Added cumulative additive flag

README.md

@@ -117,6 +117,8 @@ In finmarketpy/examples you will find several examples, including some simple tr
 
 # finmarketpy log
 
+* 11 Nov 2020
+    * Added cumulative additive index flag for backtests
 * 20 Oct 2020
     * Fixed missing GBP depo tickers
     * Fixed startup on newer MacOS

finmarketpy/backtest/backtestengine.py

@@ -446,23 +446,33 @@ def calculate_trading_PnL(self, br, asset_a_df, signal_df, contract_value_df, ru
             self._portfolio_cum = resultsC.get()
 
         else:
-            # calculate return statistics of the each asset/signal after signal leverage (but before portfolio level constraints)
+            # Calculate return statistics of the each asset/signal after signal leverage (but before portfolio level constraints)
             # self._ret_stats_pnl.calculate_ret_stats()
 
-            # calculate return statistics of the each asset/signal after signal leverage AND after portfolio level constraints
+            # Calculate return statistics of the each asset/signal after signal leverage AND after portfolio level constraints
             # self._ret_stats_pnl_components.calculate_ret_stats()
 
-            # calculate return statistics of the final portfolio
+            # Calculate return statistics of the final portfolio
             # self._ret_stats_portfolio.calculate_ret_stats()
 
-            # calculate individual signals cumulative P&L after signal leverage but before portfolio level constraints
-            self._pnl_cum = calculations.create_mult_index(self._pnl)
+            # Calculate final portfolio cumulative P&L
+            if br.cum_index == 'mult':
+                # Calculate individual signals cumulative P&L after signal leverage but before portfolio level constraints
+                self._pnl_cum = calculations.create_mult_index(self._pnl)
 
-            # calculate individual signals cumulative P&L after signal leverage AND after portfolio level constraints
-            self._components_pnl_cum = calculations.create_mult_index(self._components_pnl)
+                # Calculate individual signals cumulative P&L after signal leverage AND after portfolio level constraints
+                self._components_pnl_cum = calculations.create_mult_index(self._components_pnl)
 
-            # calculate final portfolio cumulative P&L
-            self._portfolio_cum = calculations.create_mult_index(self._portfolio)  # portfolio cumulative P&L
+                self._portfolio_cum = calculations.create_mult_index(self._portfolio)  # portfolio cumulative P&L
+
+            elif br.cum_index == 'add':
+                # Calculate individual signals cumulative P&L after signal leverage but before portfolio level constraints
+                self._pnl_cum = calculations.create_add_index(self._pnl)
+
+                # Calculate individual signals cumulative P&L after signal leverage AND after portfolio level constraints
+                self._components_pnl_cum = calculations.create_add_index(self._components_pnl)
+
+                self._portfolio_cum = calculations.create_add_index(self._portfolio)  # portfolio cumulative P&L
 
         logger.info("Completed cumulative index calculations")
 
@@ -1329,7 +1339,10 @@ def compare_strategy_vs_benchmark(self, br, strategy_df, benchmark_df):
                 strategy_benchmark_df = filter.filter_time_series_by_date(br.plot_start, br.finish_date,
                                                                           strategy_benchmark_df)
 
-            strategy_benchmark_df = calculations.create_mult_index_from_prices(strategy_benchmark_df)
+            if br.cum_index == 'mult':
+                strategy_benchmark_df = calculations.create_mult_index_from_prices(strategy_benchmark_df)
+            elif br.cum_index == 'add':
+                strategy_benchmark_df = calculations.create_add_index_from_prices(strategy_benchmark_df)
 
             self._strategy_benchmark_pnl = benchmark_df
             self._strategy_benchmark_pnl_ret_stats = ret_stats
@@ -1957,7 +1970,10 @@ def calculate_vol_adjusted_index_from_prices(self, prices_df, br):
 
         returns_df, leverage_df = self.calculate_vol_adjusted_returns(prices_df, br, returns=False)
 
-        return calculations.create_mult_index(returns_df)
+        if br.cum_index == 'mult':
+            return calculations.create_mult_index(returns_df)
+        elif br.cum_index == 'add':
+            return calculations.create_add_index(returns_df)
 
     def calculate_vol_adjusted_returns(self, returns_df, br, returns=True):
         """Adjusts returns for a vol target

finmarketpy/backtest/backtestrequest.py

@@ -75,6 +75,11 @@ def __init__(self):
         # annualization factor for return stats (and should we resample data first before calculating it?)
         self.__ann_factor = 252
         self.__resample_ann_factor = None
+
+        # how do we create a cumulative index of strategy returns
+        # either multiplicative starting a 100
+        # or additive starting at 0
+        self.__cum_index = 'mult' # 'mult' or 'add'
 
     ##### properties for output of the backtest
     @property
@@ -376,3 +381,11 @@ def resample_ann_factor(self):
     @resample_ann_factor.setter
     def resample_ann_factor(self, resample_ann_factor):
         self.__resample_ann_factor = resample_ann_factor
+
+    @property
+    def cum_index(self):
+        return self.__cum_index
+
+    @cum_index.setter
+    def cum_index(self, cum_index):
+        self.__cum_index = cum_index

finmarketpy/economics/quickchart.py

@@ -37,7 +37,7 @@ def __init__(self, engine='plotly', data_source='bloomberg', market_data_generat
     def plot_chart(self, tickers=None, tickers_rhs=None, start_date=None, finish_date=None,
                    chart_file=None, chart_type='line', title='',
                    fields={'close' : 'PX_LAST'}, freq='daily', source='Web', brand_label='Cuemacro', display_brand_label=True,
-                   reindex=False, yoy=False, plotly_plot_mode='offline_png',
+                   reindex=False, additive_index=False, yoy=False, plotly_plot_mode='offline_png',
                    quandl_api_key=dataconstants.quandl_api_key,
                    fred_api_key=dataconstants.fred_api_key,
                    alpha_vantage_api_key=dataconstants.alpha_vantage_api_key, df=None):
@@ -98,6 +98,11 @@ def plot_chart(self, tickers=None, tickers_rhs=None, start_date=None, finish_dat
 
             style.y_title = 'Reindexed from 100'
 
+        if additive_index:
+            df = (df - df.shift(1)).cumsum()
+
+            style.y_title = 'Additive changes from 0'
+
         if yoy:
             if freq == 'daily':
                 obs_in_year = 252

finmarketpy_examples/tradingmodelfxtrend_example.py

@@ -80,6 +80,9 @@ def load_parameters(self, br = None):
         # Tech params
         br.tech_params.sma_period = 200
 
+        # To make additive indices
+        # br.cum_index = 'add'
+
         return br
 
     def load_assets(self, br = None):