Historical Option Prices: How to Access, Analyze, and Use Past Options Data

Historical option prices are among the most valuable data sets available to options traders. While most platforms focus on real-time quotes and live option chains, the ability to look back at how option prices behaved in the past unlocks a completely different level of analysis. Whether you want to backtest a trading strategy, study how implied volatility behaves around earnings announcements, analyze historical premium levels for covered call writing, or validate a pricing model, historical option prices are the foundation. In this comprehensive guide, you will learn why historical option data matters, where to find it, how to pull it into Excel using MarketXLS, and how to apply it to practical trading scenarios.

Why Historical Option Prices Matter

Backtesting Trading Strategies

The single most important use of historical option prices is strategy backtesting. Before risking real capital on an options strategy, you want to know how it would have performed in the past under different market conditions.

For example, if you want to sell weekly put options on a stock, historical data lets you examine:

• What premium was available at various strike prices over the past year
• How often the options expired in the money (resulting in assignment)
• What the total profit or loss would have been across all trades
• How the strategy performed during high-volatility periods versus calm markets

Without historical option prices, strategy backtesting is impossible. You would be forced to forward-test with real money, which is both risky and slow.

Implied Volatility Analysis

Historical option prices allow you to reconstruct historical implied volatility (IV) levels. Since option prices embed the market's expectation of future volatility, tracking how IV changes over time reveals critical trading patterns:

• IV rank: Where current IV sits relative to its historical range (e.g., "IV is at the 85th percentile of its 52-week range")
• IV around events: How implied volatility typically behaves before and after earnings announcements, FDA decisions, or economic releases
• Volatility mean reversion: IV tends to revert to its historical average, creating trading opportunities when it is unusually high or low
• Term structure dynamics: How the IV curve across different expiration dates changes over time

Premium Decay Analysis

Options lose value as they approach expiration due to time decay (theta). Historical data lets you study:

• The rate of premium decay for different types of options
• Whether certain days of the week or times of the month show faster decay
• How decay interacts with underlying price movements

Risk Management

Historical option prices help you calibrate risk management parameters:

• What is the maximum drawdown a particular strategy experienced?
• How wide do option spreads need to be to avoid excessive losses?
• What delta range provides the best risk-reward balance historically?

How to Access Historical Option Prices in Excel

MarketXLS provides several functions for accessing both historical and current option data directly in Excel.

Getting Historical Option Prices with QM_GetHistory

The =QM_GetHistory() function retrieves end-of-day historical prices for any option contract. To use it, you need the option symbol in the standard format:

=QM_GetHistory("@AAPL 250321C00200000")

This returns the historical price data for the AAPL March 21, 2025, $200 call option.

The option symbol format is: @TICKER YYMMDD[C/P]SSSSSSSSS

• @ prefix identifies it as an option
• TICKER is the underlying stock symbol
• YYMMDD is the expiration date
• C for call, P for put
• SSSSSSSSS is the strike price multiplied by 1,000 (padded to 8 digits)

Getting Historical Prices with GetHistory

You can also use =GetHistory() with date range parameters:

=GetHistory("@AAPL 250321C00200000", "2024-06-01", "2025-03-01", "Daily")

This returns daily historical prices between the specified dates.

Getting Current Option Chains

To see all available options for a stock at current prices, use:

=QM_GetOptionChain("AAPL")

This returns the complete option chain including all available expirations and strike prices with current bid, ask, volume, open interest, and Greeks.

For S&P 500 index options:

=QM_GetOptionChain("^SPX")

Building Option Symbols

Use =OptionSymbol() to construct option symbols programmatically:

=OptionSymbol("AAPL", "2025-06-20", "C", 200)

This returns @AAPL 250620C00200000, which you can then pass to =QM_Last() for current prices or =QM_GetHistory() for historical prices.

Getting Current Option Prices

For real-time option quotes:

=QM_Last("@AAPL 250620C00200000")

This returns the last traded price for the specified option contract.

Getting Option Greeks and Detailed Quotes

For comprehensive option data including all Greeks:

=QM_GetOptionQuotesAndGreeks("AAPL")

This returns bid, ask, last price, volume, open interest, delta, gamma, theta, vega, rho, and implied volatility for all available contracts.

Historical Option Price Data: What Is Included

When you retrieve historical option prices, the data typically includes:

Understanding Option Price Components

Historical option prices reflect several factors at the time of the trade:

1. Intrinsic value: The amount the option is in the money (strike vs. stock price)
2. Time value (extrinsic value): The premium above intrinsic value, driven by time to expiration and implied volatility
3. Implied volatility: The market's expectation of future price movement embedded in the option price
4. Interest rates: The cost of carry component
5. Dividends: Expected dividend payments between now and expiration

When analyzing historical prices, it is important to consider what was driving the price at each point in time. A high option price might reflect high implied volatility rather than the option being deep in the money.

Practical Applications of Historical Option Data

Application 1: Covered Call Backtesting

Covered call writing is one of the most popular options strategies. Historical data lets you evaluate:

Step 1: Pull historical stock prices:

=GetHistory("AAPL", "2023-01-01", "2025-01-01", "Daily")

Step 2: For each month, find the option that was approximately 5% out of the money:

=OptionSymbol("AAPL", "2024-02-16", "C", 195)

Step 3: Get the historical premium received:

=QM_GetHistory("@AAPL 240216C00195000")

Step 4: Track outcomes — did the option expire worthless (keep premium), or was the stock called away? Calculate total return including premium received and any capital gains or losses.

By repeating this analysis across many months, you can determine:

• Average monthly premium collected as a percentage of the stock price
• Win rate (percentage of months the option expired worthless)
• Total return versus simply holding the stock
• Performance during high-volatility versus low-volatility periods

Application 2: Implied Volatility Study Around Earnings

Earnings announcements are among the most predictable volatility events. Historical option prices reveal consistent patterns:

Step 1: Identify earnings dates for the past two years

Step 2: Pull option prices for the at-the-money straddle 30 days before, 7 days before, and 1 day before each earnings date:

=QM_GetHistory("@AAPL 240726C00220000")

Step 3: Calculate the implied volatility from these prices using a pricing model

Step 4: Analyze patterns:

• IV typically rises steadily into earnings (the "IV ramp")
• IV drops sharply after the announcement (the "IV crush")
• The magnitude of the IV crush varies by stock and quarter
• Understanding these patterns helps you time volatility trades

Application 3: Put Spread Risk Analysis

Vertical put spreads are popular defined-risk strategies. Historical data helps you calibrate spread width and strike selection:

Step 1: Pull historical data for puts at various strike prices:

=QM_GetHistory("@SPY 241220P00550000")
=QM_GetHistory("@SPY 241220P00540000")

Step 2: Calculate the historical spread value at entry and at expiration

Step 3: Determine the probability of profit based on how often the underlying remained above the short strike

Step 4: Optimize strike selection based on historical win rates and average profit/loss

Application 4: Volatility Skew Analysis

Volatility skew refers to the pattern where out-of-the-money puts typically have higher implied volatility than out-of-the-money calls. Historical data lets you:

• Track how skew changes over time
• Identify periods of extreme skew (potential trading opportunities)
• Compare current skew to historical averages
• Analyze skew behavior before and after major market events

Historical Option Data Methods Comparison

Different approaches to obtaining and using historical option data:

MarketXLS offers a significant advantage for Excel-based traders because the data flows directly into your spreadsheet where you can immediately apply formulas, build models, and create visualizations without any data import or formatting steps.

Building an Options Analysis Spreadsheet

Basic Options Tracker

Create a spreadsheet that tracks your options positions with real-time data:

Column A: Option Symbol (built with =OptionSymbol())

=OptionSymbol("AAPL", "2025-06-20", "C", 200)
=OptionSymbol("MSFT", "2025-06-20", "P", 400)
=OptionSymbol("AMZN", "2025-07-18", "C", 200)

Column B: Current Price

=QM_Last("@AAPL 250620C00200000")
=QM_Last("@MSFT 250620P00400000")
=QM_Last("@AMZN 250718C00200000")

Column C: Entry Price (manually entered)

Column D: P&L per contract

= (B2 - C2) × 100

Column E: Underlying Current Price

=Last("AAPL")
=Last("MSFT")
=Last("AMZN")

Greeks Dashboard

Build a dashboard that shows real-time Greeks for all positions:

=QM_GetOptionQuotesAndGreeks("AAPL")

This returns comprehensive data including delta, gamma, theta, vega, and implied volatility for every available AAPL option contract. Use this to:

• Monitor your portfolio's net delta (directional exposure)
• Track theta (daily time decay in your favor or against you)
• Watch vega (sensitivity to implied volatility changes)
• Manage gamma risk around expiration

Historical Comparison Tool

Create a tool that compares current option prices to historical averages:

Step 1: Get current at-the-money option price:

=QM_Last("@AAPL 250620C00220000")

Step 2: Get the same relative option price from past periods:

=QM_GetHistory("@AAPL 240621C00195000")

Step 3: Calculate whether current premiums are above or below historical averages, indicating whether options are relatively expensive or cheap.

Options Data Quality Considerations

Bid-Ask Spread Impact

Historical option prices typically reflect the last traded price or the settlement price, not the mid-market price. For illiquid options with wide bid-ask spreads, the last traded price may not accurately represent the fair value. When backtesting:

• Use mid-market estimates (average of bid and ask) when possible
• Add realistic slippage to your backtest assumptions
• Focus on liquid options (high volume, tight spreads) for more reliable analysis

Corporate Actions

Stock splits, mergers, special dividends, and spin-offs can create adjusted option contracts with non-standard terms. Historical prices for these adjusted options may look unusual unless you account for the corporate action. Always check whether an option symbol represents a standard or adjusted contract.

Expiration and Exercise

Options that expire worthless have a final value of zero, but this may not always appear in historical data if no trades occurred on the last day. When backtesting, explicitly handle expiration:

• In-the-money options: Assume exercise (or assignment for short positions)
• Out-of-the-money options: Value = 0
• At-the-money options: May or may not be exercised depending on transaction costs

Data Gaps

Some option contracts, especially far out-of-the-money or far-dated options, may have days with no trading activity. This results in gaps in the historical data. For backtesting, you can either skip these days or interpolate using a pricing model.

Advanced Historical Options Analysis

Volatility Surface Construction

Using historical option prices across multiple strikes and expirations, you can construct a volatility surface — a three-dimensional representation of implied volatility as a function of strike price and time to expiration.

Pull prices for options at multiple strikes:

=QM_Last("@AAPL 250620C00190000")
=QM_Last("@AAPL 250620C00200000")
=QM_Last("@AAPL 250620C00210000")
=QM_Last("@AAPL 250620C00220000")
=QM_Last("@AAPL 250620C00230000")

Calculate implied volatility from each price using a pricing model, then plot the surface to visualize:

• Skew: How IV varies across strikes at a single expiration
• Term structure: How IV varies across expirations at a single strike
• Surface dynamics: How the entire surface shifts over time

Put-Call Parity Verification

Put-call parity states that for European options: Call Price - Put Price = Stock Price - Strike Price × e^(-rT)

Using historical data, you can verify that this relationship held. Significant deviations from put-call parity may indicate:

• Market stress or dislocation
• Dividend expectation changes
• Borrowing cost spikes
• Arbitrage opportunities (historically)

Term Structure Analysis

The implied volatility term structure shows how IV varies across different expiration dates. Historical analysis reveals:

• How term structure flattens or inverts during market stress
• Seasonal patterns (e.g., IV tends to be higher for expirations spanning earnings dates)
• The relationship between short-term and long-term IV expectations

Pull options at different expirations:

=QM_GetOptionChain("AAPL")

This returns all available expirations, allowing you to construct and analyze the term structure.

Common Mistakes When Using Historical Option Data

Mistake 1: Survivorship Bias

Only analyzing options on stocks that still exist today creates survivorship bias. Companies that went bankrupt or were acquired are missing from the dataset, potentially making strategies look better than they actually were.

Mistake 2: Ignoring Transaction Costs

Options trading involves commissions, bid-ask spread costs, and potential assignment fees. A strategy that shows small profits in backtesting may be unprofitable after accounting for these real-world costs. Always include realistic transaction cost estimates.

Mistake 3: Overfitting

Optimizing strategy parameters to perfectly fit historical data often produces strategies that fail in live trading. Use out-of-sample testing: optimize on one time period and validate on a different, unseen period.

Mistake 4: Assuming Constant Liquidity

Liquidity conditions change over time. An option that was liquid in the past may not be liquid today, and vice versa. Historical volume and open interest data help assess whether past trading conditions are representative.

Mistake 5: Ignoring Early Exercise Risk

American-style options (most individual stock options) can be exercised early. This risk is not captured by simply looking at historical prices at expiration. Deep in-the-money options, especially puts near ex-dividend dates, have meaningful early exercise risk that must be factored into analysis.

Frequently Asked Questions

Where can I find historical option prices?

Historical option prices are available through several sources. MarketXLS provides direct Excel access using functions like =QM_GetHistory("@AAPL 250321C00200000") to pull end-of-day data for any option contract. The CBOE DataShop offers institutional-grade datasets for comprehensive research. Broker platforms like thinkorswim and Interactive Brokers provide limited historical option data within their platforms. For Excel-based analysis and backtesting, MarketXLS offers the most seamless workflow because data flows directly into your spreadsheet.

How do I read an option symbol?

Option symbols follow the format @TICKER YYMMDD[C/P]SSSSSSSSS. The @ prefix identifies it as an option. The ticker is the underlying stock symbol. YYMMDD is the expiration date (year, month, day). C indicates a call and P indicates a put. The final digits represent the strike price multiplied by 1,000. For example, @AAPL 250620C00200000 is an AAPL call option expiring June 20, 2025, with a $200 strike price. You can build symbols automatically using =OptionSymbol("AAPL", "2025-06-20", "C", 200).

Can I backtest options strategies with historical prices?

Yes, historical option prices are the foundation of options strategy backtesting. Use =QM_GetHistory() or =GetHistory() to retrieve past prices for specific option contracts. Combine this with historical stock prices from =GetHistory("AAPL", "2023-01-01", "2025-01-01", "Daily") to reconstruct the complete picture of how a strategy would have performed. Track entry prices, exit prices, premium collected or paid, and assignment outcomes to calculate historical profit and loss.

What is implied volatility and how does historical data help?

Implied volatility (IV) is the market's expectation of future price movement, embedded in option prices. Historical option data lets you calculate what IV was at any point in the past, revealing patterns like the "IV ramp" before earnings and the "IV crush" afterward. By comparing current IV to its historical range, you can determine whether options are relatively expensive or cheap. This analysis — known as IV rank or IV percentile — is one of the most powerful tools for options traders and is only possible with historical option price data.

How far back does historical option data go?

The availability of historical option data depends on the data provider and the specific option contract. MarketXLS provides data for the full life of each option contract. Major index options (SPX, VIX) may have longer histories than individual stock options. Keep in mind that option contracts have limited lifespans — they expire and cease to exist. To analyze long time periods, you need to chain together data from successive option contracts (e.g., monthly at-the-money calls over a two-year period).

How do I handle option data around stock splits?

Stock splits create adjusted option contracts with non-standard terms. For example, a 2-for-1 split would double the number of contracts and halve the strike price for existing options. Historical prices before and after the split may appear discontinuous if you do not account for the adjustment. When backtesting across stock splits, use adjusted prices or limit your analysis to periods without splits. Check the Options Clearing Corporation (OCC) for details on how specific corporate actions affected option contract terms.

Getting Started with Historical Options Analysis

Historical option prices transform options trading from guesswork into a data-driven discipline. With MarketXLS, you can access, analyze, and apply historical options data entirely within Excel.

Here is your workflow:

1. Build option symbols: Use =OptionSymbol("AAPL", "2025-06-20", "C", 200) to construct symbols programmatically
2. Pull historical data: Use =QM_GetHistory() or =GetHistory() to retrieve past prices
3. Analyze current chains: Use =QM_GetOptionChain("AAPL") to see all available contracts
4. Get real-time prices: Use =QM_Last() for current option quotes
5. Study Greeks: Use =QM_GetOptionQuotesAndGreeks("AAPL") for comprehensive option analytics

Visit MarketXLS to start analyzing historical option prices in Excel. Check the pricing page for subscription options that include options data access.

None of the content published on marketxls.com constitutes a recommendation that any particular security, portfolio of securities, transaction, or investment strategy is suitable for any specific person. The author is not offering any professional advice of any kind. The reader should consult a professional financial advisor to determine their suitability for any strategies discussed herein. The article is written to help users collect the required information from various sources deemed to be an authority in their content.