Supported Indicators

Gamma

Introduction

Option Gamma indicator that calculate the gamma of an option

To view the implementation of this indicator, see the LEAN GitHub repository.

Using G Indicator

To create an automatic indicators for Gamma, call the G helper method from the QCAlgorithm class. The G method creates a Gamma object, hooks it up for automatic updates, and returns it so you can used it in your algorithm. In most cases, you should call the helper method in the Initializeinitialize method.

public class GammaAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Symbol _option, _mirrorOption;
    private Gamma _g;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _option = QuantConnect.Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Put, 450m, new DateTime(2023, 12, 22));
        AddOptionContract(_option, Resolution.Daily);
        _mirrorOption = QuantConnect.Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Call, 450m, new DateTime(2023, 12, 22));
        AddOptionContract(_mirrorOption, Resolution.Daily);
        _g = G(_option, _mirrorOption);
    }

    public override void OnData(Slice data)
    {
        if (_g.IsReady)
        {
            // The current value of _g is represented by itself (_g)
            // or _g.Current.Value
            Plot("Gamma", "g", _g);
            // Plot all properties of g
            Plot("Gamma", "impliedvolatility", _g.ImpliedVolatility);
            Plot("Gamma", "optionsymbol", _g.OptionSymbol);
            Plot("Gamma", "riskfreerate", _g.RiskFreeRate);
            Plot("Gamma", "dividendyield", _g.DividendYield);
            Plot("Gamma", "price", _g.Price);
            Plot("Gamma", "oppositeprice", _g.OppositePrice);
            Plot("Gamma", "underlyingprice", _g.UnderlyingPrice);
        }
    }
}
class GammaAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self.option = Symbol.create_option("SPY", Market.USA, OptionStyle.AMERICAN, OptionRight.PUT, 450, datetime(2023, 12, 22))
        self.add_option_contract(self.option, Resolution.DAILY)
        self.mirror_option = Symbol.create_option("SPY", Market.USA, OptionStyle.AMERICAN, OptionRight.CALL, 450, datetime(2023, 12, 22))
        self.add_option_contract(self.mirror_option, Resolution.DAILY)
        self._g = self.g(self.option, self.mirror_option)

    def on_data(self, slice: Slice) -> None:
        if self._g.is_ready:
            # The current value of self._g is represented by self._g.current.value
            self.plot("Gamma", "g", self._g.current.value)
            # Plot all attributes of self._g
            self.plot("Gamma", "implied_volatility", self._g.implied_volatility.current.value)
            self.plot("Gamma", "option_symbol", self._g.option_symbol.current.value)
            self.plot("Gamma", "risk_free_rate", self._g.risk_free_rate.current.value)
            self.plot("Gamma", "dividend_yield", self._g.dividend_yield.current.value)
            self.plot("Gamma", "price", self._g.price.current.value)
            self.plot("Gamma", "opposite_price", self._g.opposite_price.current.value)
            self.plot("Gamma", "underlying_price", self._g.underlying_price.current.value)

The following reference table describes the G method:

g(symbol, mirror_option=None, risk_free_rate=None, dividend_yield=None, option_model=None, iv_model=None, resolution=None)[source]

Gets the parameter with the specified name. If a parameter with the specified name does not exist, the given default value is returned if any, else null

Parameters:
  • symbol (Symbol) — The option symbol whose values we want as an indicator
  • mirror_option (Symbol, optional) — The mirror option for parity calculation
  • risk_free_rate (float, optional) — The risk free rate
  • dividend_yield (float, optional) — The dividend yield
  • option_model (OptionPricingModelType, optional) — The option pricing model used to estimate Gamma
  • iv_model (OptionPricingModelType, optional) — The option pricing model used to estimate IV
  • resolution (Resolution, optional) — The desired resolution of the data
Returns:

A new Gamma indicator for the specified symbol

Return type:

Gamma

G(symbol, mirrorOption=None, riskFreeRate=None, dividendYield=None, optionModel=None, ivModel=None, resolution=None)[source]

Gets the parameter with the specified name. If a parameter with the specified name does not exist, the given default value is returned if any, else null

Parameters:
  • symbol (Symbol) — The option symbol whose values we want as an indicator
  • mirrorOption (Symbol, optional) — The mirror option for parity calculation
  • riskFreeRate (decimal, optional) — The risk free rate
  • dividendYield (decimal, optional) — The dividend yield
  • optionModel (OptionPricingModelType, optional) — The option pricing model used to estimate Gamma
  • ivModel (OptionPricingModelType, optional) — The option pricing model used to estimate IV
  • resolution (Resolution, optional) — The desired resolution of the data
Returns:

A new Gamma indicator for the specified symbol

Return type:

Gamma

If you don't provide a resolution, it defaults to the security resolution. If you provide a resolution, it must be greater than or equal to the resolution of the security. For instance, if you subscribe to hourly data for a security, you should update its indicator with data that spans 1 hour or longer.

For more information about the selector argument, see Alternative Price Fields.

For more information about plotting indicators, see Plotting Indicators.

You can manually create a Gamma indicator, so it doesn't automatically update. Manual indicators let you update their values with any data you choose.

Updating your indicator manually enables you to control when the indicator is updated and what data you use to update it. To manually update the indicator, call the Updateupdate method with time/number pair or an IndicatorDataPoint. The indicator will only be ready after you prime it with enough data.

public class GammaAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Symbol _option, _mirrorOption;
    private Gamma _g;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _option = QuantConnect.Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Put, 450m, new DateTime(2023, 12, 22));
        AddOptionContract(_option, Resolution.Daily);
        _mirrorOption = QuantConnect.Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Call, 450m, new DateTime(2023, 12, 22));
        AddOptionContract(_mirrorOption, Resolution.Daily);
        _g = new Gamma(_option, interest_rate_model, dividend_yield_model, _mirrorOption);
    }

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
        {      
            _g.Update(new IndicatorDataPoint(_symbol, bar.EndTime, bar.Close));
        }
        if (data.QuoteBars.TryGetValue(_option, out bar))
        {      
            _g.Update(new IndicatorDataPoint(_option, bar.EndTime, bar.Close));
        }
        if (data.QuoteBars.TryGetValue(_mirrorOption, out bar))
        {      
            _g.Update(new IndicatorDataPoint(_mirrorOption, bar.EndTime, bar.Close));
        }
   
        if (_g.IsReady)
        {
            // The current value of _g is represented by itself (_g)
            // or _g.Current.Value
            Plot("Gamma", "g", _g);
            // Plot all properties of g
            Plot("Gamma", "impliedvolatility", _g.ImpliedVolatility);
            Plot("Gamma", "optionsymbol", _g.OptionSymbol);
            Plot("Gamma", "riskfreerate", _g.RiskFreeRate);
            Plot("Gamma", "dividendyield", _g.DividendYield);
            Plot("Gamma", "price", _g.Price);
            Plot("Gamma", "oppositeprice", _g.OppositePrice);
            Plot("Gamma", "underlyingprice", _g.UnderlyingPrice);
        }
    }
}
class GammaAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self.option = Symbol.create_option("SPY", Market.USA, OptionStyle.AMERICAN, OptionRight.PUT, 450, datetime(2023, 12, 22))
        self.add_option_contract(self.option, Resolution.DAILY)
        self.mirror_option = Symbol.create_option("SPY", Market.USA, OptionStyle.AMERICAN, OptionRight.CALL, 450, datetime(2023, 12, 22))
        self.add_option_contract(self.mirror_option, Resolution.DAILY)
        self._g = Gamma(self.option, interest_rate_model, dividend_yield_model, self.mirror_option)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self._g.update(IndicatorDataPoint(self._symbol, bar.end_time, bar.close))
        bar = slice.quote_bars.get(self.option)
        if bar:
            self._g.update(IndicatorDataPoint(self.option, bar.end_time, bar.close))
        bar = slice.quote_bars.get(self.mirror_option)
        if bar:
            self._g.update(IndicatorDataPoint(self.mirror_option, bar.end_time, bar.close))
        if self._g.is_ready:
            # The current value of self._g is represented by self._g.current.value
            self.plot("Gamma", "g", self._g.current.value)
            # Plot all attributes of self._g
            self.plot("Gamma", "implied_volatility", self._g.implied_volatility.current.value)
            self.plot("Gamma", "option_symbol", self._g.option_symbol.current.value)
            self.plot("Gamma", "risk_free_rate", self._g.risk_free_rate.current.value)
            self.plot("Gamma", "dividend_yield", self._g.dividend_yield.current.value)
            self.plot("Gamma", "price", self._g.price.current.value)
            self.plot("Gamma", "opposite_price", self._g.opposite_price.current.value)
            self.plot("Gamma", "underlying_price", self._g.underlying_price.current.value)

To register a manual indicator for automatic updates with the security data, call the RegisterIndicatorregister_indicator method.

public class GammaAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Symbol _option, _mirrorOption;
    private Gamma _g;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _option = QuantConnect.Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Put, 450m, new DateTime(2023, 12, 22));
        AddOptionContract(_option, Resolution.Daily);
        _mirrorOption = QuantConnect.Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Call, 450m, new DateTime(2023, 12, 22));
        AddOptionContract(_mirrorOption, Resolution.Daily);
        _g = new Gamma(_option, interest_rate_model, dividend_yield_model, _mirrorOption);
        RegisterIndicator(_symbol, _g, Resolution.Daily);
        RegisterIndicator(_option, _g, Resolution.Daily);
        RegisterIndicator(_mirrorOption, _g, Resolution.Daily);
    }

    public override void OnData(Slice data)
    {
        if (_g.IsReady)
        {
            // The current value of _g is represented by itself (_g)
            // or _g.Current.Value
            Plot("Gamma", "g", _g);
            // Plot all properties of g
            Plot("Gamma", "impliedvolatility", _g.ImpliedVolatility);
            Plot("Gamma", "optionsymbol", _g.OptionSymbol);
            Plot("Gamma", "riskfreerate", _g.RiskFreeRate);
            Plot("Gamma", "dividendyield", _g.DividendYield);
            Plot("Gamma", "price", _g.Price);
            Plot("Gamma", "oppositeprice", _g.OppositePrice);
            Plot("Gamma", "underlyingprice", _g.UnderlyingPrice);
        }
    }
}
class GammaAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self.option = Symbol.create_option("SPY", Market.USA, OptionStyle.AMERICAN, OptionRight.PUT, 450, datetime(2023, 12, 22))
        self.add_option_contract(self.option, Resolution.DAILY)
        self.mirror_option = Symbol.create_option("SPY", Market.USA, OptionStyle.AMERICAN, OptionRight.CALL, 450, datetime(2023, 12, 22))
        self.add_option_contract(self.mirror_option, Resolution.DAILY)
        self._g = Gamma(self.option, interest_rate_model, dividend_yield_model, self.mirror_option)
        self.register_indicator(self._symbol, self._g, Resolution.DAILY)
        self.register_indicator(self.option, self._g, Resolution.DAILY)
        self.register_indicator(self.mirror_option, self._g, Resolution.DAILY)

    def on_data(self, slice: Slice) -> None:
        if self._g.is_ready:
            # The current value of self._g is represented by self._g.current.value
            self.plot("Gamma", "g", self._g.current.value)
            # Plot all attributes of self._g
            self.plot("Gamma", "implied_volatility", self._g.implied_volatility.current.value)
            self.plot("Gamma", "option_symbol", self._g.option_symbol.current.value)
            self.plot("Gamma", "risk_free_rate", self._g.risk_free_rate.current.value)
            self.plot("Gamma", "dividend_yield", self._g.dividend_yield.current.value)
            self.plot("Gamma", "price", self._g.price.current.value)
            self.plot("Gamma", "opposite_price", self._g.opposite_price.current.value)
            self.plot("Gamma", "underlying_price", self._g.underlying_price.current.value)

The following reference table describes the Gamma constructor:

Gamma

class QuantConnect.Indicators.Gamma[source]

Option Gamma indicator that calculate the gamma of an option

get_enumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

reset()

Resets this indicator and all sub-indicators

to_detailed_string()

Provides a more detailed string of this indicator in the form of {Name} - {Value}

Return type:

str

update(time, value)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • time (datetime)
  • value (float)
Return type:

bool

update(input)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • input (IBaseData)
Return type:

bool

property consolidators

The data consolidators associated with this indicator if any

Returns:

The data consolidators associated with this indicator if any

Return type:

ISet[IDataConsolidator]

property current

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property dividend_yield

Dividend Yield

Returns:

Dividend Yield

Return type:

Identity

property expiry

Gets the expiration time of the option

Returns:

Gets the expiration time of the option

Return type:

datetime

property implied_volatility

Gets the implied volatility of the option

Returns:

Gets the implied volatility of the option

Return type:

ImpliedVolatility

property is_ready

Gets a flag indicating when this indicator is ready and fully initialized

Returns:

Gets a flag indicating when this indicator is ready and fully initialized

Return type:

bool

property item

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Returns:

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Return type:

IndicatorDataPoint

property name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

str

property opposite_price

Gets the mirror option price level, for implied volatility

Returns:

Gets the mirror option price level, for implied volatility

Return type:

IndicatorBase[IndicatorDataPoint]

property option_symbol

Option's symbol object

Returns:

Option's symbol object

Return type:

Symbol

property previous

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property price

Gets the option price level

Returns:

Gets the option price level

Return type:

IndicatorBase[IndicatorDataPoint]

property right

Gets the option right (call/put) of the option

Returns:

Gets the option right (call/put) of the option

Return type:

OptionRight

property risk_free_rate

Risk Free Rate

Returns:

Risk Free Rate

Return type:

Identity

property samples

Gets the number of samples processed by this indicator

Returns:

Gets the number of samples processed by this indicator

Return type:

int

property strike

Gets the strike price of the option

Returns:

Gets the strike price of the option

Return type:

float

property style

Gets the option style (European/American) of the option

Returns:

Gets the option style (European/American) of the option

Return type:

OptionStyle

property underlying_price

Gets the underlying's price level

Returns:

Gets the underlying's price level

Return type:

IndicatorBase[IndicatorDataPoint]

property use_mirror_contract

Flag if mirror option is implemented for parity type calculation

Returns:

Flag if mirror option is implemented for parity type calculation

Return type:

bool

property warm_up_period

Required period, in data points, for the indicator to be ready and fully initialized.

Returns:

Required period, in data points, for the indicator to be ready and fully initialized.

Return type:

int

property window

A rolling window keeping a history of the indicator values of a given period

Returns:

A rolling window keeping a history of the indicator values of a given period

Return type:

RollingWindow[IndicatorDataPoint]

Gamma

class QuantConnect.Indicators.Gamma[source]

Option Gamma indicator that calculate the gamma of an option

GetEnumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

Reset()

Resets this indicator and all sub-indicators

ToDetailedString()

Provides a more detailed string of this indicator in the form of {Name} - {Value}

Return type:

String

Update(time, value)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • time (DateTime)
  • value (decimal)
Return type:

Boolean

Update(input)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • input (IBaseData)
Return type:

Boolean

property Consolidators

The data consolidators associated with this indicator if any

Returns:

The data consolidators associated with this indicator if any

Return type:

ISet<IDataConsolidator>

property Current

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property DividendYield

Dividend Yield

Returns:

Dividend Yield

Return type:

Identity

property Expiry

Gets the expiration time of the option

Returns:

Gets the expiration time of the option

Return type:

DateTime

property ImpliedVolatility

Gets the implied volatility of the option

Returns:

Gets the implied volatility of the option

Return type:

ImpliedVolatility

property IsReady

Gets a flag indicating when this indicator is ready and fully initialized

Returns:

Gets a flag indicating when this indicator is ready and fully initialized

Return type:

bool

property Name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

string

property OppositePrice

Gets the mirror option price level, for implied volatility

Returns:

Gets the mirror option price level, for implied volatility

Return type:

IndicatorBase<IndicatorDataPoint>

property OptionSymbol

Option's symbol object

Returns:

Option's symbol object

Return type:

Symbol

property Previous

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property Price

Gets the option price level

Returns:

Gets the option price level

Return type:

IndicatorBase<IndicatorDataPoint>

property Right

Gets the option right (call/put) of the option

Returns:

Gets the option right (call/put) of the option

Return type:

OptionRight

property RiskFreeRate

Risk Free Rate

Returns:

Risk Free Rate

Return type:

Identity

property Samples

Gets the number of samples processed by this indicator

Returns:

Gets the number of samples processed by this indicator

Return type:

int

property Strike

Gets the strike price of the option

Returns:

Gets the strike price of the option

Return type:

decimal

property Style

Gets the option style (European/American) of the option

Returns:

Gets the option style (European/American) of the option

Return type:

OptionStyle

property UnderlyingPrice

Gets the underlying's price level

Returns:

Gets the underlying's price level

Return type:

IndicatorBase<IndicatorDataPoint>

property UseMirrorContract

Flag if mirror option is implemented for parity type calculation

Returns:

Flag if mirror option is implemented for parity type calculation

Return type:

bool

property WarmUpPeriod

Required period, in data points, for the indicator to be ready and fully initialized.

Returns:

Required period, in data points, for the indicator to be ready and fully initialized.

Return type:

Int32

property Window

A rolling window keeping a history of the indicator values of a given period

Returns:

A rolling window keeping a history of the indicator values of a given period

Return type:

RollingWindow<IndicatorDataPoint>

property [System.Int32]

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Returns:

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Return type:

IndicatorDataPoint

Visualization

The following image shows plot values of selected properties of Gamma using the plotly library.

Gamma line plot.

Indicator History

To get the historical data of the Gamma indicator, call the IndicatorHistoryself.indicator_history method. This method resets your indicator, makes a history request, and updates the indicator with the historical data. Just like with regular history requests, the IndicatorHistoryindicator_history method supports time periods based on a trailing number of bars, a trailing period of time, or a defined period of time. If you don't provide a resolution argument, it defaults to match the resolution of the security subscription. 

public class GammaAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Symbol _option, _mirrorOption;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _option = QuantConnect.Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Put, 225m, new DateTime(2024, 7, 12));
        AddOptionContract(_option, Resolution.Daily);
        _mirrorOption = QuantConnect.Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Call, 225m, new DateTime(2024, 7, 12));
        AddOptionContract(_mirrorOption, Resolution.Daily);
        var g = G(_option, _mirrorOption);
        var countIndicatorHistory = IndicatorHistory(g, new[] { _symbol, _option, _mirrorOption }, 100, Resolution.Minute);
        var timeSpanIndicatorHistory = IndicatorHistory(g, new[] { _symbol, _option, _mirrorOption }, TimeSpan.FromDays(10), Resolution.Minute);
        var timePeriodIndicatorHistory = IndicatorHistory(g, new[] { _symbol, _option, _mirrorOption }, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
    }
}
class GammaAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._option = Symbol.create_option("SPY", Market.USA, OptionStyle.AMERICAN, OptionRight.PUT, 225, datetime(2024, 7, 12))
        self.add_option_contract(self._option, Resolution.DAILY)
        self._mirror_option = Symbol.create_option("SPY", Market.USA, OptionStyle.AMERICAN, OptionRight.CALL, 225, datetime(2024, 7, 12))
        self.add_option_contract(self._mirror_option, Resolution.DAILY)
        g = self.g(self.option, self.mirror_option)
        count_indicator_history = self.indicator_history(g, [self._symbol, self._option, self._mirror_option], 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(g, [self._symbol, self._option, self._mirror_option], timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(g, [self._symbol, self._option, self._mirror_option], datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)

To make the IndicatorHistoryindicator_history method update the indicator with an alternative price field instead of the close (or mid-price) of each bar, pass a selector argument.

var indicatorHistory = IndicatorHistory(g, 100, Resolution.Minute, (bar) => ((TradeBar)bar).High);
indicator_history = self.indicator_history(g, 100, Resolution.MINUTE, lambda bar: bar.high)
indicator_history_df = indicator_history.data_frame

If you already have a list of Slice objects, you can pass them to the IndicatorHistoryindicator_history method to avoid the internal history request.

var history = History(new[] { _symbol, _option, _mirrorOption }, 100, Resolution.Minute);
var historyIndicatorHistory = IndicatorHistory(g, history);

To access the properties of the indicator history, invoke the property of each IndicatorDataPoint object.index the DataFrame with the property name.

var impliedvolatility = indicatorHistory.Select(x => ((dynamic)x).ImpliedVolatility).ToList();
var optionsymbol = indicatorHistory.Select(x => ((dynamic)x).OptionSymbol).ToList();
var riskfreerate = indicatorHistory.Select(x => ((dynamic)x).RiskFreeRate).ToList();
var dividendyield = indicatorHistory.Select(x => ((dynamic)x).DividendYield).ToList();
var price = indicatorHistory.Select(x => ((dynamic)x).Price).ToList();
var oppositeprice = indicatorHistory.Select(x => ((dynamic)x).OppositePrice).ToList();
var underlyingprice = indicatorHistory.Select(x => ((dynamic)x).UnderlyingPrice).ToList();

// Alternative way
// var impliedvolatility = indicatorHistory.Select(x => x["impliedvolatility"]).ToList();
// var optionsymbol = indicatorHistory.Select(x => x["optionsymbol"]).ToList();
// var riskfreerate = indicatorHistory.Select(x => x["riskfreerate"]).ToList();
// var dividendyield = indicatorHistory.Select(x => x["dividendyield"]).ToList();
// var price = indicatorHistory.Select(x => x["price"]).ToList();
// var oppositeprice = indicatorHistory.Select(x => x["oppositeprice"]).ToList();
// var underlyingprice = indicatorHistory.Select(x => x["underlyingprice"]).ToList();

implied_volatility = indicator_history_df["implied_volatility"]
option_symbol = indicator_history_df["option_symbol"]
risk_free_rate = indicator_history_df["risk_free_rate"]
dividend_yield = indicator_history_df["dividend_yield"]
price = indicator_history_df["price"]
opposite_price = indicator_history_df["opposite_price"]
underlying_price = indicator_history_df["underlying_price"]

# Alternative way
# implied_volatility = indicator_history_df.implied_volatility
# option_symbol = indicator_history_df.option_symbol
# risk_free_rate = indicator_history_df.risk_free_rate
# dividend_yield = indicator_history_df.dividend_yield
# price = indicator_history_df.price
# opposite_price = indicator_history_df.opposite_price
# underlying_price = indicator_history_df.underlying_price

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