Fundamental analysis Macroeconomic indicators

The Impact of the Economic Uncertainty Index on the Financial Markets

Anton Volkov 06 july 2022 55 4

In financial markets, bidders actively use a wide variety of indicators to make decisions. The studies have already looked at indicators reflecting financial stress and inflation forecast. Today we will consider another indicator of the market - the index of economic uncertainty.

 

The economic uncertainty index includes 3 main components:


  • Number of news articles in the top 10 US newspapers discussing economic policy uncertainty;


  • Number of tax code provisions that expire in the next 10 years;


  • Variance between forecasts by Philadelphia Federal Reserve Bank professional forecasters for future levels of the consumer price index, federal spending, and state and local spending.
Hypothesis
To conclusion

The growth of the economic uncertainty index weakens gold and the S&P 500 stock index, but strengthens the US dollar. The economic uncertainty index decline strengthens gold and the S&P 500 stock index, but weakens the US dollar.

К выводам
Data used

Daily values of the economic uncertainty index:


https://fred.stlouisfed.org/series/WLEMUINDXD


Historical data on quotes of world currencies, the S&P 500 index and gold:

  • AUDUSD
  • EURUSD
  • GBPUSD
  • NZDUSD
  • USDCAD
  • USDCHF
  • USDJPY
  • USDRUB
  • Gold
  • S&P 500 index

Timeframe – D (daily)

Period - from 1985 to 2021

There are 9,626 values in total.


Strategy



The correlation coefficient is used to determine the presence of a connection, as well as the degree of strength of the connection between the economic uncertainty index and financial instruments. The correlation is calculated day by day and with shifts of 1,2,3,4,5 days forward and backward. To determine the strength of the connection, the correlation coefficient is compared with the reference values of the Chaddock scale:


Chaddock scale

Connection degree
Correlation:
Direct connection
Reverse connection
No connection
0 - 0,1
(-0,1) - 0
Weak connection
0,1 – 0,3
(-0,3) – (-0,1)
Moderate connection
0,3 – 0,5
(-0,5) – (-0,3)
Salient connection
0,5 – 0,7
(-0,7) – (-0,5)
Strong connection
0,7 – 0,9
(-0,9) – (-0,7)
Very strong connection
0,9 - 1
(-1) – (-0,9)

The correlation coefficients between changes in the economic uncertainty index and the considered financial instruments do not reach a minimum significant level of 0.1 modulo. Therefore, there is no connection between the index and financial instruments.

With shifts, the correlation coefficients also do not reach the minimum significant level of 0.1 modulo. It can be concluded that the economic uncertainty index and financial instruments do not follow each other.



Further, let's determine the rate of return of the trade opening strategy using the economic uncertainty index:


  • With the economic uncertainty index growth: we sell gold, the S&P 500 index and pairs with the quoted currency USD, we buy pairs with the base currency USD.



  • When the economic uncertainty index decreases: we buy gold, the S&P 500 index and pairs with the quoted currency USD, we sell pairs with the base currency USD.


Entry into the market - at the opening of the next day after the publication of the economic uncertainty index.

 

Exit from the market:

  • At the close of the 1st day (day of entry into the market)
  • At the close of the 2nd day
  • At the close of the 3rd day
  • At the close of the 4th day
  • At the close of the 5th day
  • At the close of the day when the opposite signal appears


To improve the effectiveness of the strategy, we will use the quality criterion: the value of the economic uncertainty index is above/below a certain threshold level:

  • < 100 (low uncertainty)
  • 100-200 (medium uncertainty)
  • 200-300 (high uncertainty)
  • 300-400 (very high uncertainty)
  • > 400 (extreme, panic in the media)


Theoretically, the higher the index threshold level used as a signal to open/close a position, the higher the strategy rate of return should be. The reverse side of signal quality is frequency of its occurrence:

  • Index values above 100 occur in 25.45% of cases (1 time in 4 days)
  • Index values above 200 occur in 10.29% of cases (1 time in 10 days)
  • Index values above 300 occur in 5.09% of cases (1 time in 20 days)
  • Index values above 400 occur in 2.8% of cases (1 time in 36 days)



The strategy will be evaluated according to the following criteria:


  • The average rate of return reflects the relative change in the quotes of financial instruments in percentage. A positive value of the rate of return indicates the profitability of the strategy, a negative one indicates a loss. 


The average rate of return (D) of a financial instrument is calculated using the formula:


D = Σ P (%) / n,


where:

n is the number of trades;


 

P (%) – the percentage of change in the quote of a financial instrument at the time of fixing a position, is calculated as follows:

 

for buy positions

P (%) = (position closing price - position opening price) / position opening price * 100%

 

for sell positions

P (%) = (position opening price - position closing price) / position opening price * 100%

 

  • The total rate of return (TD) is the sum of the profits from all trades. The greater the value of the total rate of return, the greater the profit brought by the signal during its testing period. 


  • Maximum drawdown (MaxDD) is the maximum loss in percentage terms from fixing unprofitable trades for the entire testing period. The lower the value of the maximum drawdown, the better the trading signal works.


MaxDD = | min ( DD1: DDn ) |

DDn = TDn – max ( TD1: TDn )


where:

 

n – number of trades;

D – rate of return;

TDn – total rate of return of n trades;

DDn – drawdown at the time of closing the n-th trade;

MaxDD – maximum drawdown.



Analysis of the obtained results



For variable parameters, the following designations are used: 1, 100, where: 

1 (the first number) is the daily candlestick on which the position is closed. Possible values: 1,2,3,4,5.

100 (the second number) is the threshold level of the economic uncertainty index for opening/closing a position. Possible values: 100, 200, 300, 400.

Testing the strategy on currency pairs has shown poor performance: for all considered parameters of exit candlesticks and index values, the average rate of return does not reach a significant level of 0.3%.

The rate of return of the strategy when testing on gold quotes and the S&P 500 index has turned out to be significantly higher than that of currency pairs. For gold, the average rate of return ranges from 0.15% to 0.26%. The average rate of return of the S&P 500 index ranges from 0.01% to 0.18%. Nevertheless, the significance level of 0.3% for the average rate of return parameter has also not been reached.



Further, the strategy with an exit from the position on the opposite signal will be considered.

The strategy has turned out to be ineffective for all considered currency pairs, excluding the USDRUB.

For gold and the S&P 500 index, the strategy has turned out to be effective at the threshold level of the economic uncertainty index of 300 and 400. For the S&P 500 index, the average rate of return has amounted to 0.4 and 0.76%, for gold, 0.36% and 0.67%, respectively.

 

The strategy shows efficiency under the condition of entering “vice versa” for the USDRUB currency pair: the average rate of return is 0.4%, 0.64% and 1.23% at the threshold levels of the economic uncertainty index of 200, 300, 400.

There is a noticeable trend for the S&P 500 index: applying a higher threshold level of the economic uncertainty index for entering/exiting a position allows reducing a maximum drawdown from 144.68% to 101.38%. The USDRUB currency pair has the opposite situation: the threshold increase does not lead to the maximum drawdown decrease. 

 

For gold, the minimum drawdown of 44.46% is observed at the threshold level of 300.

As the threshold level increases, the number of trades naturally decreases:

 

  • With a threshold level of 100, trades are made on average once every 5 days.
  • With a threshold level of 200, trades are made on average once every 10 days.
  • With a threshold level of 300, trades are made on average once every 17 days.
  • With a threshold level of 400, trades are made on average once every 30 days.
Conclusion

No relationship has been found between changes in the economic uncertainty index and the considered financial instruments. In addition, the index of economic uncertainty and the considered financial instruments do not follow each other.


The effectiveness of the strategy with exiting the position 1,2,3,4,5 days after entering the market has not been revealed.


The effectiveness of the strategy for the S&P 500 index and gold has been revealed at the threshold levels of the economic uncertainty index of 300 and 400, as well as exiting the market on the opposite signal.


The effectiveness of applying the strategy for the USDRUB currency pair under the condition of entering “vice versa” and exiting the market on the opposite signal has also been revealed.

Detailed results are shown in the Appendix:

XLSX (0.16 MB)The impact of the economic uncertainty index on the financial markets.xlsx


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