About Cash Indices
The Cash Indices dataset by QuantConnect covers 125 US Indices and 3 International indices. The data starts on various dates from January 1998 and is delivered on any frequency from minute to daily.
About QuantConnect
QuantConnect was founded in 2012 to serve quants everywhere with the best possible algorithmic trading technology. Seeking to disrupt a notoriously closed-source industry, QuantConnect takes a radically open-source approach to algorithmic trading. Through the QuantConnect web platform, more than 50,000 quants are served every month.
About QuantConnect
QuantConnect was founded in 2012 to serve quants everywhere with the best possible algorithmic trading technology. Seeking to disrupt a notoriously closed-source industry, QuantConnect takes a radically open-source approach to algorithmic trading. Through the QuantConnect web platform, more than 50,000 quants are served every month.
Algorithm Example
from AlgorithmImports import *
from QuantConnect.DataSource import *
class IndexDataAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self.set_start_date(2020, 1, 1)
self.set_end_date(2021, 7, 8)
self.set_cash(100000)
# Request SPY data as a trading vehicle for SPX
self.spy = self.add_equity("SPY").symbol
# Request SPX data for trade signal generation
spx = self.add_index("SPX").symbol
# Create short and long-term EMA indicators for trend estimation to trade
self.ema_fast = self.EMA(spx, 80, Resolution.DAILY)
self.ema_slow = self.EMA(spx, 200, Resolution.DAILY)
self.set_warm_up(200, Resolution.DAILY)
# Historical data
history = self.history(spx, 60, Resolution.DAILY)
self.debug(f'We got {len(history.index)} items from our history request')
def on_data(self, slice: Slice) -> None:
# Trade signals required indicators to be ready
if self.is_warming_up or not self.ema_slow.is_ready:
return
# If short-term EMA is above long-term, it indicates an up trend, so we buy SPY
if not self.portfolio.invested and self.ema_fast > self.ema_slow:
self.set_holdings(self.spy, 1)
# If it is the reverse, it indicates a downtrend, and we liquidate any position
elif self.ema_fast < self.ema_slow:
self.liquidate()
Example Applications
The Cash Indices enables you to incorporate popular indices into your trading algorithms. Examples include the following use cases:
- Exploring the difference between the Index and the ETF that tracks it
- Using these indices as the underlying asset fo Index Options strategies
- Understanding the stock market's level of expected forward-looking volatility, also known as the "fear index". When the VIX starts moving higher, it is telling you that traders are getting nervous. When the VIX starts moving lower, it is telling you that traders are gaining confidence.
Pricing
Cloud Access
Freely harness gigabytes of Cash Indices data in the QuantConnect Cloud for your backtesting and live trading purposes.
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