E A Reality Check For The Tech Sector’s Risk Profile Amid Volatility

The Tech sector is the most profitable and fastest-growing sector in the S&P 500. Though it is considered by many investors to be of cyclical nature, and hence perceived to be a sector that one should avoid exposure to amid expectations of weakening economic conditions and rising volatility ahead. Nevertheless, the thrill of financial market data analysis lies in entering into uncharted territory, digging into numbers that others are shunning. The return of volatility in 2018 led to negative performances for various sectors, culminating into negative results for risk-adjusted performance measures, which are considered useless among research analysts. However, while individually these negative results may be meaningless, putting the negative results of various sectors together actually helps uncover insightful revelations about how the Tech sector is not as risky as perceived in comparison to other sectors, and that long-term investors should continue holding exposure to the sector even amid expectations of increased volatility.

We will compare the risk-adjusted performance of the Tech sector (during 2018) to defensive sectors, for which sector ETFs (issued by State Street Global Advisors) will be used as proxies for sector performance.

Two common measures of risk-adjusted performance are the Sharpe and Sortino ratios. While the Sharpe ratio is useful for determining how effectively the security delivers returns per unit of volatility, its biggest flaw is that because it uses the standard deviation as a measure of volatility risk, it considers upside deviation as risky as downside deviation, which is certainly not the case given that upside movements are favorable for the investor. Hence for more effective risk-adjusted analysis, we will use the Sortino ratio to determine how the ETFs performed during the volatile 2018. The Sortino ratio only considers downside deviation as volatility risk to the investors, by only taking the standard deviation of negative returns. However, let us take this a step further and modify the Sortino ratio so that it better allows us to analyze the performance of the securities amid risks of negative performance. In the traditional Sortino ratio, the standard deviation in the denominator calculates the deviation of negative returns from the mean (of negative returns), and thus reflects how much all the negative returns deviate away from the average negative return. However, it would be more worthwhile to use ‘0’ instead of the ‘mean negative return’ when determining the security’s downside deviation. Thereby, we will not calculate the standard deviation based on the deviation of data points away from the average negative return, but instead from ‘0’. This results in a better examination of the risk-adjusted performances of the securities, as it adjusts for the extent to which the security performances can deviate into negative territory, away from ‘0’.

The Sortino ratios have been calculated by taking the average monthly return for each ETF, subtracting the risk-free rate from each of those returns (to derive at excess monthly returns), and then using those excess returns to calculate the average monthly excess return. This result was then divided by our modified standard deviation of the negative monthly returns. Note that the risk-free rate used is the average 1-month Treasury yield during 2018 (to match with the monthly returns scale). The annualized results can be found in the table below.

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