Live trading and backtesting platform written in Python.

The library is event-based, which means it is more complex and slower than the vectorised/for-loop approach usually employed in researching strategies, but display more stable and realistic live behaviour (same code is indeed used for both back-testing and live trading) and less prone by construction to looking-ahead bias.

The event-loop is as follows:

• the data handler (feeds) reads the data (from csv files or databases) and generates a market event (either a new daily bar - BarEvent - or a tick - TickEvent - for more granular back-testing or live trading).
• The market event is then used to produce a signal (SignalEvent), e.g. a moving average cross.
• In turn the signal is used to generate an order - OrderEvent - after relevant sizing (e.g. volatility-based) and risk management (e.g. capping number of lots).
• Finally the order gets executed by a Broker (either simulated or a live one) and the filled order recorded.

Repeat.

• Data handler(s) in feeds: gets data from csv files (or quandl or databases), create a market event and pass it to the queue.
• Strategies: transforms a market event into a suggested action (i.e. signal), create signal event to be passed to the queue.
• Positions (Stocks, ...): represents an instrument (tickers, ...), and its book-keeping: its quantity, price and market values (pnl, ...).
• Portfolio: handles any new position or modification to a current position (forwarding market value updates to the position class), and updates overall market/accounting values (closed and still open positions).
• Portfolio handler helps managing the queue during back-testing (and live trading) by calling relevant objects (position sizer and refiners, and portfolio for positions/value updates).
• Broker(s): executes orders by creating a filled order event and passing to the queue.
• Statistics: updates equity curve and relative timestamp to calculate statistics (equity_returns, hwm, drawdowns, Sharpe ratio, ...) and to plot.

• finish volatility position sizing;

• create the pension strategy sample;

• integrate TA-Lib? (see backtrader);

• introduce currency conversion in either position or portfolio;

• create futures position (currently supporting only stocks);

• test Carver's systems (moma + carry);

• create FX position;

• getting more tests done on samples.

  Nice to have: i. getting Sphynx for docs, ii. CI Travis, iii. finish Mongo, iv. integrate arctic database?