Pratham Malviya

Advisor

Kharagpur, West Bengal, India3 yrs 7 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Developed successful trading strategies with high returns.
Led a nationwide event attracting over 3000 participants.
Created advanced models achieving high accuracy in predictions.

Stackforce AI infers this person is a Fintech professional with expertise in quantitative finance and machine learning.

Contact

Skills

Core Skills

Quantitative FinanceTrading StrategiesEquity TradingMachine LearningData Analysis

Other Skills

ARIMAAlpha creationAnalytical SkillsArbitrage strategiesBacktestingC (Programming Language)C++Content curationData VisualizationDeep LearningDerivativesDeveloped trading strategiesEconometricsEvent managementFinance

About

I’m an undergrad with a passion for building statistical trading models and applying ML and deep learning in finance. Always up for new challenges and eager to learn. If you're into quant research, trading, and risk management, let’s connect and chat! Open to work!

Experience

Inter iit tech meet 13.0

Contingent Member

Oct 2024 – Dec 2024 · 2 mos · Mumbai, Maharashtra, India

Quant club, iit kharagpur

3 roles

Advisor

Sep 2024 – Present · 1 yr 6 mos · Kharagpur, West Bengal, India

Executive Head & Senior Quant Researcher

Promoted

Sep 2023 – Aug 2024 · 11 mos · Kharagpur, West Bengal, India

Developed and backtested trading strategies in equity and derivatives segments for multiple companies as a member of the club
Led "Summer of Quant", attracting 3000+ participants nationwide, curated content on Stock Market and Derivatives fundamentals

Developed trading strategiesBacktestingEquity tradingDerivativesQuantitative FinanceTrading Strategies

Associate Quant Researcher

Jul 2022 – Sep 2023 · 1 yr 2 mos · Kharagpur, West Bengal, India

• Engaged in paper trading equities in Indian and US markets and cryptocurrency futures, focused on technical analysis and price action

Paper tradingTechnical analysisPrice actionEquity Trading

Inter iit tech meet 12.0

Contingent Member

Nov 2023 – Dec 2023 · 1 mo · Chennai, Tamil Nadu, India · On-site

Sportshedge : sports stock exchange

Quantitative Researcher

Aug 2023 – Nov 2023 · 3 mos · Bengaluru, Karnataka, India · Remote

Modeled advanced scoring and pricing models for cricket players using variance shrinkage techniques based on average performance
Contributed to risk models for Dynamic Asset Issuance and Tactical Risk Allocation, targeted market-making and risk management
Incorporated Exchange Traded Funds (ETF) for players basket, leveraging arbitrage strategies to manage and mitigate exchange risks

Time line investments

Data Analyst

Jun 2023 – Oct 2023 · 4 mos · Bengaluru, Karnataka, India · Remote

Analyzed NIFTY and BANKNIFTY options trades with LSTM and ARIMA model to gain insights on trading patterns, volatility trends
Evaluated trade profitability assessment for multiple expiries, used random forest algorithm for risk evaluation of +100 trades a month
Designed a Python-based GUI to automate trades analysis reports for house trades, reducing manual processing time by over 50%

Scoring modelsRisk modelsArbitrage strategiesQuantitative Finance

Worldquant

Research Consultant

May 2023 – Present · 2 yrs 10 mos · Remote

Created alphas by using a variety of data sources, including fundamental metrics, price-volume, analyst reports, and sentiment analysis
Attained a maximum Sharpe ratio of 2 and a 17.5% return through a momentum-based trading strategy applied to top 3000 US stocks
Tested over 100 alphas and selected 23 for out-sample testing, which yielded an average Sharpe ratio of 1.45 and a 13% return

Alpha creationData analysisSentiment analysisSharpe ratio optimizationQuantitative FinanceMachine Learning

Indian school of business

Research Intern

May 2023 – Jul 2023 · 2 mos · Hyderabad, Telangana, India · Remote

Designed and deployed facial expression identifier Web App using Streamlit, showcasing user-friendly design & seamless functionality
Formed ensembled sophisticated models, including RetinaFace, MobileNet, and MTCNN, achieving 92.47% accuracy & 0.98 F1 score
Enhanced the user experience with interactive and dynamic graph visualizations, combining technical proficiency & data presentations

Data analysisLSTMARIMAPython GUI designData Analysis