diff --git a/docs/developer.md b/docs/developer.md
index e7f79bc1c..ccd5cdd8f 100644
--- a/docs/developer.md
+++ b/docs/developer.md
@@ -81,6 +81,50 @@ Please also run `self._validate_whitelist(pairs)` and to check and remove pairs
 This is a simple method used by `VolumePairList` - however serves as a good example.
 It implements caching (`@cached(TTLCache(maxsize=1, ttl=1800))`) as well as a configuration option to allow different (but similar) strategies to work with the same PairListProvider.
 
+## Implement a new Exchange (WIP)
+
+!!! Note
+    This section is a Work in Progress and is not a complete guide on how to test a new exchange with FreqTrade.
+
+Most exchanges supported by CCXT should work out of the box.
+
+### Stoploss On Exchange
+
+Check if the new exchange supports Stoploss on Exchange orders through their API.
+
+Since CCXT does not provide unification for Stoploss On Exchange yet, we'll need to implement the exchange-specific parameters ourselfs. Best look at `binance.py` for an example implementation of this. You'll need to dig through the documentation of the Exchange's API on how exactly this can be done. [CCXT Issues](https://github.com/ccxt/ccxt/issues) may also provide great help, since others may have implemented something similar for their projects.
+
+### Incomplete candles
+
+While fetching OHLCV data, we're may end up getting incomplete candles (Depending on the exchange).
+To demonstrate this, we'll use daily candles (`"1d"`) to keep things simple.
+We query the api (`ct.fetch_ohlcv()`) for the timeframe and look at the date of the last entry. If this entry changes or shows the date of a "incomplete" candle, then we should drop this since having incomplete candles is problematic because indicators assume that only complete candles are passed to them, and will generate a lot of false buy signals. By default, we're therefore removing the last candle assuming it's incomplete.
+
+To check how the new exchange behaves, you can use the following snippet:
+
+``` python
+import ccxt
+from datetime import datetime
+from freqtrade.data.converter import parse_ticker_dataframe
+ct = ccxt.binance()
+timeframe = "1d"
+raw = ct.fetch_ohlcv(pair, timeframe=timeframe)
+
+# convert to dataframe
+df1 = parse_ticker_dataframe(raw, timeframe, drop_incomplete=False)
+
+print(df1["date"].tail(1))
+print(datetime.utcnow())
+```
+
+``` output
+19   2019-06-08 00:00:00+00:00
+2019-06-09 12:30:27.873327
+```
+
+The output will show the last entry from the Exchange as well as the current UTC date.
+If the day shows the same day, then the last candle can be assumed as incomplete and should be dropped (leave the setting `"ohlcv_partial_candle"` from the exchange-class untouched / True). Otherwise, set `"ohlcv_partial_candle"` to `False` to not drop Candles (shown in the example above).
+
 ## Creating a release
 
 This part of the documentation is aimed at maintainers, and shows how to create a release.