India Equity

To create an India Equity subscription, in the Initialize method, call the AddEquity method. The AddEquity method returns an Equity object, which contains a Symbol. Save a reference to the Symbol so you can use it in OnData to access the security data in the Slice.

_symbol = AddEquity("YESBANK", market: Market.India).Symbol;

self.symbol = self.AddEquity("YESBANK", market=Market.India).Symbol

If you set the brokerage model to an India brokerage, you don't need to pass a market argument. To view the integrated brokerages that offer India Equities, see Brokerages.

The following table shows the available resolutions and data formats for India Equity subscriptions:

Resolution	TradeBar	QuoteBar	Trade Tick	Quote Tick
Tick
Second
Minute
Hour
Daily

The default resolution for India Equity subscriptions is Resolution.Minute. To change the resolution, pass a resolution argument to the AddEquity method.

_symbol = AddEquity("YESBANK", Resolution.Daily, Market.India).Symbol;

self.symbol = self.AddEquity("YESBANK", Resolution.Daily, Market.India).Symbol

To create custom resolution periods, see Consolidating Data.

LEAN groups all of the India Equity exchanges under Market.India. To set the market for a security, pass a market argument to the AddEquity method.

_symbol = AddEquity("YESBANK", market: Market.India).Symbol;

self.symbol = self.AddEquity("YESBANK", market=Market.India).Symbol

The brokerage models have a default market for each asset class. If you set a brokerage model, you may not need to specify the market to use.

Fill forward means if there is no data point for the current slice, LEAN uses the previous data point. Fill forward is the default data setting. If you disable fill forward, you may get stale fills or you may see trade volume as zero.

To disable fill forward for a security, set the fillForward argument to false when you create the security subscription.

_symbol = AddEquity("YESBANK", market: Market.India, fillForward: false).Symbol;

self.symbol = self.AddEquity("YESBANK", market=Market.India, fillForward=False).Symbol

LEAN models buying power and margin calls to ensure your algorithm stays within the margin requirements. The amount of margin that's available depends on the brokerage model you use. For more information about the margin requirements of each brokerage, see the Margin section of the brokerage guides. To change the amount of leverage you can use for a security, pass a leverage argument to the AddEquity method.

_symbol = AddEquity("YESBANK", market: Market.India, leverage: 3).Symbol;

self.symbol = self.AddEquity("YESBANK", market=Market.India, leverage=3).Symbol

By default, your security subscriptions only cover regular trading hours. To subscribe to pre and post-market trading hours for a specific asset, enable the extendedMarketHours argument when you create the security subscription.

_symbol = AddEquity("YESBANK", market: Market.India, extendedMarketHours: true).Symbol;

self.symbol = self.AddEquity("YESBANK", market=Market.India, extendedMarketHours=True).Symbol

You only receive extended market hours data if you create the subscription with minute, second, or tick resolution. If you create the subscription with daily or hourly resolution, the bars only reflect the regular trading hours.

To view the schedule of regular and extended market hours, see Market Hours.

The data normalization mode defines how historical data is adjusted for corporate actions. The data normalization mode affects the data that LEAN passes to OnData and the data from history request. By default, LEAN adjusts India Equity data for splits and dividends to produce a smooth price curve, but the following data normalization modes are available:

If you use Adjusted, SplitAdjusted, or TotalReturn, we use the entire split and dividend history to adjust historical prices. This process ensures you get the same adjusted prices, regardless of the backtest end date. The ScaledRaw data normalization is only for history requests. When you use ScaledRaw, we use the split and dividend history before the algorithm's current time to adjust historical prices. The ScaledRaw data normalization model enables you to warm up indicators with adjusted data when you subscribe to Raw security data.

To set the data normalization mode for a security, pass a dataNormalizationMode argument to the AddEquity method..

_symbol = AddEquity("YESBANK", market: Market.India, dataNormalizationMode: DataNormalizationMode.Raw).Symbol;

self.symbol = AddEquity("YESBANK", market=Market.India, dataNormalizationMode=DataNormalizationMode.Raw).Symbol

The AddEquity method returns an Equity object, which have the following properties: