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Thursday, June 24, 2021

Euro 50 - UK 100 - Consequences of a Hawkish Tilt

تم إعداد هذا المنشور من قبل سنشري للاستشارات

Euro 50 - UK 100 - Consequences of a Hawkish Tilt
Euro 50 - UK 100 Consequences of a Hawkish Tilt

*Trading in financial markets carries risk and can result in loss of capital
*This performance is only observed with historical backtests and not traded by the company

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The product and investment ideas do not consider the risk profile and financial position of the recipient and may not be suitable for everyone. Trading in financial markets and use of margin involves a significant risk of loss, which can exceed deposits. Please read the complete disclaimer carefully.

The yield curve started to flatten in the second quarter of 2014 which resulted in the outperformance of Tech sector, along defensive stocks such as Utilities and Healthcare. Sectors such as financials, energy and industrials performed poorly. Along with US treasury spreads narrowing, the Germany Bund spreads (benchmark for European Yields) also narrowed along the same period.

Germany Bund 30 Yr &5 Yr Spread Germany Bund 30 Yr &5 Yr Spread

A Multi-Month Trend

The latest economic forecasts released by the Fed in the FOMC meeting for the month of June 2021, 11 of 18 policymakers expected at least two interest rate hikes by the end of 2023. The prospect of those earlier-than-expected moves have soared short-term yields higher while keeping longer-duration yields subdued as market fears of out-of-control inflation subside.

Presently, the economy is expected to witness a similar wave like it did in 2014 and thus the tech dominated indices in the EU zone should fundamentally outperform the indices that are dominated by the financial sector. This could be a gradual and a multi-month trend.

2014 onwards, as the yield curve started to tumble, the Euro 50 Index rallied and outperformed UK 100. The ratio between the two indices increased from 0.4535 to 0.5471, by approximately 21%.

Euro 50/UK 100 ratio from 2014 to 2015 Euro 50/UK 100 ratio from 2014 to 2015

The Pair Trading Strategy involves going long on Euro 50 increasing in value and simultaneously holding a short position on UK 100.

Along with the generic outlook of the Technology and IT sector rallying, the core reason for Euro 50 to surge is mainly because the major constituents of the Euro50 index are from the Consumer Discretionary sector followed by Technology and the index also comprises of blue-chip European companies from dierent sectors. The consumer discretionary sector that has a weightage of 28% in Euro 50 is anticipated to perform well with reopening of the European economy.

The UK 100 index comprises mainly of the Material and Financial sector accounting for 35 percent of the index. The banking sector will logically witness reduced net interest margins due to narrowing yield spreads in a flattening yield curve scenario. Additionally, the Energy, Material and Industrial sector may foresee lower profit margins since a cap on inflation implies a cap on sales price.

Euro 50 Sector Constituents

Sector € Market Cap (In Bln) Market Cap %
Consumer Discretionary 1100.00 28%
Information Technology 517.04 13%
Industrials 500.05 13%
Consumer Staples 458.61 12%
Financials 416.98 11%
Materials 292.27 7%
Health Care 200.03 5%
Utilities 180.38 5%
Energy 143.71 4%
Communication Services 118.65 3%
Real Estate 31.33 1%
Total 3959.05 100%

Date: 23rd June 2021
Source: Bloomberg

UK 100 Sector Constituents

Sector € Market Cap (In Bln) Market Cap %
Materials 398.55 18%
Financials 375.00 17%
Consumer Staples 371.40 16%
Energy 288.24 13%
Industrials 211.54 9%
Health Care 198.98 9%
Consumer Discretionary 177.47 8%
Communication Services 99.47 4%
Utilities 62.23 3%
Information Technology 33.78 1%
Others 23.30 1%
Real Estate 23.27 1%
Total 2263.23 100%

Date: 23rd June 2021
Source: Bloomberg

Given the flattening of the yield curve and current sector weightings, Euro 50 index is likely to outperform UK 100.

However, it is important to note that Trading pairs is not a risk-free strategy. The jeopardy comes when prices of the two securities move contrary to the positions taken resulting in losses. Thus, it is important to adhere to strict risk management rules when dealing with such adverse situations.

Disclaimer: Individual stocks in the index are subject to both weightage recalculation & recomposition risk. As a result, certain stocks may be added or removed from the index upon index recalculation. Consequently, the performance of the relative index may deviate from the one specified above.

Note: Trading Timings (subject to change) –
Euro 50: 00:00-00:15/00:30-01:00/02:00-04:00/04:15-00:00
UK 100: 00:00-00:15/00:30-01:00/02:00-00:00
(GMT+4)

Risks and Assumptions for Back-tested trading strategies
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The risks and assumptions listed here are not intended to be an exhaustive summary of all the risks and assumptions involved.
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The strategy might suffer from look-ahead bias which occurs due to the use of information or data in a study or simulation that would not have been known or available during the period being analyzed. This can lead to inaccurate results in the study or simulation.
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Future price movements may not be exactly the same as the historical price movements and this could lead to variation in performance.
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Testing can sometimes lead to over-optimization. This is a condition where performance results are tuned so high to the past they are no longer as accurate in the future.
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The model assumes no slippages in trading. Slippage refers to the difference between the expected price of a trade and the price at which the trade is actually executed.
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Drawdowns in actual trading can be higher than the tested system and losses could be significant in the event of leverage.
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Unforeseen events can lead to variation in performance from the tested trading strategy.
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The tested result has been computed with price feeds available from Bloomberg.
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The testing environment has not considered transaction or any other costs.
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Trading indicators used for the purpose of testing has been provided by Bloomberg.
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The strategy might suffer from data mining fallacy, selection bias and backfill bias.

Data Source: Bloomberg
Date: 24/6/2021

Arun Leslie John
Chief Market Analyst

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