Version 1.0

Quantsbin.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: Quantsbin
-Version: 1.0
+Version: 1.0a0
 Summary: Quantitative Finance Tools
 Home-page: https://github.com/quantsbin/Quantsbin
 Author: Quantsbin
@@ -10,11 +10,11 @@ Description: # Quantsbin
 
         Open source library for finance.
 
-        Quantsbin 1.0, which started as a weekend project is currently in its initial phase and
+        Quantsbin 1.0.a, which started as a weekend project is currently in its initial phase and
         incorporates tools for pricing and plotting of vanilla option prices, greeks and various other analysis around them.
         We are working on optimising calculations and expanding the scope of library in multiple directions for future releases.
 
-        ## Quantsbin 1.0 includes
+        ## Quantsbin 1.0.a includes
            1. Option payoff, premium and greeks calculation for vanilla options on Equity, FX, Commodity and Futures.
            2. Capability to calculate greeks numerically for all models and also analytically for Black Scholes Model.
            3. Price vanilla options with European expiry using BSM, Binomial tree and MonteCarlo with option to 
@@ -53,10 +53,10 @@ Description: # Quantsbin
         For collaboration and suggestion reach us at [Quantsbin](http://www.quantsbin.com/)
 
         ## Tutorial
-        Refer to our [Tutorial](http://www.quantsbin.com/tutorial/) page
+        Refer to our [Tutorial](https://quantsbin.wordpress.com/2018/07/05/introduction-to-options-and-option-pricing-using-python-open-source-library-quantsbin/) page
 
         ## Note
-        For Quantsbin 0.0.0 testing and documentation are still WIP.
+        For Quantsbin 1.0.a testing and documentation are still WIP.
 
 Platform: UNKNOWN
 Description-Content-Type: text/markdown

README.md

@@ -2,11 +2,11 @@
 
 Open source library for finance.
 
-Quantsbin 1.0, which started as a weekend project is currently in its initial phase and
+Quantsbin 1.0.a, which started as a weekend project is currently in its initial phase and
 incorporates tools for pricing and plotting of vanilla option prices, greeks and various other analysis around them.
 We are working on optimising calculations and expanding the scope of library in multiple directions for future releases.
 
-## Quantsbin 1.0 includes
+## Quantsbin 1.0.a includes
    1. Option payoff, premium and greeks calculation for vanilla options on Equity, FX, Commodity and Futures.
    2. Capability to calculate greeks numerically for all models and also analytically for Black Scholes Model.
    3. Price vanilla options with European expiry using BSM, Binomial tree and MonteCarlo with option to 
@@ -45,7 +45,7 @@ Refer to our [Documentation](http://www.quantsbin.com/documentation/) page
 For collaboration and suggestion reach us at [Quantsbin](http://www.quantsbin.com/)
 
 ## Tutorial
-Refer to our [Tutorial](http://www.quantsbin.com/tutorial/) page
+Refer to our [Tutorial](https://quantsbin.wordpress.com/2018/07/05/introduction-to-options-and-option-pricing-using-python-open-source-library-quantsbin/) page
 
 ## Note
-For Quantsbin 1.0 testing and documentation are still WIP.
+For Quantsbin 1.0.a testing and documentation are still WIP.

build/lib/quantsbin/derivativepricing/namesnmapper.py

@@ -37,14 +37,14 @@ class UnderlyingParameters(Enum):
 
 
 class RiskParameter(Enum):
-    DELTA = 'Delta'
-    GAMMA = 'Gamma'
-    THETA = 'Theta'
-    VEGA = 'Vega'
-    RHO = 'Rho'
-    PHI = 'Phi'
-    RHO_FOREIGN = 'Rho_foreign'
-    RHO_CONV = 'Rho_conv_yield'
+    DELTA = 'delta'
+    GAMMA = 'gamma'
+    THETA = 'theta'
+    VEGA = 'vega'
+    RHO = 'rho'
+    PHI = 'phi'
+    RHO_FOREIGN = 'rho_foreign'
+    RHO_CONV = 'rho_conv_yield'
 
 
 class VanillaOptionType(Enum):

build/lib/quantsbin/derivativepricing/optionstrategies.py

@@ -20,6 +20,7 @@
     UdlType.COMMODITY.value: inst.ComOption
 }
 
+
 def p_map(func, parameter):
     if platform.system() == "Windows":
         return map(func, parameter)

build/lib/quantsbin/derivativepricing/pricingmodels.py

@@ -31,11 +31,11 @@ def risk_parameters(self):
         pass
 
     @property
-    def cnv_yield(self):
+    def _cnv_yield(self):
         if self.instrument.undl == UdlType.FUTURES.value:
             return self.rf_rate
         else:
-            return self._cnv_yield
+            return self.cnv_yield
 
     @property
     def pricing_date(self):
@@ -76,7 +76,7 @@ def __init__(self, instrument, spot0=None, rf_rate=0, cnv_yield=0, cost_yield=0,
         self.instrument = instrument
         self.spot0 = spot0 or .00001
         self.rf_rate = rf_rate or 0
-        self._cnv_yield = cnv_yield or 0
+        self.cnv_yield = cnv_yield or 0
         self.cost_yield = cost_yield or 0
         self.pv_cnv = pv_cnv or 0
         self.pv_cost = pv_cost or 0
@@ -90,7 +90,7 @@ def adj_spot0(self):
     @property
     def d1(self):
         return (log(self.adj_spot0 / self.instrument.strike) + (
-            self.rf_rate - self.cnv_yield + self.cost_yield + 0.5 * (self.volatility ** 2)) * self.maturity) \
+            self.rf_rate - self._cnv_yield + self.cost_yield + 0.5 * (self.volatility ** 2)) * self.maturity) \
                / (self.volatility * sqrt(self.maturity))
 
     @property
@@ -103,7 +103,7 @@ def discount_factor(self):
 
     @property
     def adj_discount_factor(self):
-        return e ** (-1 * (self.cnv_yield - self.cost_yield) * self.maturity)
+        return e ** (-1 * (self._cnv_yield - self.cost_yield) * self.maturity)
 
     @property
     def option_flag(self):
@@ -143,7 +143,7 @@ def rho_fut(self):
     def theta(self):
         return ((-1 * norm.pdf(self.d1) * self.volatility * self.adj_discount_factor * self.adj_spot0 / (
             2 * sqrt(self.maturity))) +
-                (self.option_flag * (self.cnv_yield - self.cost_yield) * self.adj_spot0
+                (self.option_flag * (self._cnv_yield - self.cost_yield) * self.adj_spot0
                  * norm.cdf(self.option_flag * self.d1) * self.adj_discount_factor) -
                 (self.option_flag * self.rf_rate * self.instrument.strike * self.discount_factor
                  * norm.cdf(self.option_flag * self.d2))) / 365
@@ -167,7 +167,7 @@ def objective_func(vol_guess):
             return val - premium
 
         try:
-            return optimize.bisect(objective_func, 0.5, xtol=0.00005)
+            return optimize.bisect(objective_func, a=0.001, b=0.999, xtol=0.00005)
         except ValueError:
             raise ValueError("Unable to converge to implied volatility")
 
@@ -284,7 +284,7 @@ def __init__(self, instrument, spot0=None, rf_rate=0, cnv_yield=0, cost_yield=0,
         self.instrument = instrument
         self.spot0 = spot0 or .0001
         self.rf_rate = rf_rate or 0
-        self._cnv_yield = cnv_yield or 0
+        self.cnv_yield = cnv_yield or 0
         self.cost_yield = cost_yield or 0
         self.volatility = volatility or 0.10
         self._pricing_date = dt.strptime(pricing_date, '%Y%m%d')
@@ -301,7 +301,7 @@ def div_processed(self):
 
     @property
     def drift(self):
-        return self.rf_rate + self.cost_yield - self.cnv_yield
+        return self.rf_rate + self.cost_yield - self._cnv_yield
 
     @property
     def no_of_path(self):
@@ -399,7 +399,7 @@ def __init__(self, instrument, spot0=None, rf_rate=0, cnv_yield=0, cost_yield=0,
         self.instrument = instrument
         self.spot0 = spot0 or 0.0001
         self.rf_rate = rf_rate or 0
-        self._cnv_yield = cnv_yield or 0
+        self.cnv_yield = cnv_yield or 0
         self.cost_yield = cost_yield or 0
         self.volatility = volatility or 0.10
         self._pricing_date = dt.strptime(pricing_date, '%Y%m%d')
@@ -409,7 +409,7 @@ def __init__(self, instrument, spot0=None, rf_rate=0, cnv_yield=0, cost_yield=0,
 
     @property
     def drift(self):
-        return self.rf_rate + self.cost_yield - self.cnv_yield
+        return self.rf_rate + self.cost_yield - self._cnv_yield
 
     @property
     def div_processed(self):

quantsbin/derivativepricing/optionstrategies.py

@@ -20,6 +20,7 @@
     UdlType.COMMODITY.value: inst.ComOption
 }
 
+
 def p_map(func, parameter):
     if platform.system() == "Windows":
         return map(func, parameter)

setup.py

@@ -20,7 +20,7 @@
 
 setup(
     name='Quantsbin',
-    version='1.0',
+    version='1.0.a',
     description='Quantitative Finance Tools',
     long_description=long_description,
     long_description_content_type='text/markdown',