A volatility channel plots lines above and below a central measure of price. These lines, also known as envelopes or bands, widen or contract according to how volatile or nonvolatile a market is. Nordqvist It should be noted that event itself and its consequences may either be positive or negative for example wars, natural disasters and technical innovations.
Also, black swan theory also applies to events happening to an individual and not necessarily a large number of people all the time. Black Swan Investment Strategy We invested in stocks which have had the largest percentage decrease or increase after an extreme event. Based on the mean reversion assumption, we expect these stocks to come back to their fundamental mean values thus providing us the highest profit.
We can go either long or short relevant to the negative or positive Black Swan event. Methodology 3. All of them traded by the various trading strategies, among them the BB indicators. Some assets inside the portfolio are highly correlated among themselves. We could remove them too but still left them as is for the sake of simplicity. Netflix Inc. Figure 2.
Alphabet Inc. Selecting assets with Black Swan events We selected the assets based on the 3 types of Black Swan events: 1. The p-value for all tests is 0. All assets were normalized and added into 2 equally weighted portfolios with the highest number of Black Swan events and the lowest value of the Jarque Bera test.
Assets with Black Swan events Figure 4. For example, the American Airlines Group Inc. AAL asset with Black Swan trade signals 3. The Bollinger Bands Trading Strategy In BB indicators we compared rolling mean with STDs against another quick rolling mean instead of the real asset in order to decrease the number of trades. For example, the quick rolling mean can be the 5-day and the STD can be calculated based on the day rolling mean.
All trading strategies generate many identical sequential signals. In that case we take into account only the first signal and the rest identical signals remain unattended. The optimization function goal was to reach the maximum portfolio return after the iterations. We know that the professional traders tend to use other targets for the optimization functions like, for example Sharpe ratio, VaR or CVaR.
We will be using here the total asset returns for the sake of simplicity. We also neglect the trading costs and the costs of borrowing money for long trades and borrowing assets for short trades. The hyperparameters for each asset are calculated separately and all assets then combined together into an equally-weighted portfolio. On the other hand, the Calmar ratio uses the maximum returns drawdown instead of the standard deviation.
The maximum drawdown is the largest drop of returns, when considering sequential tops and bottoms. It is the largest peak to trough decline. Results 4. Hypothesis I It is not possible to construct a Mean-Reverse strategy solely based on the BB indicator that outperforms the market over time. Figure 7. We assume that it happens because of the relatively high normality of the containing assets.
Figure 9. Table 3. Hypothesis II It is not possible to construct a Mean-Reverse strategy based on the Black Swan events that outperforms the market over time. Figure Table 5. Table 7. Any other hyperparameter combination returns negative results. Thus, it speculates on reversal to the fundamental value which is mean reversion.
Since the bands are two standard deviations below and above the moving average, this alternatively provides a relative definition of high and low. However, because stock prices always reflect the true value of firms as per the efficient market hypothesis Fama, , no overbuying or overselling can be witnessed.
As pointed out by Vargas and Estrada , mean reversion must be present for the strategy to outperform the market. Their assumption was that indices do not follow random walk but are mean reverting. We assumed mean reversion for our trading strategy. In addition, both Bali et al. Furthermore, mean reversion was proved by Gatev et al. The findings from the above-mentioned researchers therefore supports our findings. If mean reversion did not exist, then our findings would have no empirical backbone which is that of mean reversion.
His findings were that the BB strategy did not outperform the market. In addition, the BB strategy with the shortest-term moving average was found to generate the greatest abnormal returns, considering transaction costs. Furthermore, the research has found that it is possible to construct a Mean-Reverse strategy based on the Black Swan events that outperforms the market over time.
Before the financial crisis, the prices of stocks were highly overbought. Because the BB strategy recognized those overbought stocks, it provided investors with a sell signal. Thus, this strategy could outperform the market in the presence of black events. However, bubbles do not last forever, as they will burst one day. Contributions to literature This research contributes to literature in several ways. This trading strategy provided can be applied by the investors who prefer sensation seeking and are less than fully rational.
Summary of research findings, conclusions and recommendations 6. Introduction This chapter outlines the summary of research findings and gives the conclusions that can be drawn from the study. In addition, it also gives recommendations to traders and paves the way for further studies in the subject. The research concluded that it is possible to construct a Mean-Reverse strategy solely based on the BB indicator that outperforms the market over time but only for the portfolio consisting from naturally distributed assets and that one can outperform the market with a mean reverse strategy based on the black swan events.
Recommendations to traders As we clearly see Bollinger Bands indicator as an implementation of the Mean-Reverse strategy alone can be considered a sign for buy or sell signals for naturally distributed assets. In any case the Black Swan events give much stronger signals and can be used for opening long or short trading positions. Researchers like Lo and MacKinlay , have found the evidence against mean reversion. It is also worth adding to the study of Grey and White events. They are not as strong as the Black ones but can be predicted with greater probability, opposite to the Black that cannot be predicted at all.
The reaction to such a Black Swan event is predictable: defensive assets are heading north and risk-sensitive assets are heading south. Safe haven currencies such as the US dollar and the Japanese yen are on the rise. Gold, silver and oil, which retraced to highs since September , are also on an upward trajectory. Equity markets, risk currencies and emerging market currencies are in decline across the board. The Russian ruble has plunged to all-time lows.
The current downside target is 1. The median consensus is calling for 7. Markets are expecting another volatile week with whippy price action across asset classes. We got more headline grabbing UK data this morning. Risk-off sentiment has dominated global markets in recent weeks. Headlines around some of the more speculative areas of the market like cryptos, have abounded in this environment.
Similar to a positive black swan event, negative black swans also have an extreme impact. Lastly, one quality that qualifies a black swan event is the improbability for it to occur. This comes largely due to the perception of humans.
Another distinct character of a Black swan event is that the same event does not repeat again. History has offered numerous examples of black swan events that makes for a good study. The past black swan events can help the reader to understand the black swan theory. It also offers insights on how investors and speculators in the financial markets can use the past experiences to better protect themselves. The dot com crash spanned two years.
The dot com era emerged after the emergence of the Internet. Boasting of nearly 18 million users at the time, the Internet caught on commercially. This led to an influx of capital which turned many small companies into overnight publicly listed stocks. Interestingly, some of the companies that emerged during the dot com boom were the likes of Amazon Inc.
EBAY to name a few which survived the crash. The most famous example of the dot com bubble was pet. An online store that allowed customers to purchase pet supplies. The company debuted in February of and went bust in under a year. During the height of the dot com boom, anyone with an idea to build something online quickly became an overnight sensation. The optimism was fueled by banks also actively participating as underwriters. For the banks, profits came mostly from underwriting and investment fees rather than investing in the stocks.
Before the bubble burst, a market crash was unthinkable. Cracks started to emerge by early The Nasdaq which surged strongly lost over a trillion in market valuation within a month. This came as companies began to report losses. The losses came as basic logic was shown the door as investors grew exuberant. While in hindsight it would have been easy to see the crash, the optimism in the build up to the crash certainly blinded many.
The mortgage crisis started in and was the aftermath of the housing market boom. The U. The mortgage crisis emerged after the U. Federal Reserve cut interest rates to historically low levels. Fueled by cheap credit, lenders began to extend mortgages even to those with weak credit histories.
Sentiment in the economy was high, rather clouded and at one point a mass default was deemed improbable. The black swan event of wiped out billions in valuation, left many people without a job and caused some leading financial institutions to bankruptcy. Within no time, as the mortgage rates started to rise, the number of defaults started to grow.
The default on mortgages hit a peak in As job losses started to grow it was difficult for the average home owner to refinance their mortgages. This led to a meltdown in the financial markets. Financial institutions on their part also played a major role. The development of mortgage related securities became famous and every other bank started to trade with them.
The central bank of Switzerland announced that it was going to terminate the cap on the Swiss franc. The SNB had a program in place to keep the euro from falling below 1. This event had far reaching implications in the spot forex markets as some online retail forex brokerages went bankrupt.
Even day traders were not spared. Even the large and well established forex brokerages were not spared. FXCM Inc. Prior to the SNB giving up the floor, market participants considered it to be unthinkable. The central bank announced its currency peg in Despite retail and institutional trades repeatedly testing the floor of 1. Over a period of time, the retail investing community took it for granted.
It quickly became the norm that no matter what, the Swiss national bank would continue defending the floor. It was due to this complacency that traders started to feel at ease. Every time the Swiss franc increased in value, the central bank would purchase foreign exchange to weaken the franc. As with a black swan event, the rationalization that came after the event tried to explain the central bank actions.
Reasons given included the Swiss citizens ire against the central bank amassing huge forex reserves to defend the currency peg. With the central bank printing more currency, fears of hyperinflation also made the rounds as a rational explanation. The removal of the peg came at a time when the European Central Bank was starting to increase its bond purchases under the quantitative easing program.
Combined, the above factors explained the reasons making the currency de-peg as a black swan event. One of the common misconception is that a black swan event is always disastrous. However, you can be insulated from a black swan event. Taleb explains this using the illustration of the butcher and a turkey. A turkey is fed for days, which leads the turkey to become complacent. From the Great Depression to the more recent Global Lockdown, these events resulted in decimating entire economies, stocks, and currencies.
A textbook black swan event example — and one of the most devastating black swan events in history — is the Great Depression. This event was so severe that it is often used by economists to describe how intense a financial crisis can hit the world economy. This flash crash caused a worldwide decline in stock prices and a severe reduction of the global economic output. Although some countries began to recover by the mids, other countries felt the negative effects until the beginning of World War II.
While the causes of the Great Recession are still not crystal clear, some economists believe that the sudden crash of the stock market led to lower investor confidence, which in turn caused a reduction in consumption and investment spending. As deflation hit the economy and prices started to fall, many people believed they would be better off by reducing the spending even further in anticipation of even lower prices.
As a result, the extreme drop in demand has catastrophic consequences on the US economy, which later spread to other countries globally. Another popular theory is the monetarist explanation, which believes that the shrinking in money supply was the main cause of why an ordinary recession turned into one of the greatest economic downturns. Finally, some economists blame the gold standard to be the primary transmission mechanism of the Great Depression.
However, it was the suspension of gold convertibility that made economic recovery possible. Almost every major currency left the gold standard during the Great Depression. In , the United Kingdom ceased exchanging pounds for gold after a series of speculative attacks on the currency, which made the country one of the first to recover from the economic downturn. Japan and the Scandinavian countries followed the UK and left the gold standard in , followed by Italy and the US.
Some countries, like France, Belgium, and Switzerland, stayed on the standard until , which caused a slower economic recovery than countries that had freely floating currencies. Although the Great Depression is reaching its th anniversary, it still provides valuable lessons to traders and investors about how severe an economic downturn can be, and how pegged currencies can prove to be a major hurdle for recovery.
One of the more recent black swan event examples in the financial markets was the Asian financial crisis. Singapore, Taiwan, and Japan also felt the consequences of the crisis, although to a lesser extent. However, higher interest rates and economic growth in the region also attracted speculative money that searched for a quick profit. Asset prices kept rising, forming a bubble that required even more capital to be maintained.
The crisis started with the collapse of the Thai baht on July 2, , after the government lifted the currency peg to the US dollar due to lack of foreign reserves. As a result, capital outflows started almost immediately, leading to a sharp sell-off in the Thai baht, and later in other Asian currencies as well. The fact that south-east Asia accumulated a huge pile of foreign debt made the devaluation of their currencies even worse.
Figure 1Source: www. Currency markets were the most hit during the crisis. The Thai baht fell from The Indonesian rupiah was hit the most. The dot-com bubble, also known as the Internet bubble, was a bubble in the stock market in the late s, mostly fueled by excessive speculation in internet-related companies. The advance of the internet and massive adoption of computer technologies nursed many new companies that were focused on the internet, including names such as Pets.
Speculative capital began to flow to newly-founded companies that were mainly focused on delivering their services over the internet. Investment banks were also profiting from a surge in IPOs and encouraged investment in the new internet companies. At the peak of the dot-com bubble, internet companies were able to become public companies and organize an IPO without a penny of profits.
People started quitting their jobs to trade the financial markets, and many employees who received stock options became instant millionaires. Some popular companies, like Amazon and Cisco, were also hit hard but managed to survive the drop in their market capitalization. The bursting of the bubble was initiated by several smaller events.
First, former Fed governor Alan Greenspan announced that the central bank is planning to hike interest rates in , which led to increased market volatility and concerns of higher borrowing costs for internet companies.