4

I am researching/backtesting a trading system.

I have a Pandas dataframe containing OHLC data and have added several calculated columns which identify price patterns that I will use as signals to initiate positions.

I would now like to add a further column that will keep track of the current net position. I have tried using df.apply(), but passing the dataframe itself as the argument instead of the row object, as with the latter I seem to be unable to look back at previous rows to determine whether they resulted in any price patterns:

open_campaigns = []
Campaign = namedtuple('Campaign', 'open position stop')

def calc_position(df):
  # sum of current positions + any new positions

  if entered_long(df):
    open_campaigns.add(
        Campaign(
            calc_long_open(df.High.shift(1)), 
            calc_position_size(df), 
            calc_long_isl(df)
        )
    )

  return sum(campaign.position for campaign in open_campaigns)

def entered_long(df):
  return buy_pattern(df) & (df.High > df.High.shift(1))

df["Position"] = df.apply(lambda row: calc_position(df), axis=1)

However, this returns the following error:

ValueError: ('The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()', u'occurred at index 1997-07-16 08:00:00')

Rolling window functions would seem to be the natural fit, but as I understand it, they only act on a single time series or column, so wouldn't work either as I need to access the values of multiple columns at multiple timepoints.

How should I in fact be doing this?

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1 に答える 1

6

この問題の原因はNumPyにあります。

def entered_long(df):
  return buy_pattern(df) & (df.High > df.High.shift(1))

entered_long配列のようなオブジェクトを返しています。NumPyは、配列がTrueかFalseかを推測することを拒否します。

In [48]: x = np.array([ True,  True,  True], dtype=bool)

In [49]: bool(x)

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

これを修正するには、anyまたはを使用allして、配列がTrueになる意味を指定します。

def calc_position(df):
  # sum of current positions + any new positions

  if entered_long(df).any():  # or .all()

のany()項目のいずれかがTrueの場合、メソッドはTrueを返しますentered_long(df)。のall()すべての項目がTrueの場合、メソッドはTrueを返しますentered_long(df)。

于 2013-01-17T19:08:00.270 に答える