Hi, I'm Arnav Sharma

Quantitative Researcher

Passionate about financial markets, algorithmic trading, and building sophisticated quantitative models to decode market behavior and optimize investment strategies.

black_scholes_model.py

import numpy as np

from scipy.stats import norm

 

def black_scholes(S, K, T, r, sigma):

  d1 = calculate_d1(S, K, T, r, sigma)

  return S * norm.cdf(d1)

About Me

I'm a quantitative researcher and developer specializing in financial modeling, algorithmic trading, and risk management. My work focuses on creating sophisticated mathematical models to understand market dynamics, price derivatives, and develop systematic trading strategies.

8+

Quant Models

1+

Years Experience

500+

Backtests Run

Quantitative Models

Black-Scholes Model

Complete implementation of the Black-Scholes option pricing model with Greeks calculation, volatility surface analysis, and real-time pricing for European options.

Python NumPy SciPy Matplotlib

Heston Stochastic Volatility Model

Advanced volatility modeling using the Heston model for option pricing with stochastic volatility, calibration algorithms, and Monte Carlo simulation methods.

Python QuantLib Pandas Monte Carlo

Monte Carlo Simulation Suite

Comprehensive Monte Carlo simulation framework for option pricing, portfolio optimization, and risk assessment with variance reduction techniques.

Python NumPy Numba Multiprocessing

Local Volatility Model

Advanced volatility modeling toolkit with implied volatility surface construction, term structure analysis, and volatility smile fitting algorithms.

Python SciPy Plotly Statistics

Streamlit Finance App

Interactive financial analysis application with real-time data visualization, multiple quantitative models, and user-friendly interface for financial calculations.

Python Streamlit Pandas Plotly

Model Comparison Framework

Comprehensive model comparison system for evaluating different quantitative finance models, performance metrics, and statistical analysis tools.

Python Statistical Analysis Model Validation Performance Metrics

Live Interactive Dashboard

Experience my quantitative finance models in real-time. Run Black-Scholes calculations, Monte Carlo simulations, and explore advanced option pricing models with live data visualization.

Interactive Quant Models

Click to explore live calculations

Launch Full Dashboard

Black-Scholes Model

Real-time option pricing with Greeks calculation

Monte Carlo Simulation

Stochastic modeling with path visualization

Live Visualization

Interactive charts and parameter controls

Model Comparison

Side-by-side analysis of different approaches

Research & Expertise

Options Pricing

Black-Scholes, Heston, and exotic options modeling with advanced numerical methods

Volatility Modeling

Stochastic volatility models, GARCH, and volatility surface construction

Monte Carlo Methods

Advanced simulation techniques with variance reduction and parallel computing

Interactive Applications

User-friendly financial tools and interactive dashboards for real-time analysis

Model Comparison

Statistical validation, performance metrics, and comprehensive model evaluation

Local Volatility

Advanced volatility modeling with local volatility surfaces and calibration techniques

Technical Skills

Programming Languages

Python R C++ SQL MATLAB JavaScript

Quantitative Libraries

NumPy SciPy Pandas QuantLib Streamlit Plotly

Financial Modeling

Black-Scholes Monte Carlo Heston Model Local Volatility Options Pricing Risk Modeling

Data & Visualization

Matplotlib Plotly Seaborn Interactive Dashboards Statistical Analysis Model Validation

Let's Collaborate

Ready to Build Something Great?

I'm always interested in discussing quantitative finance, algorithmic trading strategies, and innovative financial modeling projects. Let's connect and explore opportunities.