About US Cash Indices
The US Cash Indices dataset by TickData covers 3 US Indices: SPX, VIX, and NDX. The data starts on various dates from Janunary 1998 and is delivered on any frequency from tick to daily. This dataset is created by TickData negotiating directly with exchanges for their official archive and by partnering with real-time data providers who have direct exchange connections and multiple redundant ticker plants.
Additionally, this dataset includes EUREX EU STOXX Index (SX5E).
About TickData
TickData was founded by a futures broker and a programmer in 1984 as the first company in the world to offer historical tick-by-tick prices on the futures and index markets. TickData provides access to comprehensive and detailed market data and analytics products in the financial industry covering Equities, Futures, Options, cash FOREX, and Cash Indices.
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 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 indicator 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 down trend and we liquidate any position
elif self.ema_fast < self.ema_slow:
self.liquidate()
Example Applications
The US Cash Indices enables you to incorporate popular US 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 for US 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.
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