Replica of TradingView's Backtesting Engine with ArraysHello everyone,
Here is a perfectly replicated TradingView backtesting engine condensed into a single library function calculated with arrays. It includes TradingView's calculations for Net profit, Total Trades, Percent of Trades Profitable, Profit Factor, Max Drawdown (absolute and percent), and Average Trade (absolute and percent). Here's how TradingView defines each aspect of its backtesting system:
Net Profit: The overall profit or loss achieved.
Total Trades: The total number of closed trades, winning and losing.
Percent Profitable: The percentage of winning trades, the number of winning trades divided by the total number of closed trades.
Profit Factor: The amount of money the strategy made for every unit of money it lost, gross profits divided by gross losses.
Max Drawdown: The greatest loss drawdown, i.e., the greatest possible loss the strategy had compared to its highest profits.
Average Trade: The sum of money gained or lost by the average trade, Net Profit divided by the overall number of closed trades.
Here's how each variable is defined in the library function:
_backtest(bool _enter, bool _exit, float _startQty, float _tradeQty)
bool _enter: When the strategy should enter a trade (entry condition)
bool _exit: When the strategy should exit a trade (exit condition)
float _startQty: The starting capital in the account (for BTCUSD, it is the amount of USD the account starts with)
float _tradeQty: The amount of capital traded (if set to 1000 on BTCUSD, it will trade 1000 USD on each trade)
Currently, this library only works with long strategies, and I've included a commented out section under DEMO STRATEGY where you can replicate my results with TradingView's backtesting engine. There's tons I could do with this beyond what is shown, but this was a project I worked on back in June of 2022 before getting burned out. Feel free to comment with any suggestions or bugs, and I'll try to add or fix them all soon. Here's my list of thing to add to the library currently (may not all be added):
Add commission calculations.
Add support for shorting
Add a graph that resembles TradingView's overview graph.
Clean and optimize code.
Clean up in a way that makes it easy to add other TradingView calculations (such as Sharpe and Sortino ratio).
Separate all variables, so they become accessible outside of calculations (such as gross profit, gross loss, number of winning trades, number of losing trades, etc.).
Thanks for reading,
OztheWoz
Strategies
Profit EstimateLibrary "profitestimate"
Simple profit Estimatr. Engages when Position != 0
and holds until posittion is na/0...
if position changes sizes, it will update automatically and adjust.
it has an input for comission to estmate exit fees
update_avgprice(_sizewas, _delta, _pricewas, _newprice)
Get a new Average position Price
Parameters:
_sizewas : (float) the position prior
_delta : (float) the order amount
_pricewas : (float) the prior price
_newprice : (float) the price of order
Returns: New Avg Price
amount(_position, _close, _commission, _leverage, _fullqty)
Position Net Profit Net Commission, automatic on/off if position != 0
Parameters:
_position : (float) position size (total or margin size)
_close
_commission : (float) % where (0.1 = 0.1%)
_leverage : (float) optional if leveraged, default 1x
_fullqty : (bool) if position entered is tottal trade size default is margin qty (1/lev)
Returns: quote value of profit
percent(_position, _close, _commission, _leverage, _fullqty)
Position Net Profit, automatic on/off if position != 0
Parameters:
_position : (float) position size (total or margin size)
_close
_commission : (float) % where (0.1 = 0.1%)
_leverage : (float) optional if leveraged, default 1x
_fullqty : (bool) if position entered is tottal trade size, default is margin qty (1/lev)
Returns: percentage profit (1% = 1)
PlurexSignalStrategyLibrary "PlurexSignalStrategy"
Provides functions that wrap the built in TradingView strategy functions so you can seemlessly integrate with Plurex Signal automation.
NOTE: Be sure to:
- set your strategy default_qty_value to the default entry percentage of your signal
- set your strategy default_qty_type to strategy.percent_of_equity
- set your strategy pyramiding to some value greater than 1 or something appropriate to your strategy in order to have multiple entries.
long(secret, budgetPercentage, priceLimit, marketOverride)
Open a new long entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
longAndFixedStopLoss(secret, stop, budgetPercentage, priceLimit, marketOverride)
Open a new long entry. Wraps strategy function and sends plurex message as an alert. Also sets a gobal stop loss for full open position
Parameters:
secret : The secret for your Signal on plurex
stop : The trigger price for the stop loss. See strategy.exit documentation
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
longAndTrailingStopLoss(secret, trail_offset, trail_price, trail_points, budgetPercentage, priceLimit, marketOverride)
Open a new long entry. Wraps strategy function and sends plurex message as an alert. Also sets a gobal trailing stop loss for full open position. You must set one of trail_price or trail_points.
Parameters:
secret : The secret for your Signal on plurex
trail_offset : See strategy.exit documentation
trail_price : See strategy.exit documentation
trail_points : See strategy.exit documentation
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
short(secret, budgetPercentage, priceLimit, marketOverride)
Open a new short entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
shortAndFixedStopLoss(secret, stop, budgetPercentage, priceLimit, marketOverride)
Open a new short entry. Wraps strategy function and sends plurex message as an alert. Also sets a gobal stop loss for full open position
Parameters:
secret : The secret for your Signal on plurex
stop : The trigger price for the stop loss. See strategy.exit documentation
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
shortAndTrailingStopLoss(secret, trail_offset, trail_price, trail_points, budgetPercentage, priceLimit, marketOverride)
Open a new short entry. Wraps strategy function and sends plurex message as an alert. Also sets a gobal trailing stop loss for full open position. You must set one of trail_price or trail_points.
Parameters:
secret : The secret for your Signal on plurex
trail_offset : See strategy.exit documentation
trail_price : See strategy.exit documentation
trail_points : See strategy.exit documentation
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeAll(secret, marketOverride)
Close all positions. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeLongs(secret, marketOverride)
close all longs. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeShorts(secret, marketOverride)
close all shorts. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeLastLong(secret, marketOverride)
Close last long entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeLastShort(secret, marketOverride)
Close last short entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeFirstLong(secret, marketOverride)
Close first long entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeFirstShort(secret, marketOverride)
Close first short entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
strategyLibrary "strategy"
Library containing few key calculations for strategy involving leveraged limit and stop orders
getQty(entry, stop, riskPercentage)
calculate qty and leverage based on entry and stop price for given risk percentage.
Parameters:
entry : Entry Price
stop : Stop Price
riskPercentage : risk percentage per trade
Returns: - Quantity based on the risk and calculated leverage on position including existing positions
bracketOrder(entry, stop, target, maxLeverage, isLimitOrder, riskPercentage)
Calculates position size based on risk and creates bracket orders for given entry/stop/target
Parameters:
entry : Entry Price
stop : Stop Price
target : Target Price
maxLeverage : Maximum leverage allowed
isLimitOrder : if true, places limit order for entry, else places stop order.
riskPercentage : risk percentage per trade
Returns: orderPlaced - true if orders successfully placed, false otherwise.
order(entry, stop, maxLeverage, isLimitOrder, riskPercentage)
Calculates position size based on risk and creates order for given entry/stop
Parameters:
entry : Entry Price
stop : Stop Price
maxLeverage : Maximum leverage allowed
isLimitOrder : if true, places limit order for entry, else places stop order.
riskPercentage : risk percentage per trade
Returns: orderPlaced - true if orders successfully placed, false otherwise.
TradingWolfLibaryLibrary "TradingWolfLibary"
getMA(int, string)
Gets a Moving Average based on type
Parameters:
int : length The MA period
string : maType The type of MA
Returns: A moving average with the given parameters
minStop(float, simple, float, string)
Calculates and returns Minimum stop loss
Parameters:
float : entry price (Close if calculating on the entry candle)
simple : int Calculate how many bars back to look at swings
float : Minimum Stop Loss allowed (Should be x 0.01) if input
string : Direciton of trade either "Long" or "Short"
Returns: Stop Loss Value
Strategy PnL LibraryLibrary "Strategy_PnL_Library"
TODO: This is a library that helps you learn current pnl of open position and use it to create your own dynamic take profit or stop loss rules based on current level of your profit. It should only be used with strategies.
inTrade()
inTrade: Checks if a position is currently open.
Returns: bool: true for yes, false for no.
notInTrade()
inTrade: Checks if a position is currently open. Interchangeable with inTrade but just here for simple semantics.
Returns: bool: true for yes, false for no.
pnl()
pnl: Calculates current profit or loss of position after the commission. If the strategy is not in trade it will always return na.
Returns: float: Current Profit or Loss of position, positive values for profit, negative values for loss.
entryBars()
entryBars: Checks how many bars it's been since the entry of the position.
Returns: int: Returns a int of strategy entry bars back. Minimum value is always corrected to 1 to avoid lookback errors.
pnlvelocity()
pnlvelocity: Calculates the velocity of pnl by following the change in open profit compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl velocity.
pnlacc()
pnlacc: Calculates the acceleration of pnl by following the change in profit velocity compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl acceleration.
pnljerk()
pnljerk: Calculates the jerk of pnl by following the change in profit acceleration compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl jerk.
pnlhigh()
pnlhigh: Calculates the highest value the pnl has reached since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float highest value the pnl has reached.
pnllow()
pnllow: Calculates the lowest value the pnl has reached since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float lowest value the pnl has reached.
pnldev()
pnldev: Calculates the deviance of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float deviance value of the pnl.
pnlvar()
pnlvar: Calculates the variance value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float variance value of the pnl.
pnlstdev()
pnlstdev: Calculates the stdev value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float stdev value of the pnl.
pnlmedian()
pnlmedian: Calculates the median value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float median value of the pnl.
AkselitoLibraryLibrary "AkselitoLibrary"
TODO: add library description here
fun(x)
TODO: add function description here
Parameters:
x : TODO: add parameter x description here
Returns: TODO: add what function returns
hi()
FrostyBotLibrary "FrostyBot"
JSON Alert Builder for FrostyBot.js Binance Futures and FTX orders
github.com
More Complete Version Soon.
TODO: Comment Functions and annotations from command reference ^^
TODO: Add additional whitelist and symbol mappings.
leverage()
buy()
sell()
cancelall()
closelong()
closeshort()
traillong()
trailshort()
long()
short()
takeprofit()
stoploss()
PineHelperLibrary "PineHelper"
This library provides various functions to reduce your time.
recent_opentrade_entry_bar_index()
get a recent opentrade entry bar_index
Returns: (int) bar_index
recent_closedtrade_entry_bar_index()
get a recent closedtrade entry bar_index
Returns: (int) bar_index
recent_closedtrade_exit_bar_index()
get a recent closedtrade exit bar_index
Returns: (int) bar_index
all_opnetrades_roi()
get all aopentrades roi
Returns: (float) roi
bars_since_recent_opentrade_entry()
get bars since recent opentrade entry
Returns: (int) number of bars
bars_since_recent_closedtrade_entry()
get bars since recent closedtrade entry
Returns: (int) number of bars
bars_since_recent_closedtrade_exit()
get bars since recent closedtrade exit
Returns: (int) number of bars
recent_opentrade_entry_id()
get recent opentrade entry ID
Returns: (string) entry ID
recent_closedtrade_entry_id()
get recent closedtrade entry ID
Returns: (string) entry ID
recent_closedtrade_exit_id()
get recent closedtrade exit ID
Returns: (string) exit ID
recent_opentrade_entry_price()
get recent opentrade entry price
Returns: (float) price
recent_closedtrade_entry_price()
get recent closedtrade entry price
Returns: (float) price
recent_closedtrade_exit_price()
get recent closedtrade exit price
Returns: (float) price
recent_opentrade_entry_time()
get recent opentrade entry time
Returns: (int) time
recent_closedtrade_entry_time()
get recent closedtrade entry time
Returns: (int) time
recent_closedtrade_exit_time()
get recent closedtrade exit time
Returns: (int) time
time_since_recent_opentrade_entry()
get time since recent opentrade entry
Returns: (int) time
time_since_recent_closedtrade_entry()
get time since recent closedtrade entry
Returns: (int) time
time_since_recent_closedtrade_exit()
get time since recent closedtrade exit
Returns: (int) time
recent_opentrade_size()
get recent opentrade size
Returns: (float) size
recent_closedtrade_size()
get recent closedtrade size
Returns: (float) size
all_opentrades_size()
get all opentrades size
Returns: (float) size
recent_opentrade_profit()
get recent opentrade profit
Returns: (float) profit
all_opentrades_profit()
get all opentrades profit
Returns: (float) profit
recent_closedtrade_profit()
get recent closedtrade profit
Returns: (float) profit
recent_opentrade_max_runup()
get recent opentrade max runup
Returns: (float) runup
recent_closedtrade_max_runup()
get recent closedtrade max runup
Returns: (float) runup
recent_opentrade_max_drawdown()
get recent opentrade maxdrawdown
Returns: (float) mdd
recent_closedtrade_max_drawdown()
get recent closedtrade maxdrawdown
Returns: (float) mdd
max_open_trades_drawdown()
get max open trades drawdown
Returns: (float) mdd
recent_opentrade_commission()
get recent opentrade commission
Returns: (float) commission
recent_closedtrade_commission()
get recent closedtrade commission
Returns: (float) commission
qty_by_percent_of_equity(percent)
get qty by percent of equtiy
Parameters:
percent : (series float) percent that you want to set
Returns: (float) quantity
qty_by_percent_of_position_size(percent)
get size by percent of position size
Parameters:
percent : (series float) percent that you want to set
Returns: (float) size
is_day_change()
get bool change of day
Returns: (bool) day is change or not
is_in_trade()
get bool using number of bars
Returns: (bool) allowedToTrade
discord_message(name, message)
get json format discord message
Parameters:
name : (string) name of bot
message : (string) message that you want to send
Returns: (string) json format string
telegram_message(chat_id, message)
get json format telegram message
Parameters:
chat_id : (string) chatId of bot
message : (string) message that you want to send
Returns: (string) json format string
MetaWorldEngineFilterLibrary3Library "MetaWorldEngineFilterLibrary3"
GetCandleStickSize(Rule, Rule)
returns size of the candle
Parameters:
Rule : 1: (float) _src_high
Rule : 2: (float) _src_low
Returns: candlestick size
GetCandleStickBodySize(Rule, Rule)
returns size of the candle body
Parameters:
Rule : 1: (float) _src_open
Rule : 2: (float) _src_close
Returns: candlestick body size
FilterLongerLowerWickCandles(Rule, Rule, Rule)
Alters Candlestick Value to Magnify Candles with Long Wicks
Parameters:
Rule : 1: (float) open
Rule : 2: (float) close
Rule : 2: (float) low
Returns: Midpoint of the candle body less the lower wick. If value returned has a large delta from midpoint of the body, then it is short wick
IsBullish(Rule, Rule)
Determine if Candle is Bullish or Bearish
Parameters:
Rule : 1: (float) open
Rule : 2: (float) close
Returns: True is Bullish
IsDoji(Rule, Rule)
Determine if Candle is a Doji
Parameters:
Rule : 1: (int) Candle Index
Rule : 2: (float) Percentage of candle size. Larger the Number the less stringent the doji criterion
Returns: True if a Doji
MACD(Rule, Rule, Rule, Rule)
Computes MACD
Parameters:
Rule : 1: (float) _src
Rule : 2: (int) _fastLength input fast ema length
Rule : 2: (int) _slowLength input slow ema length
Rule : 3: (int) _signalLength input length of signal line (sma of MACD line)
Returns: Returns MACD and Signal Line
isFastSlowCrossed(Rule, Rule)
Computes if SeriesA crosses SeriesB
Parameters:
Rule : 1: (float) Series Input
Rule : 2: (float) Series Input
Returns: if SeriesA crosses SeriesB then true else false
isReversalUpTrend(Rule, Rule)
Computes if SeriesA crosses over SeriesB to determine reversal uptrend
Parameters:
Rule : 1: (float) Series Input
Rule : 2: (float) Series Input
Returns: if SeriesA crosses over SeriesB then true else false
isReversalDownTrend(Rule, Rule)
Computes if SeriesA crosses over SeriesB to determine reversal uptrend
Parameters:
Rule : 1: (float) Series Input
Rule : 2: (float) Series Input
Returns: if SeriesA crosses over SeriesB then true else false
SSMA(Rule, Rule)
Computes smoothed SMA
Parameters:
Rule : 1: (float) source
Rule : 2: (float) sma length
Returns: a single concatenated string for evaluation
GetTimeFrame()
Get Current timeframe in minutes
Returns: an integer value in minutes
getMA(float, int, string, float)
Gets a Moving Average based on type
Parameters:
float : _src The source data
int : length The MA period
string : maType The type of MA
float : sigma / smoothness of ALMA, else NA
Returns: A moving average with the given parameters
obvFilterThis library comes with everything you need to add an On Balance Volume (OBV) filter to your strategy.
getOnBalanceVolumeFilter(source, maType, fastMaLength, fastMaLength)
Get the fast and slow moving average for on balance volume
Parameters:
source : hook this up to an 'input.source' input
maType : Choose from EMA, SMA, RMA, or WMA
fastMaLength : int smoothing length for fast moving average
fastMaLength : int smoothing length for fast moving average int smoothing length for slow moving average
Returns: Tuple with fast obv moving average and slow obv moving average
Add this to your strategy
▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾ ▾
import jordanfray/obvFilter/1 as obv
obvSource = input.source(defval=close, title="OBV Source", group="On Balance Volume Filter")
obvMaType = input.string(defval="EMA", title="OBV Smoothing Type", options = , group="On Balance Volume Filter")
fastMaLength = input.int(title = "Fast OBV MA Length", defval = 9, minval = 2, maxval = 200, group="On Balance Volume Filter")
slowMaLength = input.int(title = "Slow OBV MA Length", defval = 21, minval = 1, maxval = 200, group="On Balance Volume Filter")
= obv.getOnBalanceVolumeFilter(obvSource, obvMaType, fastMaLength, slowMaLength)
PlurexSignalLibrary "PlurexSignal"
Provides functions that wrap the built in TradingView strategy functions so you can seemlessly integrate with Plurex Signal automation.
NOTE: Be sure to set your strategy close_entries_rule="ANY" and pyramiding=20 or some other amount appropriate to your strategy in order to have multiple entries.
plurexMarket()
Build a Plurex market string from a base and quote asset symbol.
Returns: A market string that can be used in Plurex Signal messages.
tickerToPlurexMarket()
Builds Plurex market string from the syminfo
Returns: A market string that can be used in Plurex Signal messages.
simpleMessage(secret, action, marketOverride)
Builds Plurex Signal Message json to be sent to a Signal webhook
Parameters:
secret : The secret for your Signal on plurex
action : The action of the message. One of .
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
long(secret, marketOverride, qty)
Open a new long entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
qty : Corresponds to strategy.entry qty
short(secret, marketOverride, qty)
Open a new short entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
qty : Corresponds to strategy.entry qty
closeAll(secret, marketOverride)
Close all positions. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeLongs(secret, marketOverride)
Close all longs. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeShorts(secret, marketOverride)
Close all shorts. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeLastLong(secret, marketOverride)
Close last long entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeFirstLong(secret, marketOverride)
Close first long entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeLastShort(secret, marketOverride)
Close last short entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeFirstShort(secret, marketOverride)
Close first short entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
CalulateWinLossLibrary "CalulateWinLoss"
TODO: add library description here
colorwhitered(x)
TODO: add function description here
Parameters:
x : TODO: add parameter x description here
Returns: TODO: add what function returns
colorredwhite()
cal()
LibBacktestingDayRangeLibrary "LibBacktestingDayRange"
TODO: add library description here
import Nut_Satit/CalulateWinLoss/version as backtest
rangdate(startDate, finishDate)
TODO: add function description here
Parameters:
startDate : TODO: add parameter startDate description here
finishDate : TODO: add parameter finishDate description here
Returns: TODO: add what function returns
time_cond : TODO: insert variable and buy or sell condition
Binance_Min_Limit_Order_amount_libraryLibrary "Binance_Min_Limit_Order_amount_library"
TODO: This library give us the minimum Limit Order amount for the contract in Binance.
m_qty(n_v, m_fee, t_fee, cost, m_t)
TODO: it give us the Minimum Qty for the trading in Binance
Parameters:
n_v : TODO: min_notional_value. 5 dollar is the minimum notional amount in Binance at the moment.
m_fee : TODO: maker_fee %
t_fee : TODO: taker_fee %
cost : TODO: your investing money
m_t : TODO: if you want Limit_Order, put the "T", if you want Market_Order, put the "M" defval="M"
Returns: TODO: for the coin of binance on your chart,
Reference: www.binance.com
LevelsManagerLibrary "LevelsManager"
TODO: Track up to 6 TakeProfits and 1 StopLoss achievement for one or many of your buy/sell conditions.
manageTrade(bool, bool, bool, string, string, float, float, bool, bool, bool, bool, bool, bool, float, float, float, float, float, float, float)
Track TakeProfits and StopLoss achievement for one or many of your buy/sell conditions. CHECK the commented section: "Function @manageTrade" for Description
Parameters:
bool : useSignal.
bool : b_gameOVer.
bool : b_gameOVer.
string : bName.
string : sName.
float : buyEntrySource.
float : sellEntrySource.
bool : useTp1.
bool : useTp2.
bool : useTp3.
bool : useTp4.
bool : useTp5.
bool : useTp6.
float : tp1x.
float : tp2x.
float : tp3x.
float : tp4x.
float : tp5x.
float : tp6x.
float : slx.
Returns: check commented section: "Function @manageTrade".
showOnlyFirstOccurence(booleanInput)
Single out the occurence of a bool series between to 2 bool series.
Parameters:
booleanInput : to activate or deactivate occurences filtering.
Returns: filterred or not bool series.
FunctionKellyCriterionLibrary "FunctionKellyCriterion"
Kelly criterion methods.
the kelly criterion helps with the decision of how much one should invest in
a asset as long as you know the odds and expected return of said asset.
simplified(win_p, rr)
simplified version of the kelly criterion formula.
Parameters:
win_p : float, probability of winning.
rr : float, reward to risk rate.
Returns: float, optimal fraction to risk.
usage:
simplified(0.55, 1.0)
partial(win_p, loss_p, win_rr, loss_rr)
general form of the kelly criterion formula.
Parameters:
win_p : float, probability of the investment returns a positive outcome.
loss_p : float, probability of the investment returns a negative outcome.
win_rr : float, reward on a positive outcome.
loss_rr : float, reward on a negative outcome.
Returns: float, optimal fraction to risk.
usage:
partial(0.6, 0.4, 0.6, 0.1)
from_returns(returns)
Calculate the fraction to invest from a array of returns.
Parameters:
returns : array trade/asset/strategy returns.
Returns: float, optimal fraction to risk.
usage:
from_returns(array.from(0.1,0.2,0.1,-0.1,-0.05,0.05))
final_f(fraction, max_expected_loss)
Final fraction, eg. if fraction is 0.2 and expected max loss is 10%
then you should size your position as 0.2/0.1=2 (leverage, 200% position size).
Parameters:
fraction : float, aproximate percent fraction invested.
max_expected_loss : float, maximum expected percent on a loss (ex 10% = 0.1).
Returns: float, final fraction to invest.
usage:
final_f(0.2, 0.5)
hpr(fraction, trade, biggest_loss)
Holding Period Return function
Parameters:
fraction : float, aproximate percent fraction invested.
trade : float, profit or loss in a trade.
biggest_loss : float, value of the biggest loss on record.
Returns: float, multiplier of effect on equity so that a win of 5% is 1.05 and loss of 5% is 0.95.
usage:
hpr(fraction=0.05, trade=0.1, biggest_loss=-0.2)
twr(returns, rr, eps)
Terminal Wealth Relative, returns a multiplier that can be applied
to the initial capital that leadds to the final balance.
Parameters:
returns : array, list of trade returns.
rr : float , reward to risk rate.
eps : float , minimum resolution to void zero division.
Returns: float, optimal fraction to invest.
usage:
twr(returns=array.from(0.1,-0.2,0.3), rr=0.6)
ghpr(returns, rr, eps)
Geometric mean Holding Period Return, represents the average multiple made on the stake.
Parameters:
returns : array, list of trade returns.
rr : float , reward to risk rate.
eps : float , minimum resolution to void zero division.
Returns: float, multiplier of effect on equity so that a win of 5% is 1.05 and loss of 5% is 0.95.
usage:
ghpr(returns=array.from(0.1,-0.2,0.3), rr=0.6)
run_coin_simulation(fraction, initial_capital, n_series, n_periods)
run multiple coin flipping (binary outcome) simulations.
Parameters:
fraction : float, fraction of capital to bet.
initial_capital : float, capital at the start of simulation.
n_series : int , number of simulation series.
n_periods : int , number of periods in each simulation series.
Returns: matrix(n_series, n_periods), matrix with simulation results per row.
usage:
run_coin_simulation(fraction=0.1)
run_asset_simulation(returns, fraction, initial_capital)
run a simulation over provided returns.
Parameters:
returns : array, trade, asset or strategy percent returns.
fraction : float , fraction of capital to bet.
initial_capital : float , capital at the start of simulation.
Returns: array, array with simulation results.
usage:
run_asset_simulation(returns=array.from(0.1,-0.2,0.-3,0.4), fraction=0.1)
strategy_win_probability()
calculate strategy() current probability of positive outcome in a trade.
strategy_avg_won()
calculate strategy() current average won on a trade with positive outcome.
strategy_avg_loss()
calculate strategy() current average lost on a trade with negative outcome.
threengine_global_automation_libraryLibrary "threengine_global_automation_library"
A collection of functions used for trade automation
getBaseCurrency()
Gets the base currency for the chart's ticker. Supported trade pairs are USD, USDT, USDC, BTC, and PERP.
Returns: Base currency as a string
getChartSymbol()
Get the current chart's symbol without the base currency appended to it. Supported trade paris are USD, USDT, USDC, BTC, and PERP.
Returns: Ssymbol and base currency
getDecimals()
Calculates how many decimals are on the quote price of the current market
Returns: The current deimal places on the market quote price
checkVar()
Plot a string as a label on the chart to test variable value. Use str.tostring() for any variable that isn't a string.
Returns: Label with stringified variable
getStrategyAlertMessage()
Generates stringified JSON for a limit order that can be passed to the strategy alert_message for a long entry.
Returns: Stringifed JSON for a long entry
taGetAdx()
Calculates the Average Directional Index
Returns: The value of ADX as a float
taGetEma()
Calculates the EMA based on a type, source, and length. Supported types are EMA, SMA, RMA, and WMA.
Returns: The value of the selected EMA
isBetweenTwoTimes()
Checks to see if within a rage based on two times
@retunrs true/false boolean
getAllTradeIDs()
This gets all closed trades and open trades
@retunrs an array of all open and closed trade ID's
getOpenTradeIDs()
This gets all open trades
@retunrs an array of all open trade ID's
orderAlreadyExists()
This checks to see if a provided order id uses the getAllTradeIDs() function to check
@retunrs an array of all open and closed trade ID's
orderCurrentlyExists()
This checks to see if a provided order id uses the getAllTradeIDs() function to check
Returns: an array of all open and closed trade ID's
getContractCount()
calulates the number of contracts you can buy with a set amount of capital and a limit price
Returns: number of contracts you can buy based on amount of capital you want to use and a price
getLadderSteps()
Returns: array of ladder entry prices and amounts based on total amount you want to invest across all ladder rungs and either a range between ladderStart and LadderStop based on specificed number of ladderRungs OR ladderStart, ladderRungs, and LadderSpacingPercent
PlurexSignalIntegrationLibrary "PlurexSignalIntegration"
Provides tools for integrating Strategies and Alerts into plurex.io signals.
plurexMarket() Build a Plurex market from a base and quote asset symbol.
Returns: A market string that can be used in Plurex Signal messages.
tickerToPlurexMarket() Builds simple Plurex market string from the syminfo
Returns: A market string that can be used in Plurex Signal messages.
simpleMessage(secret, action, marketOverride) Builds simple Plurex Signal Messages
Parameters:
secret : The secret for your Signal on plurex
action : The action of the message. One of .
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
executeStrategy(secret, openLong, openShort, closeLongs, closeShorts, marketOverride) Executes strategy actions with Plurex Signal messages
Parameters:
secret : The secret for your Signal on plurex
openLong : Strategy should open long if true, aggregated with other boolean values
openShort : Strategy should open short if true, aggregated with other boolean values
closeLongs : Strategy should close longs if true, aggregated with other boolean values
closeShorts : Strategy should close shorts if true, aggregated with other boolean values
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
fontilabLibrary "fontilab"
Provides function's indicators for pivot - trend - resistance.
pivots(src, lenght, isHigh) Detecting pivot points (and returning price + bar index.
Parameters:
src : The chart we analyse.
lenght : Used for the calcul.
isHigh : lookging for high if true, low otherwise.
Returns: The bar index and the price of the pivot.
calcDevThreshold(tresholdMultiplier, closePrice) Calculate deviation threshold for identifying major swings.
Parameters:
tresholdMultiplier : Usefull to equilibrate the calculate.
closePrice : Close price of the chart wanted.
Returns: The deviation threshold.
calcDev(basePrice, price) Custom function for calculating price deviation for validating large moves.
Parameters:
basePrice : The reference price.
price : The price tested.
Returns: The deviation.
pivotFoundWithLines(dev, isHigh, index, price, dev_threshold, isHighLast, pLast, iLast, lineLast) Detecting pivots that meet our deviation criteria.
Parameters:
dev : The deviation wanted.
isHigh : The type of pivot tested (high or low).
index : The Index of the pivot tested.
price : The chart price wanted.
dev_threshold : The deviation treshold.
isHighLast : The type of last pivot.
pLast : The pivot price last.
iLast : Index of the last pivot.
lineLast : The lst line.
Returns: The Line and bool is pivot High.
getDeviationPivots(thresholdMultiplier, depth, lineLast, isHighLast, iLast, pLast, deleteLines, closePrice, highPrice, lowPrice) Get pivot that meet our deviation criteria.
Parameters:
thresholdMultiplier : The treshold multiplier.
depth : The depth to calculate pivot.
lineLast : The last line.
isHighLast : The type of last pivot
iLast : Index of the last pivot.
pLast : The pivot price last.
deleteLines : If the line are draw or not.
closePrice : The chart close price.
highPrice : The chart high price.
lowPrice : The chart low price.
Returns: All pivot the informations.
getElIntArrayFromEnd() Get the last element of an int array.
getElFloatArrayFromEnd() Get the last element of an float array.
getElBoolArrayFromEnd() Get the last element of a bool array.
isTrendContinuation(isTrendUp, arrayBounds, lastPrice, precision) Check if last price is between bounds array.
Parameters:
isTrendUp : Is actual trend up.
arrayBounds : The trend array.
lastPrice : The pivot Price that just be found.
precision : The percent we add to actual bounds to validate a move.
Returns: na if price is between bounds, true if continuation, false if not.
getTrendPivots(trendBarIndexes, trendPrices, trendPricesIsHigh, interBarIndexes, interPrices, interPricesIsHigh, isTrendHesitate, isTrendUp, trendPrecision, pLast, iLast, isHighLast) Function to update array and trend related to pivot trend interpretation.
Parameters:
trendBarIndexes : The array trend bar index.
trendPrices : The array trend price.
trendPricesIsHigh : The array trend is high.
interBarIndexes : The array inter bar index.
interPrices : The array inter price.
interPricesIsHigh : The array inter ishigh.
isTrendHesitate : The actual status of is trend hesitate.
isTrendUp : The actual status of is trend up.
trendPrecision : The var precision to add in "iscontinuation" function.
pLast : The last pivot price.
iLast : The last pivot bar index.
isHighLast : The last pivot "isHigh".
Returns: trend & inter arrays, is trend hesitate, is trend up.
drawBoundLines(startIndex, startPrice, endIndex, endPrice, breakingPivotIndex, breakingPivotPrice, isTrendUp) Draw bounds and breaking line of the trend.
Parameters:
startIndex : Index of the first bound line.
startPrice : Price of first bound line.
endIndex : Index of second bound line.
endPrice : price of second bound line.
breakingPivotIndex : The breaking line index.
breakingPivotPrice : The breaking line price.
isTrendUp : The actual status of the trend.
Returns: The lines bounds and breaking line.
Strategy Table LibraryLibrary "table_library"
TODO: With this library, you can add tables to your strategies.
strategy_table()
Returns: Strategy Profit Table
Adds a table to the graph of the strategy for which you are calling the function. You can see data such as net profit in this table.
No parameters. Just call the function inside the strategy.
Example Code :
import only_fibonacci/table_lib/1 as st
st.strategy_table()
MonthlyReturnsVsMarketLibrary "MonthlyReturnsVsMarket" is a repackaging of the script here
Credits to @QuantNomad for orginal script
Now you can avoid to pollute your own strategy's code with the monthly returns table code and just import the library and call displayMonthlyPnL(int precision) function
To be used in strategy scripts.
RicardoLibraryLibrary "RicardoLibrary"
Ricardo's personal Library
GetPipValue() GetPipValue
Returns: Pip value of Symbol
Calculate_SL(IsLong) Calculate_SL: Calcultes Stop Loss
Parameters:
IsLong : If true, then I am going to enter a long position, if false then Short position
Returns: Stop loss Price
