Original paper
Abstract
Stock market average returns and Sharpe ratios are significantly higher on days when important macroeconomic news about inflation, unemployment, or interest rates is scheduled for announcement. The average announcement day excess return from 1958 to 2009 is 11.4 basis points versus 1.1 basis points for all the other days, suggesting that over 60% of the cumulative annual equity risk premium is earned on announcement days. The Sharpe ratio is ten times higher. In contrast, the risk-free rate is detectably lower on announcement days, consistent with a precautionary saving motive. Our results demonstrate a trade-off between macroeconomic risk and asset returns, and provide an estimate of the premium investors demand to bear this risk.
Keywords:Â Asset Pricing, Macroeconomic Risk, Macroeconomic News
Trading rules
- Use CFDs, ETFs, or futures for opening a long position in the stock market on economic announcement days.
- Focus on days presenting CPI, PPI, job statistics, or FOMC verdicts.
- Stay in cash when not investing during these announcement days.
Python code
Backtrader
import backtrader as bt
import datetime
class EconomicAnnouncementStrategy(bt.Strategy):
def __init__(self):
self.in_announcement = False
def next(self):
announcement_days = self.get_announcement_days()
if self.datetime.date(0) in announcement_days:
self.in_announcement = True
self.order_target_percent(target=1.0) # Long exposure to equity market
elif self.in_announcement:
self.in_announcement = False
self.order_target_percent(target=0.0) # Move to cash
def get_announcement_days(self):
# Replace this function with actual dates of CPI, PPI, employment data, and FOMC decisions
return [
datetime.date(2023, 4, 20),
datetime.date(2023, 5, 15),
datetime.date(2023, 6, 19),
# ...
]
if __name__ == '__main__':
cerebro = bt.Cerebro()
data = bt.feeds.YahooFinanceData(
dataname='SPY', fromdate=datetime.datetime(2023, 1, 1),
todate=datetime.datetime(2023, 12, 31))
cerebro.adddata(data)
cerebro.addstrategy(EconomicAnnouncementStrategy)
cerebro.run()