Trading — Eshanthsai Vanam

*This is a brief overview. For alpha preservation, the exact strategy parameters are confidential, but applications can be provided given the listed mechanisms.

Proprietary Prop Firm Empire

3 Uncorrelated systematic strategies combined into a capital-efficient prop firm portfolio

Research → Backtest → Forward Test → Live Deployment

Multi-Strategy Portfolio Uncorrelated systematic strategies optimized for prop firm passes

Bootstrapped Monte Carlo Stress-tested across thousands of return paths

Custom Prop Firm Simulators Optimizes pass time, cost per pass, and EV

Multi-Account Scaling Capital-efficient diversification across funded accounts

*Figures displayed are for illustrative purposes. Slight discrepancies may exist due to data timing, rounding, and simulation parameters.

AI Quantitative Research Assistant

60–75% Time saved on the full systematic strategy development cycle

Automated Bias Audit 45-item rubric hard gate

OOS Validation Auto-flags overfitting

Monte Carlo 10K block-bootstrap paths

Prop Firm Simulator FTMO, The5ers, full risk sweep

Condition Analysis 9 regime templates

Statistical Testing Relationship validation

AI Quantitative Research Assistant Display

In Development

SPY / TLT Rebalancing Strategy

Takes advantage of institutional end-of-month rebalancing flows between stocks (SPY) and bonds (TLT). The edges (displayed via scatterplot & regression) show various relationships, such as end-of-month vs start-of-month relative performance (SPY - TLT), that make this strategy successful. The initial backtest, without seasonality analysis and edge refinement, yielded a Sharpe ratio of ~0.97, which was significantly improved as shown below. Over 275 trades were executed.

Idea → Stat Tests → Backtest → Seasonality Analysis → Backtest

16.4% CAGR

1.44 Sharpe Ratio

2011–2025 Data Sample

QQQ / TQQQ Rebalancing Strategy

Takes advantage of end-of-day rebalancing protocols on TQQQ (3x Leveraged QQQ) on ≥ 1% days. The edge (displayed via scatterplot & regression) is tailored after structured seasonality analysis. For alpha preservation, further bar charts and strategy parameters are undisclosed. 800+ trades were executed.

Idea → Stats Test → Backtest → Seasonality Analysis → Stats Test → Backtest

>23.86% CAGR

>1.12 Sharpe Ratio

2011–2025 Data Sample

ES & NQ Futures Intraday System

Takes advantage of intraday orderflow mechanisms on primarily E-Mini S&P 500 (ES) and E-mini Nasdaq-100 (NQ) Futures. This discretionary trading system takes advantage of higher context via technical, fundamental, and orderflow analysis.

Fundamental Analysis

Monitoring financial news, leveraging earnings data, and keeping economic information into consideration.

Technical Analysis

Supply/Demand, liquidity levels, Fibonacci retracements, fair-value-gaps, and other key levels.

Orderflow Tools

Volume profile, footprint (Bid/Ask Cluster) charts, bookmap (DOM Heatmap) charts, and corresponding levels from those tools.

Orderflow Mechanisms

Clustered Limit Order Urgency for Directional Continuation
Clustered Market Order Absorption (Delta) for Directional Shifts
Irregular Size Limit Orders for Directional Reaction
Large/Extended Clustered Limit Order for Directional Targets

~1.95 Avg R/R

~1.67 Sharpe Ratio

~62% Win Rate

1 ES Mini Avg Risk Size

Certificate

Showcases extraordinary performance from being able to pass a proprietary firm challenge on a $50,000 simulated trading account.

Trading Analysis

Showcases trading analysis of one of the mentioned orderflow mechanisms. More videos on @TheV2Trading YouTube channel.

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