diff --git a/catalyst/exchange/data_api.py b/catalyst/exchange/data_api.py
new file mode 100644
index 00000000..717dbe82
--- /dev/null
+++ b/catalyst/exchange/data_api.py
@@ -0,0 +1,73 @@
+import datetime
+
+
+def get_date_from_ms(ms):
+    return datetime.datetime.fromtimestamp(ms / 1000.0)
+
+
+def get_history_mock(exchange_name, data_frequency, symbol, start_ms, end_ms,
+                     exchanges):
+    """
+    Mocking the history API written by Victor by proxying the request
+    to Bitfinex.
+
+    :param exchange_name: string
+        The name identifier of the exchange (e.g. bitfinex).
+        Only bitfinex is supported in this mock function.
+    :param data_frequency: string
+        The bar frequency (minute or daily)
+    :param symbol: string
+        The trading pair symbol.
+    :param start_ms: float
+        The start date in milliseconds.
+    :param end_ms: float
+        The end date in milliseconds.
+    :param exchanges: MOCK ONLY
+        This won't be required in production mode since the exchange object
+        will be retrieved on the server.
+    :return ohlcv: list[dict[string, float]]
+        The open, high, low, volume collection for the resulting bars.
+
+    Notes
+    =====
+    Using milliseconds for the start and end dates for ease of use in the
+    URL query parameters.
+
+    Sometimes, one minute goes by without completing a trade of the given
+    trading pair on the given exchange. To minimize the payload size, we
+    don't return identical sequential bars. Post-processing code will
+    forward fill missing bars outside of this function.
+    """
+
+    if exchange_name != 'bitfinex':
+        raise ValueError('get_history mock function only works with bitfinex')
+
+    exchange = exchanges[exchange_name]
+    assets = [exchange.get_asset(symbol=symbol)]
+    start = get_date_from_ms(start_ms)
+    end = get_date_from_ms(end_ms)
+
+    delta = end - start
+
+    periods = delta.seconds % 3600 / 60.0 \
+        if data_frequency == 'minute' else delta.days
+
+    candles = exchange.get_candles(
+        data_frequency=data_frequency,
+        assets=assets,
+        bar_count=periods,
+        start_dt=start,
+        end_dt=end
+    )
+
+    ohlcv = []
+    for candle in candles:
+        ohlcv.append(dict(
+            open=candle['open'],
+            high=candle['high'],
+            low=candle['low'],
+            close=candle['close'],
+            volume=candle['volume'],
+            last_traded=candle['last_traded']
+        ))
+    return ohlcv