Stranum's Market Making Algorithm uses long calendar spreads for trading index fund options

Offers low cost exposure to the market using highly liquid index options such as SPY, and QQQ while minimizing risks related to market downturns and volatility spikes.

Key Features

Trades option on highly liquid index ETFs like SPY and QQQ
Ensures tight bid-ask spread and efficient pricing.

A digital stock market ticker displaying the SPY index value at 452.65, alongside a graphical representation of market performance with green and red indicators. The numbers 2.16 and 0.48% suggest a percentage change. The image uses bright LED-like dots for visual impact against a dark background.

Buys longer-term options and sells shorter-term options
Matches strike prices to create calendar spreads at or near the current market price (ATM).

Allocates hedging exposure proportionately across portfolio holdings, targeting specific sectors or indices relevant to the portfolio's composition.

Inputs and Parameters

The algorithm optimizes the Theta decay differential between long and short options to maximize profitability.
Sets rules for rolling over short-term options to the next expiry to maintain the spread.

Risk Tolerance

Defines maximum capital allocation per trade and overall hedge exposure as a percentage of portfolio value.

A digital stock trading interface with the focus on AMC Entertainment Holdings, Inc. The screen displays various financial data including stock prices, volume, and market cap. A red line graph shows stock performance over time and several buttons allow for different time frame selections like 1W, 1M, and 1Y. Various stock metrics appear in rows and columns.

Volatility Metrics

Tracks implied volatility (IV) levels to identify favorable entry points, e.g. low IV for long options purchase trigger.

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Trade Execution

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Algorithm initiates trades when IV skew is favorable, indicating potential profitability from time decay.

Calculates optimal contract size based on portfolio size, delta, and risk limits.

Uses historical IV percentiles to determine underpriced options.

Monitors short-term options nearing expiry and rolls them forward to maintain the spread and manage exposure.

A laptop displays a financial trading platform with a candlestick chart showing stock market data. The chart is colorful, with blue and orange bars representing volume, and fluctuating lines indicating stock prices over time. Surrounding the laptop are two small potted plants on a white surface.

Performance Monitoring

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Integration with Portfolio Management

Separately tracks realized and unrealized gains from calendar spreads.
Measures the algorithm's impact on overall portfolio volatility and hedge effectiveness.
Continuously backtests using historical data to refine entry/exit criteria and improve returns.

The algorithm adjusts hedging based on changes in portfolio composition, size, and market conditions.
Uses real-time market data feeds to adapt to changes in volatility, pricing, and liquidity.

Backtest

Please refer to the worst case scenario backtest. The Stranum Algorithm is constantly improved to ensure a systematic, data-driven hedging mechanism that enhances portfolio resilience against market volatility while taking advantage of time decay and IV volatility. Alternatively, it can be used as a stand-alone tool for outstanding ROI.

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