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We are data driven, applying deep statistical analysis to find alpha.
We are data driven, applying deep statistical analysis to find alpha.
Our analysis does not "predict" the market, it identifies positive expectancy.
Our analysis does not "predict" the market, it identifies positive expectancy.
This means we use repeatable trades, that over hundreds of occurrences, return more than they lose.
This means we use repeatable trades, that over hundreds of occurrences, return more than they lose.
RISK MANAGEMENT IS THE CORNERSTONE OF OUR BUSINESS
RISK MANAGEMENT IS THE CORNERSTONE OF OUR BUSINESS
Monte Carlo Test
Monte Carlo Test
Tail Risk Correlation
Tail Risk Correlation
At Premium Traders, we believe that alpha is found in the data, but preserved through rigorous risk architecture. This allows our investment team to move beyond traditional P&L tracking.
By utilizing Monte Carlo simulations and Walk-Forward analysis we stress-test every strategy against thousands of market scenarios before a single dollar is deployed. Our commitment to this block-based architecture ensures that our risk is never centralized and our performance is always verifiable.
Alpha Decomposition / Modular Architecture / Tail Risk Mitigation
Alpha Decomposition / Modular Architecture / Tail Risk Mitigation
Strategy Siloing: Each alpha source is managed as a distinct data block to prevent cross-contamination.
Principle Component Analysis: Distilling down to a small set of uncorrelated variables called Principal Components.
Probabilistic Certainty: Monte Carlo and Walk Forward Analysis allows us to look at thousands of possible scenarios, not just the actual historic outcomes.
Diversification: We combine multiple uncorrelated strategies to reduce portfolio drawdowns and create steady returns.
Tail Risk Mitigation: Real-time correlation matrices ensure our portfolio remains truly diversified.
Strategy Sizing: We size our trades so that our overall portfolio adheres to our goals for CAGR, maximum drawdown, and volatility using a combination of Kelly Criterion, Monte Carlo, and Tail Risk Correlation.
Data Driven Trade Modelling
Data Driven Trade Modelling
Our investment process is based on advanced backtesting models and volatility analysis. We have access to the full history of S&P 500 options pricing, from 2013 to present, on a minute-by-minute basis.
By no means can we predict what will happen in the future, but testing historical data gives us insight into what might happen under various market conditions.
Although the company was only established in 2022, we used the historical data to see how our strategies may have performed over the last 6 years. In this example, the backtest shows an average annual return of 31% (yellow line), compared to the overall US market (blue line) annual return of 12%.
These tests also help us understand how our strategies perform in changing market conditions.
Covid Crash
Covid Crash
Every market event is unique, but we are often asked how our strategies performed through Covid.
While the company was not established until 2022, we used the historical price data to see what might have happened through the Covid crash of 2020.
While the US stock market dropped 30%, this strategy remained essentially ‘flat’, and then continued to be profitable post-Covid.
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