensionality in large datasets, helping to identify principal factors that drive market movements.

PCA

AI-Driven Insights for Market Opportunities & Risk Management

We integrate AI, Large Language Models (LLMs), Machine Learning (ML), and Deep Learning into our financial engineering solutions to help you navigate complex markets with precision. Our models analyze vast amounts of market data, uncover hidden patterns, and enhance decision-making for both buy-side and sell-side firms.

How We Apply AI & ML in Finance:

  • Predictive Market Analytics

    Using ML models to anticipate price movements and trading opportunities.

  • Analytics
  • LLM-Powered Market Sentiment Analysis

    Extracting insights from financial news, reports, and earnings calls to assess market sentiment.

  • Analysis
  • Deep Learning for Anomaly Detection

    Identifying irregular trading patterns and potential market disruptions.

  • AI-Enhanced Portfolio Optimization

    Automating real-time trade validation and error detection to mitigate operational risks.

  • Algorithmic Risk Management

    Automating real-time trade validation and error detection to mitigate operational risks.

    Lines
  • Lines

By leveraging advanced AI and statistical modelling, we help you reduce uncertainty, manage risk, and capitalize on market opportunities in real time.

Men

How We Work

We combine technology and market expertise to process thousands of securities daily, identifying patterns, anomalies, and trading opportunities based on robust financial models. By integrating data science with real-world trading environments, we help firms reduce operational risk and improve decision-making.

If you’re looking for a team that understands the nuances of trade automation and financial risk, we’re here to help.

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Data Sources and Market Apis that we have worked on

We work with complex datasets from trusted global providers and transform raw market data into actionable insights for algorithmic trading, risk modeling, and portfolio optimization.

  • DX Feed

    DX Feed

  • Yahoo Finance

    Yahoo Finance

  • Zerodha

    Zerodha

  • Tiingo

    Tiingo

  • Kibot

    Kibot

  • Intrinio

    Intrinio

  • Interactive Brokers

    Interactive Brokers

  • Tradier

    Tradier

  • TrueData

    TrueData

Financial Data Engineering

Building the Foundation for Smarter Trading and Structuring data for downstream analysis and reporting.

Modern financial markets run on data, and financial data engineering is at the core of efficient trade automation, risk management, and AI-driven analytics. Our expertise lies in designing and optimizing data infrastructures that power high-frequency trading, market risk analysis, and quantitative investment strategies.

We help financial institutions, hedge funds, and market advisories structure, process, and analyze vast amounts of market data, ensuring seamless integration with algorithmic trading, AI models, and real-time decision systems.

Analysis & Reporting

  • Market Data Pipeline Development

    Aggregating, cleaning, and structuring data from multiple exchanges, including NASDAQ, NYSE, and NSE.

  • AI-Integrated Data Workflows

    Deploying machine learning and deep learning models for trade execution and risk assessment.

  • LLM-Powered Financial Intelligence

    Extracting insights from financial reports, earnings calls, and regulatory filings.

  • Real-Time Data Processing & Validation

    Ensuring accuracy, consistency, and reliability for trading strategies and market execution.

  • Custom Risk & Compliance Infrastructure

    Automating pre-trade, at-trade, and post-trade risk management processes.

  • Cloud-Based Scalable Architectures

    Implementing high-performance financial data ecosystems using cloud and on-premise solutions.

Our team of data engineers, quants, and software architects works closely with clients to design, implement, and optimize data pipelines that empower data-driven trading, AI-driven risk models, and real-time portfolio analytics and bridge the gap between data science, market intelligence, and trade execution,

Presentation

Financial Engineering & Risk Management Presentation

A comprehensive look at how data science, quantitative modeling, and AI-driven analytics are shaping trade automation and risk management.

Get insights into how our team applies statistical models, machine learning, and financial data engineering to enhance decision-making and reduce market risk.

Latest Posts

Contact Us

We are constantly evolving, innovating and creating new products and services. If you have a specific problem that needs attention or you would just like to understand more about the scientific methods we employ, drop us a message and we will get back to you.

Hashbrown Systems is always at your beck and call.

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Careers

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