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It is not possible nor sensible to form predictions into the future. However, in times when current conditions present dubious forecasts, it is imperative to keep in mind our perspective. As Mark Twain pens in The Gilded Age: A Tale of To-Day, “History never repeats itself, but the Kaleidoscopic combinations of the pictured present often seem to be constructed out of the broken fragments of antique legends.” While Tulipmania or Black Monday will not identically reoccur, we can use such events to learn from the past and evaluate proper risk-return principles to develop our guide to current market conditions. Although the future is always unknown and unforeseeable, if we incorporate historical experiences with forward-looking expectations we may analyze such scenarios.
Between 1950 and 1960, economists used adaptive expectations theory which formulated business and consumer expectations based on past experiences and suggested change will occur slowly. However, since people hold more information than just past data, adaptive expectations theory was relatively misleading. In response to such outlook, John Muth established an alternative, rational expectations theory, which forecasts expectations using all available information. In retrospect, any expectation can be put in one of two buckets; what was predictable and what was unpredictable even looking back. Anticipated events such as the Dot.com Bubble or 2008 Financial Crisis, while unforeseen events include Black Monday or the Flash Crash. However, we must also consider the third type of occurrence. As Donald Rumsfeld ex-Secretary of Defense famously said, “there are known knowns; there are things we know we know. We also know there are known unknowns; we know there are some things we do not know. However, there are also unknown unknowns – the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones.” While Rumsfeld might sound like a hyperbolizing politician, these events are relevant to risk. There are known risks which we can and cannot quantify, and there are also risks are unknown that we can be able to quantify and but also cannot quantify. After the 2008 Financial Crisis, a new paradigm for pricing risk has developed, and the next unknown unknown is further eminent. While adaptive expectations have allowed for variable change and shifting expectations, predictions may also artificially create optimal estimates using goal seeking prediction models based on faulty conclusions. In fact, the rise of big data leading to the use of algorithms and fin-tech instruments have extended rational expectation theory. Such models have changed our perception of risk by hiding structural problems with imperfect models that remain untested during recent recessions. Attempting to understand recession probability is nearly impossible as evidenced by Graph 2 that even the Dallas Fed can not properly model recessions probability.
A recent article by investment management firm PIMCO, “Pivot Points” put forth their probability model to evaluate such future market conditions. The article announces, “if history is any guide, we believe the probability of a recession sometime in the next five years is around 70%.” If this is the case, we must consider such scenario. I analyzed three five-year time frames of growth, followed by two-year downturns. As depicted in Table 2, the years 1995 through 2000, 2002 through 2007, and post-2009 S&P 500 shows periods of boom. Conversely, during the Dot.com Crash of 2001 and 2008 Financial Crisis brought years of decline. The five-year growth during bull terms averaged 192%, while bull periods saw a negative 51% decline. From this boom-bust model along with the numbers presented by PIMCO, I project a mean expected return of negative 23% within the next five years. While this exercise uses imperfect past historical data, the results show if these modern scenarios duplicate past price action then this deserves our attention. Evaluating current expectations, we can theorize on miscellaneous macroeconomic shifters as well. In the next five years, United States fiscal policy should include tax cuts as well as increased spending. We can assume that the FED will begin to normalize balance sheet and increase interest rates. International concerns include Italian Banks, Greek debt, and continued Brexit fallout uncertainty. Concerns of Chinse economic collapse buoy in the horizon but Xi Jinping’s defect New Silk Road poses uncertain time horizons. Bilateral trade deals with China, Russia, and other nations project to widen trade policy as President Trump seeks to reduce the deficit. Again, the rise of the quants has also held an undeniable effect on markets. These models predict all known variables bridging the past, present, and future estimates and continue becoming more efficient. Skeptics argue that evidence using historical back testing will prove to be ineffective in the long run despite short-run profit due to underpinned structural risks. Indeed, these assumptions are not fact, but we can use such assumptions as macroeconomic expectations. Indeed, some tranches will fall flat, yet asset allocation contains the advantage of shielding risk from overweight market conditions and identifying markets that will outperform. Recent low volatility figures may provide a blueprint moving forward.
The Volatility Index evaluates this differential between the perception of the world and as it exists. As evidenced in Graph 1, Volatility sits at its lowest point in years and dubiously mirrors 2007. Whether this represents an eerie lull or not, what is certain is the unknown market expectations have peaked. Unusually low volatility has paved the way for questions about unknown and unquantifiable events. What is unforeseen is real growing threats to our economy gone unpriced within the market. The risk-reward paradox is critical when understanding that risk compensation for with reward one to one. Greater risk should see higher expected returns. However, this much has failed to come true in current markets. While a projection of a recession based on such problems is nearly impossible and timing, the market is a near fatal task. However, tactical asset allocation can take advantage of current conditions, good or bad. The role of such strategy is not to predict the future but to identify mispriced risk.
To evaluate unknown conditions, we must prepare for unknown unquantifiable risks when evaluating what we can forecast. While charting unknown territory, the influence of adaptive versus rational expectations, understanding historical models within present day, and understand volatility as a metric are important considerations. Overpriced assets usually contain market identified risk and thus should include such compensation. As further evidenced in the volatility index and explained the scenario analysis, unknown and uncalculatable systematic risk are not being rewarded. Eminent geopolitical, economic, and unknown risks are peaking while the Volatility Index is flat. Rising concerns around debt and credit default are real drivers of uncertainty. Thus, mispriced markets are evident. To reiterate Mark Twain’s thoughts, history does not repeat itself, but it sure does rhyme. Although the next five years will contain an inevitable market shift, allocation and models should reflect pragmatic expectations. Uncertainty about the future will remain, but the answer is where risk fully reciprocates return.
Graph 1
Table 1
Graph 2
Works Cited
Cole, Chris. “BULL MARKET IN FEAR.” (n.d.): n. pag. 23 Oct. 2012. Web.
“Federal Reserve Economic Data | FRED | St. Louis Fed.” FRED. Federal Reserve Bank of St. Louis, n.d. Web. 30 May 2017.
“The Gilded Age.” Google Books. N.p., n.d. Web. 02 June 2017.
Graham, David A. “Rumsfeld’s Knowns and Unknowns: The Intellectual History of a Quip.” The Atlantic. Atlantic Media Company, 27 Mar. 2014. Web. 02 June 2017.
Richard Clarida, Andrew Balls, Daniel J. Ivascyn. “Pivot Points.” Pacific Investment Management Company LLC. N.p., n.d. Web. 02 June 2017.
Trey Taylor 