Using Tiingo Daily Prices with an EMA Crossover in QuantConnect
Summary
This QuantConnect example adds Tiingo daily price data for Apple alongside the platform’s equity subscription, then reads the custom data in the algorithm’s data callback. It creates fast and slow exponential moving averages with periods of five and ten. Once both indicators are ready, the algorithm logs Tiingo fields and indicator values. It buys Apple when the fast average is above the slow average and the portfolio is not invested, then liquidates when the fast average falls below the slow average.
The example illustrates data integration and a simple crossover rule rather than a researched strategy. It sets a 2017 date range and initial cash, but reports no backtest results, benchmark, transaction costs, or risk analysis. The decision logic checks investment status for the long entry, and the example does not evaluate short positions or portfolio sizing beyond targeting full holdings. Readers should treat it as an API usage pattern, not evidence that the crossover is profitable.
Key ideas
- The algorithm imports Tiingo daily prices for Apple within a QuantConnect workflow.
- It calculates five-period and ten-period exponential moving averages.
- It enters a full holding when the fast average is above the slow average and exits on the reverse condition.
- The data callback checks that the equity data exists before processing the slice.
- The example specifies a 2017 period but provides no performance or risk evidence.
Tags
Full text
# TiingoPriceAlgorithm
# TiingoPriceAlgorithm
This example algorithm shows how to import and use Tiingo daily prices data.
## Source (Apache-2.0)
```python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from AlgorithmImports import *
from QuantConnect.Data.Custom.Tiingo import TiingoPrice
### <summary>
### This example algorithm shows how to import and use Tiingo daily prices data.
### </summary>
### <meta name="tag" content="strategy example" />
### <meta name="tag" content="using data" />
### <meta name="tag" content="custom data" />
### <meta name="tag" content="tiingo" />
class TiingoPriceAlgorithm(QCAlgorithm):
def initialize(self):
# Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
self.set_start_date(2017, 1, 1)
self.set_end_date(2017, 12, 31)
self.set_cash(100000)
# Set your Tiingo API Token here
Tiingo.set_auth_code("my-tiingo-api-token")
self._equity = self.add_equity("AAPL").symbol
self._aapl = self.add_data(TiingoPrice, self._equity, Resolution.DAILY).symbol
self._ema_fast = self.ema(self._equity, 5)
self._ema_slow = self.ema(self._equity, 10)
def on_data(self, slice):
# OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
if not slice.contains_key(self._equity): return
# Extract Tiingo data from the slice
row = slice[self._equity]
if not row:
return
if self._ema_fast.is_ready and self._ema_slow.is_ready:
self.log(f"{self.time} - {row.symbol.value} - {row.close} {row.value} {row.price} - EmaFast:{self._ema_fast} - EmaSlow:{self._ema_slow}")
# Simple EMA cross
if not self.portfolio.invested and self._ema_fast > self._ema_slow:
self.set_holdings(self._equity, 1)
elif self.portfolio.invested and self._ema_fast < self._ema_slow:
self.liquidate(self._equity)
```Shown in full with attribution under the source's licence. Licence: Apache-2.0
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.