class_docstr: Applies some basic trade analysis for a trading strategy (as defined by TradingModel). Use PyFolio to create some
  basic trading statistics. Also allows you test multiple parameters for a specific strategy (like TC).
class_docstr_tok: ["Applies","some","basic","trade","analysis","for","a","trading","strategy","(","as","defined","by","TradingModel",")",".","Use","PyFolio","to","create","some","basic","trading","statistics",".","Also","allows","you","test","multiple","parameters","for","a","specific","strategy","(","like","TC",")","."]
code: def run_tc_shock(
      self,
      strategy,
      tc=None,
      run_in_parallel=False,
      reload_market_data=True,
  ):
      if tc is None:
          tc = [0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0]
  
      parameter_list = [{"spot_tc_bp": x} for x in tc]
      pretty_portfolio_names = [
          str(x) + "bp" for x in tc
      ]  # names of the portfolio
      parameter_type = "TC analysis"  # broad type of parameter name
  
      return self.run_arbitrary_sensitivity(
          strategy,
          parameter_list=parameter_list,
          pretty_portfolio_names=pretty_portfolio_names,
          parameter_type=parameter_type,
          run_in_parallel=run_in_parallel,
          reload_market_data=reload_market_data,
      )
  
imports: import datetime
  import pandas
  import copy
  from chartpy import Chart, Style, ChartConstants
  from findatapy.timeseries import Calculations, Timezone
  from findatapy.util.loggermanager import LoggerManager
  from finmarketpy.backtest import Backtest
  from finmarketpy.util.marketconstants import MarketConstants
  from findatapy.util.swimpool import SwimPool
label_desc: Use image node_id 5 for calling the TradeAnalysis obj's underlying member method code with example usage: obj.run_tc_shock(strategy, tc, run_in_parallel, reload_market_data) and returns: self