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Wednesday, July 08, 2020

Fang + SaaS Vs China Tech

By Century Financial in 'Investment Insights'

Fang + SaaS Vs China Tech
Fang + SaaS versus China Tech

The COVID market crisis has been the most rapid “market crash to recovery” in history for the US stock markets. The quick unprecedented action by the US Federal Reserve backstopped the equity markets.

Stocks surged from their March 23rd lows faster than anyone could have foreseen. Many people missed out on the rapid +40% S&P 500 V-shaped recovery over the past 3 months. Investors were not been able to participate in the recovery as they feared witnessing a repeat of what happened in the months of Feb-March. They are seeing the recovery but don’t trust it.

Investors who have sat on the sidelines are growing anxious that stocks will just keep rising and fear missing out on the recovery. With a resurgence in coronavirus cases on one hand and improving macro-economic data on the other, it is tough to determine if the recent recovery will be short-lived or an indication of a rally later in the year. In the current perplexing environment, pair trading strategy can allow investors to participate in the market and overcome the FOMO effect.

However, it is important to note that Trading pairs is not a risk-free strategy. The difficulty 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.

| Strategy

The returns in the table below have been derived by undertaking long positions on software as a service (SaaS) Index while simultaneously shorting China Tech index of equal exposures. For instance: if $500K worth China Tech was sold, then simultaneously $250K worth SaaS and $250K Fang Plus was bought. The strategy has offered 54% return over the last 5 years providing an average return of ~11% per year with 2x leverage.

| Back-tested data based on the current index constituent weights

Quarter ending
SaaS Return
Fang Plus return
Average Return (Fang + SaaS)
China Tech Return
Long: Fang + SaaS Short: China Tech
9/30/2015
0% -3% -2% -25% 24%
12/31/2015
10% 17% 13% 39% -25%
3/31/2016
-5% -4% -4% -7% 2%
6/30/2016
5% 1% 3% 1% 2%
9/30/2016
10% 19% 15% 23% -9%
12/30/2016
-5% 0% -2% -13% 10%
3/31/2017
15% 14% 14% 23% -8%
6/30/2017
10% 15% 12% 20% -7%
9/29/2017
9% 12% 10% 27% -17%
12/29/2017
7% 8% 7% 2% 6%
3/29/2018
14% 10% 12% 6% 6%
6/29/2018
13% 18% 15% 8% 8%
9/28/2018
16% -3% 7% -14% 21%
12/31/2018
-16% -20% -18% -19% 1%
3/29/2019
33% 18% 26% 27% -2%
6/28/2019
10% -3% 3% -12% 16%
9/30/2019
-3% 0% -2% -8% 7%
12/31/2019
10% 22% 16% 22% -6%
3/31/2020
-8% -4% -6% -12% 6%
6/30/2020
39% 38% 38% 19% 20%
Total Return
54%

The strategy has been back-tested on the current constituent weights and hence the results are subject to backfill bias and selection bias. Besides, not all stocks were listed in the year 2015 and in such instances, their weights have been equally distributed among other stocks.

| Strategy Rationale

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Fang Plus

The US FANG Plus index has witnessed gains of over 20% in the first half of 2020 as Online shopping, Streaming, social media, gaming, etc found every reason to surge in this trying time as these activities conform to social distancing norms. This crisis has proven that tech is indispensable, and it should only speed up the transition to more tech: video meetings, telehealth, cloud computing etc. Besides, the lower dependence of these companies on physical presence and the substantial cash balances at their disposal makes Fang stocks significantly more resilient to the current downturn. With tech deeply embedded into daily life, there’s good reason to believe that the sector will keep up better than the rest.

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SAAS

Cloud computing is critical to the future of tech and the global pandemic has illuminated the importance of cloud computing. With the world working from home, businesses are relying on this technology more than ever. Cloud technology was a $227.8 billion market in 2019 and is anticipated to grow by a compounded annual growth rate (CAGR) of 16% over the next 3 years.

Software as a service (SaaS) is the largest cloud market thanks to its accessibility and scalability as a subscription-based model. This model is becoming the gold standard among software firms, as it provides a consistent, sustainable revenue stream instead of just a one-time sale. SaaS are high-growth companies since they align with the secular pivot to cloud solutions, and they’re high-margin companies, too, because the costs associated with delivering a cloud-hosted software service at scale are small. Plus, SaaS stocks are also supported by steady and predictable subscription revenue streams. Broadly speaking, SaaS stocks are often growth companies with big margins and lots of revenue predictability. That combination usually makes SaaS stocks big winners in the long run. This trend is not expected to reverse course any time soon. Only 20% of enterprise workloads have migrated to the cloud, so the runway for cloud growth could be long and promising.

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US versus China

Despite appearing to be a highly established market, the U.S. offers significant opportunity for e-commerce growth as e-commerce is still a minor shopping channel in the country. Online shopping in the U.S. accounts for just 8.9% of overall retail sales. In contrast, the Chinese e-commerce sector, which is valued at $1.15 trillion, already accounts for 23.1% of all retail sales.

According to new data from Adobe’s Digital Economy Index, U.S. e-commerce jumped 49% in April, compared to the baseline period in early March. Coronavirus-led restrictions and social distancing norms will force many to opt for online operation and lead to a boost in the US e-commerce market. Besides, US tech companies have penetrated the global economy with individuals across many countries accessing apps like Facebook, Netflix, Amazon among others. On the other hand, the negative sentiments surrounding the geopolitical tensions in China could constraint the growth for Chinese tech companies.

Risks & Assumptions

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The strategy might suffer from look-ahead bias which occurs due to 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 loses could 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.

Data Source: Bloomberg

Arun Leslie John
Chief Market Analyst

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