Capital Management
Ancova Volatility Optimizer Fund
AI-Driven Volatility Investing.
Ancova Volatility
Optimizer Fund
AI-Driven Volatility
Investing.
Harnessing artificial intelligence and proprietary strategies to deliver superior risk-adjusted returns in US equities and options markets.
Harnessing artificial intelligence and proprietary strategies to deliver superior risk-adjusted returns in US equities and options markets.
Executive Summary
Features
Features
Risk First. Returns Second. Compounding Always.
Risk First.
Returns Second. Compounding Always.
The Ancova Volatility Optimizer (AVO) Fund is a systematic equity and options strategy designed to deliver equity-like returns with lower volatility.
Backed by Ancova Investment DIFC Family Office and managed on the fully regulated Ancova Capital Management platform, AVO uses advanced AI, proprietary portfolio optimization, and machine learning to price securities efficiently while eliminating human bias
Risk First, Returns Second, Compounding AlwaysThe Ancova Volatility Optimizer (AVO) Fund is a systematic equity and options strategy designed to deliver equity-like returns with lower volatility.
Backed by Ancova Investment DIFC Family Office and managed on the fully regulated Ancova Capital Management platform, AVO uses advanced AI, proprietary portfolio optimization, and machine learning to price securities efficiently while eliminating human bias
Our Approach:
Our Approach:
Our disciplined approach aims to provide investors with S&P 500-like returns while reducing downside risk, creating a resilient, adaptive portfolio.
Our disciplined approach aims to provide investors with S&P 500-like returns while reducing downside risk, creating a resilient, adaptive portfolio.
Our disciplined approach aims to provide investors with S&P 500-like returns while reducing downside risk, creating a resilient, adaptive portfolio.
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2025 YTD Return
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17.7%, lower than benchmark
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Since inception annualized return
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Sharpe Ratio
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2025 YTD Return
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17.7%, lower than benchmark
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Since inception annualized return
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Sharpe Ratio
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2025 YTD Return
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17.7%, lower than benchmark
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Since inception annualized return
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Sharpe Ratio
Methodology
How it works
How it works
Methodology Highlights
Powerful Features. Zero Guesswork
Methodology
Highlights
Advanced Risk & Return Management
Simulation-Based Portfolio Construction
Monte Carlo frameworks model complex interactions between equities and options, generating robust strategies across diverse market scenarios.
Simulation-Based Portfolio Construction
Monte Carlo frameworks model complex interactions between equities and options, generating robust strategies across diverse market scenarios.
Simulation-Based Portfolio Construction
Monte Carlo frameworks model complex interactions between equities and options, generating robust strategies across diverse market scenarios.
Tail-Risk Control
CVaR optimization and downside modeling actively manage extreme loss scenarios, protecting portfolios during market stress events.
Tail-Risk Control
CVaR optimization and downside modeling actively manage extreme loss scenarios, protecting portfolios during market stress events.
Tail-Risk Control
CVaR optimization and downside modeling actively manage extreme loss scenarios, protecting portfolios during market stress events.
Ensemble AI Signal Processing
Multiple machine learning models aggregate diverse alpha signals, combining indicators, sentiment analysis, and pattern recognition for enhanced predictions.
Ensemble AI Signal Processing
Multiple machine learning models aggregate diverse alpha signals, combining indicators, sentiment analysis, and pattern recognition for enhanced predictions.
Ensemble AI Signal Processing
Multiple machine learning models aggregate diverse alpha signals, combining indicators, sentiment analysis, and pattern recognition for enhanced predictions.
Advanced Volatility Modeling
Stochastic volatility, skew, and kurtosis models capture the full distribution of returns, while dynamic correlation tracking adapts to changing market regimes.
Advanced Volatility Modeling
Stochastic volatility, skew, and kurtosis models capture the full distribution of returns, while dynamic correlation tracking adapts to changing market regimes.
Advanced Volatility Modeling
Stochastic volatility, skew, and kurtosis models capture the full distribution of returns, while dynamic correlation tracking adapts to changing market regimes.
The Problem
The Problem
The Problem
Traditional
Investment Challenges
Traditional
Investment
Challenges
Traditional equity exposure often ignores volatility drag and potential drawdowns. Risk is typically measured after losses occur, leaving investors exposed to sudden market swings. The Ancova Volatility Optimizer Fund addresses these challenges through:
Traditional equity exposure often ignores volatility drag and potential drawdowns. Risk is typically measured after losses occur, leaving investors exposed to sudden market swings. The Ancova Volatility Optimizer Fund addresses these challenges through:
01
Downside protection and Volatility modeling
Risk is actively managed through continuous Volatility analysis and downside-focused controls.
02
Dynamic portfolio construction using Derivatives
Exposure is adjusted dynamically using options and derivatives to improve risk efficiency.
03
A liquid alternative to traditional equities
Provides equity-like exposure with daily liquidity and improved risk control.
04
Core diversifying growth allocation
After a smooth launch, we monitor performance and provide support to ensure your product continues to deliver value over time.
01
Downside protection and Volatility modeling
Risk is actively managed through continuous Volatility analysis and downside-focused controls.
02
Dynamic portfolio construction using Derivatives
Exposure is adjusted dynamically using options and derivatives to improve risk efficiency.
03
A liquid alternative to traditional equities
Provides equity-like exposure with daily liquidity and improved risk control.
04
Core diversifying growth allocation
After a smooth launch, we monitor performance and provide support to ensure your product continues to deliver value over time.
01
Downside protection and Volatility modeling
Risk is actively managed through continuous Volatility analysis and downside-focused controls.
02
Dynamic portfolio construction using Derivatives
Exposure is adjusted dynamically using options and derivatives to improve risk efficiency.
03
A liquid alternative to traditional equities
Provides equity-like exposure with daily liquidity and improved risk control.
04
Core diversifying growth allocation
After a smooth launch, we monitor performance and provide support to ensure your product continues to deliver value over time.
Our Investment Strategy & USP
The Problem
The Problem
Advanced, Adaptive,
AI-Powered Strategy
Advanced, Adaptive,
AI-Powered Strategy
AVO employs a multi-layered investment framework, integrating AI-driven signals, proprietary simulations, and machine learning models to forecast returns and identify alpha opportunities. The fund dynamically adjusts exposure and uses derivatives prudently to optimize risk-adjusted returns.
AVO employs a multi-layered investment framework, integrating AI-driven signals, proprietary simulations, and machine learning models to forecast returns and identify alpha opportunities. The fund dynamically adjusts exposure and uses derivatives prudently to optimize risk-adjusted returns.
AI & Automation
Proprietary models reduce human and automate decisions.
AI & Automation
Proprietary models reduce human and automate decisions.
AI & Automation
Proprietary models reduce human and automate decisions.
Liquidity
Volatility modeling and tail-risk control minimize drawdowns.
Liquidity
Volatility modeling and tail-risk control minimize drawdowns.
Liquidity
Volatility modeling and tail-risk control minimize drawdowns.
Non-Directional
Outperforms S&P 500 historically with lower volatility.
Non-Directional
Outperforms S&P 500 historically with lower volatility.
Non-Directional
Outperforms S&P 500 historically with lower volatility.
Agile Management
Adapts dynamically to changing markets.
Agile Management
Adapts dynamically to changing markets.
Agile Management
Adapts dynamically to changing markets.
Transparent Reporting
Investors receive comprehensive updates and analytics.
Transparent Reporting
Investors receive comprehensive updates and analytics.
Transparent Reporting
Investors receive comprehensive updates and analytics.
Data-Driven Edge
Continuous innovation ensures long-term fund resilience.
Data-Driven Edge
Continuous innovation ensures long-term fund resilience.
Data-Driven Edge
Continuous innovation ensures long-term fund resilience.
Performance
The Problem
The Problem
Performance
Snapshot
Since 2017, AVO has generated compelling risk-adjusted returns, achieving 28.90% in 2025 and consistently outperforming traditional benchmarks. Our multi-layered AI framework adapts dynamically to market regimes, delivering alpha through both rising and falling markets while maintaining disciplined risk controls.
Since 2017, AVO has generated compelling risk-adjusted returns, achieving 28.90% in 2025 and consistently outperforming traditional benchmarks. Our multi-layered AI framework adapts dynamically to market regimes, delivering alpha through both rising and falling markets while maintaining disciplined risk controls.
Since 2017, AVO has generated compelling risk-adjusted returns, achieving 28.90% in 2025 and consistently outperforming traditional benchmarks. Our multi-layered AI framework adapts dynamically to market regimes, delivering alpha through both rising and falling markets while maintaining disciplined risk controls.
Since 2017, AVO has generated compelling risk-adjusted returns, achieving 28.90% in 2025 and consistently outperforming traditional benchmarks. Our multi-layered AI framework adapts dynamically to market regimes, delivering alpha through both rising and falling markets while maintaining disciplined risk controls.
PROP TRADING AND MODEL VALIDATION BY DELOITTE
PROP TRADING AND MODEL VALIDATION BY DELOITTE
AVO FUND LIVE TRADING. AUDITED TRACK RECORD
AVO FUND LIVE TRADING. AUDITED TRACK RECORD
Performance
The Problem
The Problem
AVO’s
Journey
AVO’s journey combines quantitative research, proprietary modeling, and systematic trading:
AVO’s journey combines quantitative research, proprietary modeling, and systematic trading:
Fund inception and research start
Self-funded pilot trading with USD 500,000
Algorithm development and model enhancements
Partnership with Ancova Investments Family Office, launching AVO as a CIMA-regulated fund
Progressive pilot years, achieving 10–28.9% returns with low volatility
Strategy & Investment Team
The Problem
Our Team
Meet Our
Experienced Team
Ronnie Chowdhury
BSc Comp Sci (UCL) MRes Comp Sci & AI (UCL) Head of Metal Derivatives - Deutsche Bank 2012 2017 25+ years quant & AI modelling experience Credit Suisse, Barclays Capital, RBS, BNP Paribas and Citigroup
Ronnie Chowdhury
BSc Comp Sci (UCL) MRes Comp Sci & AI (UCL) Head of Metal Derivatives - Deutsche Bank 2012 2017 25+ years quant & AI modelling experience Credit Suisse, Barclays Capital, RBS, BNP Paribas and Citigroup
Ronnie Chowdhury
BSc Computer Science (UCL) MRes Computer Science & AI (UCL) Head of Metal Derivatives - Deutsche Bank 2012 2017 25+ years quant & AI modelling experience Credit Suisse, Barclays Capital, RBS, BNP Paribas and Citigroup
Anthony Silver
BSc in Mathematics and Computer Science (University of Melbourne) Expertise: AI, Optimization, mathematics and portfolios modelling Extensive experience at banks and hedge funds: Barclays Capital, BNP Paribas, Citigroup
Anthony Silver
BSc in Mathematics and Computer Science (University of Melbourne) Expertise: AI, Optimization, mathematics and portfolios modelling Extensive experience at banks and hedge funds: Barclays Capital, BNP Paribas, Citigroup
Anthony Silver
BSc in Mathematics and Computer Science (University of Melbourne) Expertise: AI, Optimization, mathematics and portfolios modelling Extensive experience at banks and hedge funds: Barclays Capital, BNP Paribas, Citigroup
Andrew Bradley
MSc Computer Science & Mathematics (Manchester) System architecture and data engineering 25+ years experience of working as IT in large banks Old Lane, DB, Credit Suisse, Barclays Capital, BNP Paribas and Capula
Andrew Bradley
MSc Computer Science & Mathematics (Manchester) System architecture and data engineering 25+ years experience of working as IT in large banks Old Lane, DB, Credit Suisse, Barclays Capital, BNP Paribas and Capula
Andrew Bradley
MSc Computer Science & Mathematics (Manchester) System architecture and data engineering 25+ years experience of working as IT in large banks Old Lane, DB, Credit Suisse, Barclays Capital, BNP Paribas and Capula
Simon Kaufmann
BSc (Hons) Economics and Finance (University of Melbourne) Portfolio Manager at various organizations in Australia covering finance and telecommunications. Expertise in data engineering, quant modelling and AI.
Simon Kaufmann
BSc (Hons) Economics and Finance (University of Melbourne) Portfolio Manager at various organizations in Australia covering finance and telecommunications. Expertise in data engineering, quant modelling and AI.
Simon Kaufmann
BSc (Hons) Economics and Finance (University of Melbourne) Portfolio Manager at various organizations in Australia covering finance and telecommunications. Expertise in data engineering, quant modelling and AI.