Bonds#

The backtesting plugin supports bonds, including interbank bonds and bonds listed on the Shanghai Stock Exchange.

Interbank Bonds#

Configuration#

The configurations are as follows:

key	Description	Notes
“start_date”	start date	DATE type, required (e.g., “2020.01.01”)
“end_date”	end date	DATE type, required (e.g., “2020.01.01”)
“asset_type”	strategy group	must be “CFETSBond”
“cash”	initial cash flow	DOUBLE type, required
“data_type”	the type of market data	INT type, required, which can be: 2: snapshot + tick data 3: minute-level data (matching_mode must be set to 3 when used) 4: daily data
“matching_mode”	matching mode	INT type. daily data: 1: matching with the closing price. 2: matching with the open price. minute-level data: 1: matching when market time > order time. 2: matching with the closing price when market time = order time; matching unfilled orders with mode 1. snapshot data: matching with the order price.
“msg_as_table”	process the input market data as table or dictionary	false (default): dictionary true: table (the backtesting engine can only be created via the createBacktestEngine interface)
“benck_mark”	benchmark instrument	used in `getReturnSummary` (e.g., “000300.XSHG”)
“latency”	the latency from order submission to execution	DOUBLE type, in milliseconds
“enable_indicator_optimize”	enable indicator calculation optimization	true: enable false (default): disable
“add_time_columnIn_indicator”	add time column to indicator subscription results	true: add time column false (default): omit time column
“isBacktestMode”	backtesting mode	true (default): backtesting false: matching
“data_retention_window”	data retention policy for indicator optimization	STRING/INT type. Effective only when both enable_indicator_optimize = true and isBacktestMode = true: “ALL”: Retain all data. Retain data by trading days, e.g., “20d” retains 20 trading days. “None” (default): Retain no data. Retain data by row count, e.g., “20” retains the latest 20 rows per symbol.
“context”	strategy context structure	a dictionary consisting of global strategy variables, for example: `context = {"buySignalRSI": 70} userConfig["context"] = context`
“orderbook_matching_ratio”	the proportion of an order that gets filled	DOUBLE type, default is 1.0, valid range: 0 to 1.0.
“matchingRatio”	matching ratio within price intervals	DOUBLE type, valid range: 0 to 1.0. By default, it is equal to the orderbook_matching_ratio.

Schema of security Reference#

Field Name	Data Type	Description
symbol	STRING	underlying asset
couponRate	DOUBLE	coupon rate
frequency	INT	coupon frequency
valueDate	DATE	value date
maturityDate	DATE	maturity Date

Market Data#

When appending data into the backtest engine via the append_data interface:

col_type = {
    "symbol": "SYMBOL", "symbolSource": "SYMBOL", "timestamp": "TIMESTAMP", "bidSettlType": "INT[]", 
    "bidQty": "LONG[]", "bidPrice": "DOUBLE[]", "bidYield": "DOUBLE[]", "askSettlType": "INT[]", 
    "askQty": "LONG[]", "askPrice": "DOUBLE[]", "askYield": "DOUBLE[]", "tradePrice": "DOUBLE[]", 
    "tradeQty": "LONG[]", "settlType": "INT[]", "yield": "DOUBLE[]"
}

message_table = sf.streaming.table(types=col_type, size=0, capacity=10000000)

Schema for snapshot + tick data (“trades”):

Field	Data Type	Description
symbol	SYMBOL	symbol
symbolSource	SYMBOL	market: interbank “X_BOND”
timestamp	TIMESTAMP	timestamp
bidSettlType	INT[]	bid settlement type
bidQty	LONG[]	bid quantity
bidPrice	DOUBLE[]	bid clean price
bidYield	DOUBLE[]	bid yield
askSettlType	INT[]	ask settlement type
askQty	LONG[]	ask quantity
askPrice	DOUBLE[]	ask clean price
askYield	DOUBLE[]	ask yield
tradePrice	DOUBLE[]	trade price list
tradeQty	LONG[]	trade quantity list
settlType	INT[]	settlement type
yield	DOUBLE[]	yield to maturity

Minute-level data:

Field	Data Type	Description
symbol	SYMBOL	symbol
symbolName	STRING	symbol name
tradeDate	TIMESTAMP	trade date
maturityDate	DOUBLE	maturity date
tradeClean	DOUBLE	trade clean price
tradeDirty	DOUBLE	trade dirty price
tradeAccruedInterest	DOUBLE	accrued interest
yield	DOUBLE	yield to maturity
tradeVolume	DOUBLE	trade volume

When the backtest ends, a message with symbol=”END” is sent:

message_table = sf.sql("SELECT TOP 1 * FROM messageTable", vars={'messageTable': message_table})
sf.sql("UPDATE messageTable SET symbol='END'", vars={'messageTable': message_table})
backtester.append_data(message_table)

Strategy Callback Function#

Snapshot market callback function on_snapshot: input parameter msg.

If msg is a dictionary, it is a snapShot data dictionary with symbol=”key”, where each snapShot object contains the following fields:

Field	Data Type	Notes
symbol	SYMBOL	symbol
messageSource	SYMBOL	market: interbank “X_BOND”
byield	TIMESTAMP	timestamp
ayield	DOUBLE[]	bid yield to maturity
bmdEntryPrice	DOUBLE[]	bid clean price
amdEntryPrice	DOUBLE[]	ask clean price
bmdEntrySize	LONG[]	bid quantity
amdEntrySize	LONG[]	ask quantity
bsettlType	LONG[]	bid settlement type
asettlType	LONG[]	ask settlement type
settlType	LONG[]	settlement type
tradePrice	DOUBLE[]	trade price list
tradeYield	DOUBLE[]	yield to maturity
tradeQty	LONG[]	trade quantity list

SSE Bonds#

Configuration#

The parameters of the Backtester interface are as follows:

key	Description	Notes
“start_date”	start date	DATE type, required (e.g., “2020.01.01”)
“end_date”	end date	DATE type, required (e.g., “2020.01.01”)
“asset_type”	strategy group	must be “XSHGBond”
“cash”	initial cash flow	DOUBLE type, required
“commission”	commission	DOUBLE type, required
“tax”	stamp duty	DOUBLE type, required
“data_type”	the type of market data	INT type, required, which can be: 2: snapshot + trades details 4: daily data
“orderbook_matching_ratio”	the proportion of an order that gets filled	DOUBLE type, default is 1.0, valid range: 0 to 1.0
“matchingRatio”	matching ratio within price intervals	DOUBLE type, valid range: 0 to 1.0. By default, it is equal to the orderbook_matching_ratio
“setLastDayPosition”	base position settings	base position information table, see the table schema below

The schema of the base position information table is as follows:

Field	Data Type	Description
symbol	SYMBOL	stock code
longPosition	LONG/INT	long position size
costPrice	DOUBLE	cost price

Schema of Security Reference#

Field	Data Type	Description
symbol	STRING	symbol
couponRate	DOUBLE	coupon rate
frequency	INT	payment frequency
valueDate	DATE	value date
maturityDate	DATE	maturity date

Market Data#

The input market data supports a table composed of “firm quote market data” and “trade details,” with the following schema:

Field	Data Type	Notes
symbol	SYMBOL/STRING	symble
timestamp	TIMESTAMP	timestamp
msgType	INT	market type, which can be: 0: firm quote market data 1: trade details
symbolName	STRING	symbol name
bidId	INT	bid order id
bidTime	TIMESTAMP	bid time
bidParty	SYMBOL/STRING	bid party
bidClean	DOUBLE	bid clean price
bidQty	LONG	bid quantity
bidDirty	DOUBLE	bid dirty price
bidYield	DOUBLE	bid yield to maturity
askId	INT	ask order id
askTime	TIMESTAMP	ask time
askParty	SYMBOL/STRING	ask party
askClean	DOUBLE	ask clean price
askQty	LONG	ask quantity
askDirty	DOUBLE	ask dirty price
askYield	DOUBLE	ask yield to maturity
accruedInterest	DOUBLE	accrued interest
tradeTime	TIMESTAMP	trade time
tradeClean	DOUBLE	trade clean price
tradeAccruedInterest	DOUBLE	trade accrued interest
tradeDirty	DOUBLE	trade dirty price
yield	DOUBLE	yield to maturity
tradeVolume	INT	trade volume
tradeValue	DOUBLE	trade value
tradeType	INT	trading type, which can be: 1: firm quote 2: pending quote 3: request for quote 4: negotiated trade 6: negotiated trade (including mixed declarations) 7: bidding