Let's execute a strategy for the StatArb signal using the following steps:

1. Now, using the StatArb signal we just computed, we can build a strategy similar to the trend-following strategy we saw before. Let's start by looking at the trading logic that controls the sell trades:

  if ((final_delta_projected < StatArb_VALUE_FOR_SELL_ENTRY and abs(close_price - last_sell_price) > MIN_PRICE_MOVE_FROM_LAST_TRADE) # StatArb above sell entry threshold, we should sell
      or
      (position > 0 and (open_pnl > MIN_PROFIT_TO_CLOSE))): # long from negative StatArb and StatArb has gone positive or position is profitable, sell to close position
    orders.append(-1) # mark the sell trade
    last_sell_price = close_price
    position -= NUM_SHARES_PER_TRADE # reduce position by the size of this trade
    sell_sum_price_qty += (close_price * NUM_SHARES_PER_TRADE) # update vwap sell-price
    sell_sum_qty += NUM_SHARES_PER_TRADE
    print("Sell ", NUM_SHARES_PER_TRADE, " @ ", close_price, "Position: ", position)
    print("OpenPnL: ", open_pnl, " ClosedPnL: ", closed_pnl, " TotalPnL: ", (open_pnl + closed_pnl))

2. Now, let's look at the buy trade logic, which is quite similar to the sell trade logic:

  elif ((final_delta_projected > StatArb_VALUE_FOR_BUY_ENTRY and abs(close_price - last_buy_price) > MIN_PRICE_MOVE_FROM_LAST_TRADE) # StatArb below buy entry threshold, we should buy
        or
        (position < 0 and (open_pnl > MIN_PROFIT_TO_CLOSE))): # short from positive StatArb and StatArb has gone negative or position is profitable, buy to close position
    orders.append(+1) # mark the buy trade
    last_buy_price = close_price
    position += NUM_SHARES_PER_TRADE # increase position by the size of this trade
    buy_sum_price_qty += (close_price * NUM_SHARES_PER_TRADE) # update the vwap buy-price
    buy_sum_qty += NUM_SHARES_PER_TRADE
    print("Buy ", NUM_SHARES_PER_TRADE, " @ ", close_price, "Position: ", position)
    print("OpenPnL: ", open_pnl, " ClosedPnL: ", closed_pnl, " TotalPnL: ", (open_pnl + closed_pnl))
  else:
    # No trade since none of the conditions were met to buy or sell
    orders.append(0)
  positions.append(position)

3. Finally, let's also look at the position management and PnL update logic, very similar to previous trading strategies:

  # This section updates Open/Unrealized & Closed/Realized positions
  open_pnl = 0
  if position > 0:
    if sell_sum_qty > 0: # long position and some sell trades have been made against it, close that amount based on how much was sold against this long position
      open_pnl = abs(sell_sum_qty) * (sell_sum_price_qty / sell_sum_qty - buy_sum_price_qty / buy_sum_qty)
    # mark the remaining position to market i.e. pnl would be what it would be if we closed at current price
    open_pnl += abs(sell_sum_qty - position) * (close_price - buy_sum_price_qty / buy_sum_qty)
  elif position < 0:
    if buy_sum_qty > 0: # short position and some buy trades have been made against it, close that amount based on how much was bought against this short position
      open_pnl = abs(buy_sum_qty) * (sell_sum_price_qty / sell_sum_qty - buy_sum_price_qty / buy_sum_qty)
    # mark the remaining position to market i.e. pnl would be what it would be if we closed at current price
    open_pnl += abs(buy_sum_qty - position) * (sell_sum_price_qty / sell_sum_qty - close_price)
  else:
    # flat, so update closed_pnl and reset tracking variables for positions & pnls
    closed_pnl += (sell_sum_price_qty - buy_sum_price_qty)
    buy_sum_price_qty = 0
    buy_sum_qty = 0
    sell_sum_price_qty = 0
    sell_sum_qty = 0
    last_buy_price = 0
    last_sell_price = 0

  pnls.append(closed_pnl + open_pnl)