diff --git a/catalyst/examples/buy_and_hold_live.py b/catalyst/examples/buy_and_hold_live.py
index 25c57533..985c06fa 100644
--- a/catalyst/examples/buy_and_hold_live.py
+++ b/catalyst/examples/buy_and_hold_live.py
@@ -18,7 +18,7 @@ log = Logger('buy_and_hold_live')
 
 def initialize(context):
     log.info('initializing algo')
-    context.asset = symbol('eos_usd')
+    context.asset = symbol('eos_btc')
 
     context.TARGET_HODL_RATIO = 0.8
     context.RESERVE_RATIO = 1.0 - context.TARGET_HODL_RATIO
@@ -53,7 +53,7 @@ def handle_data(context, data):
     # Check if still buying and could (approximately) afford another purchase
     if context.is_buying and cash > price:
         # Place order to make position in asset equal to target_hodl_value
-        order(context.asset, 1, limit_price=price + 1.1)
+        order(context.asset, 1, limit_price=price * 1.1)
         # This works
         # order_target_value(
         #     context.asset,
@@ -79,7 +79,7 @@ exchange_conn = dict(
     name='bitfinex',
     key='',
     secret=b'',
-    base_currency='usd'
+    base_currency='btc'
 )
 run_algorithm(
     initialize=initialize,
diff --git a/catalyst/exchange/bitfinex.py b/catalyst/exchange/bitfinex.py
index e317a52d..8dbb1ca8 100644
--- a/catalyst/exchange/bitfinex.py
+++ b/catalyst/exchange/bitfinex.py
@@ -193,7 +193,8 @@ class Bitfinex(Exchange):
         portfolio.cash = float(base_position['available'])
 
         if portfolio.positions:
-            tickers = self.tickers(portfolio.positions.keys())
+            assets = portfolio.positions.keys()
+            tickers = self.tickers(assets)
             portfolio.positions_value = 0.0
             for ticker in tickers:
                 # TODO: convert if the position is not in the base currency
@@ -209,8 +210,9 @@ class Bitfinex(Exchange):
     @property
     def portfolio(self):
         """
-        TODO: I'm not sure how that's used yet
-        :return: 
+        Return the Portfolio
+
+        :return:
         """
         if self.store.portfolio is None:
             portfolio = ExchangePortfolio(
@@ -402,18 +404,16 @@ class Bitfinex(Exchange):
         :func:`catalyst.api.order_value`
         :func:`catalyst.api.order_percent`
         """
-        log.debug(
-            'ordering {amount} {symbol} {style}'.format(
-                amount=amount,
-                symbol=asset.symbol,
-                style=style
-            )
-        )
-
         if amount == 0:
             log.warn('skipping order amount of 0')
             return None
 
+        base_currency = asset.symbol.split('_')[1]
+        if base_currency.lower() != self.base_currency.lower():
+            raise NotImplementedError(
+                'Currency pairs must share their base with the exchange.'
+            )
+
         is_buy = (amount > 0)
 
         if isinstance(style, MarketOrder):
@@ -432,6 +432,14 @@ class Bitfinex(Exchange):
         else:
             raise NotImplementedError('%s orders not available' % style)
 
+        log.debug(
+            'ordering {amount} {symbol} for {price}'.format(
+                amount=amount,
+                symbol=asset.symbol,
+                price=price
+            )
+        )
+
         exchange_symbol = self.get_symbol(asset)
         req = dict(
             symbol=exchange_symbol,
diff --git a/catalyst/exchange/exchange_clock.py b/catalyst/exchange/exchange_clock.py
index f3866ce8..4698297c 100644
--- a/catalyst/exchange/exchange_clock.py
+++ b/catalyst/exchange/exchange_clock.py
@@ -64,8 +64,8 @@ class ExchangeClock(object):
             server_time = current_time.floor('1 min')
 
             if self._last_emit is None or server_time > self._last_emit:
+                log.debug('emitting minutely bar: {}'.format(server_time))
 
-                print 'emitting bar %s' % server_time
                 self._last_emit = server_time
                 yield server_time, BAR
 
diff --git a/docs/source/live-trading-blueprint.md b/docs/source/live-trading-blueprint.md
index 327986e0..d26638f2 100644
--- a/docs/source/live-trading-blueprint.md
+++ b/docs/source/live-trading-blueprint.md
@@ -3,36 +3,33 @@ The purpose of this document is to allow project contributors navigate
 through the ongoing live trading implementation.
 
 <h2>Components</h2>
-At a high level the following components have been implemented to coerce
+At a high level, the following components have been implemented to coerce
 zipline into live trading.
 
 <h3>Exchange</h3>
 
 *catalyst/exchange*
 
-Exchange is a new package which introduces the concept of cryptocurrency
-exchanges to zipline. The package contains all new component
-implementations adapted to characteristics of exchanges.
+Exchange is a new package introducing cryptocurrency
+exchanges to zipline. The package contains mostly new implementations
+of existing components, adapted to characteristics of exchanges.
 
-Here are some key characteristics which makes exchanges different from
-equity and futures currently implemented in zipline.
+Here are some key characteristics which make cryptocurrency exchanges
+exchanges different compared to equity brokers.
 * They trade around the clock.
 * Currency symbols are inconsistent across exchanges.
-* They trade currency pairs, i.e. the base currency is not always be USD.
-This is a significant departure from the equity market. Additional
-business logic will be required both to assess performance and
-manage trades.
-* The cryptocurrency market being relatively immature, there are still
-significant price arbitrage opportunities between exchanges.
-In contrast with the equity markets, trader usually trade directly
-against an exchange (as oppose to using a broker). Consequently,
-to extract maximum alpha, the platform should not only support
-multiple exchanges, but also multiple exchanges per algorithm.
+* They trade currency pairs (i.e. the base currency is not always be USD).
+This is a paradigm shift in context of zipline. Additional
+business logic will be required to manage the portfolio data and orders.
+* The price of a single asset might vary across exchanges. This means
+arbitrage opportunities. Consequently, to extract maximum alpha, the
+platform should not only support multiple exchanges, but also multiple
+exchanges per algorithm.
 * The fee model is usually more complex than that of an equity broker.
 It can vary drastically between exchanges.
-* There are no splits, mergers, etc to worry about.
-* Their order book is publicly available, the platform should access to
-it as it can be used to drastically reduce slippage.
+* There are no splits, mergers, etc. to worry about.
+* A complete order book is usually available, the platform should
+offer access to it order to help traders reduce slippage.
 
 <h3>New Components</h3>
 These components of the exchange package were added to the zipline
@@ -42,7 +39,7 @@ sources.
 
 *catalyst/exchange/exchange.py*
 
-Abstract class which acts an interface for the implementation of
+Abstract class which acts as an interface for the implementation of
 various exchanges. It also contains logic common to all exchanges.
 
 <h4>Bitfinex</h4>
@@ -59,14 +56,20 @@ Extends the zipline DataPortal to route spot data to the exchange.
 This is critical because it allows the algoritm to request data in
 real-time.
 
-For example, `data.current(asset, 'price')` retrieves the current price of the asset, not the price at the time
-of yielding the bar this is critical to minimize slippage.
+For example, `data.current(asset, 'price')` retrieves the current price
+of the asset, not the price at the time of yielding the bar this
+is critical to minimize slippage.
+
+At the time of writing, it only supports spot data but I believe that
+it should be extended to historical data as well. Some exchanges
+have better historical data APIs than others. This will need to
+be considered during each individual implementation.
 
 <h4>ExchangeClock</h4>
 
 *catalyst/exchange/exchange_clock.py*
 
-An implementation to the zipline Clock which runs 24/7. It yeilds a
+An implementation to the zipline Clock which runs 24/7. It yields a
 bar every minute.
 
 <h4>AssetFinderExchange</h4>
@@ -76,15 +79,14 @@ bar every minute.
 An alternate implementation of AssetFinder which locates each asset
 against the exchanges instead of bundle databases.
 
-For example, `symbol('eth_usd')` retrieves an Asset object against the exchange as opposed to querying
-a database of equities.
+For example, `symbol('eth_usd')` should return an Ethereum/USD asset
+regardless of currency notation of the target exchange.
 
-I have created a dictionary of currencies for the Bitfinex exchange.
-The primary goal is to standardize the symbol notation across exchanges.
-Here is a snippet of the file.
+To acheive this, I have created a dictionary of currencies for the
+Bitfinex exchange. Here is what it looks like.
 * Each key represents the exchange specific symbol.
-* The symbol attribute represents the standard symbol which
-should be common across exchanges for the given currency.
+* The symbol attribute represents the abstract symbol common across
+all exchanges for the given currency.
 * The start_date attribute should correspond to its first trading day
 on the exchange.
 
@@ -132,13 +134,15 @@ business logic to enable live trading.
 
 The run_algorithm interface is an entry point to execute an
 algorithm in zipline. This component was already modified for
-the catalyst concurrency bundles. I added conditional logic to
-which should not break any of the existing backtesting implementations.
+the catalyst concurrency bundles. I added conditional logic
+which should not interfere with backtesting.
 
-At a high-level the run_algorithm method now contains two additional
+In a nutshell, the run_algorithm method now contains three additional
 parameters:
 * live: If True, zipline will attempt to trade live. If False or not
 specified, it will run a backtest as normal.
+* algo_namespace: An arbitrary namespace for the current algorithm.
+It will be used to persist data between runs.
 * exchange_conn: A dictionary containing the attributes required
 to instantiate an exchange. Here is an example for Bitfinex:
 
@@ -189,7 +193,7 @@ cost basis would correspond to all positions, not just those
 initiated by the algorithm.
 * It would not be possible impose trading limits on algorithms.
 
-It follow that Portfolio metrics should be calculated using a strategic
+It follows that Portfolio metrics should be calculated using a strategic
 combination of the exchange data and algorithm activity. While tracking
 the activity of an algorithm works well in backtesting, it is more
 challenging during live trading. A live algorithm might run over