We explore Dynamic Conditional Correlation (DCC) models. Results indicate that explicitly modeling the dynamics of the conditional covariance matrix increases risk-adjusted returns for more aggressive portfolios and outperforms the market by more than the baseline Xantos algorithm does.
Our macro indicators highlight that (1) it is very unlikely that the US economy is currently recession (2) the likelihood of a recession in the near future is currently relatively high, above 50 percent. While it is impossible to say for sure whether there will be a recession soon especially as macroeconomic forecasts are notoriously inaccurate, short-term market volatility remains above its historical average. And we expect higher-than-normal volatility in the near term. Today, we continue to employ a cautious approach to allocating dollars in our portfolio.
IPOs and SPACs allow private companies to issue shares to the public and raise capital from public market investors. However, investing in recently-public firms has generally not been accretive for investors in the long run. The evidence that this is systemic reflects investor behavior consistent with early hype.
This study investigates the tradeoffs of introducing fixed income-like assets to the Xantos core fund using bond ETFs. Results indicate that a carefully selected and appropriately calibrated bond-enhanced portfolio provides significant downside protection and diversification benefits with a minimal performance cost. Capped exposures along the yield curve can be alpha-accretive in the long run. It also offers noticeable downside protection as evidenced by lower maximum drawdowns and portfolio volatility in a range of macroeconomic and financial market contexts.
It is evident from our analysis that the primary drivers of inflationary pressures are ebbing/stabilizing. Market volatility remains high in the face of Omicron-variant driven selloff and Fed policy actions. What happens next is anyone's guess. We believe our investments remain strongly positioned in the long term. Copying a quip from our Feb 2020 investor memo (at the height of sharp market selloff): This too shall pass!
The US healthcare industry is massive but plagued with operational inefficiencies that make it ripe for disruption. In our view, the revolutionary new technologies in the field of genetics engineering could present unique opportunities for above-average returns in the near decade. The less discretionary nature of healthcare spending makes the sector attractive especially during periods of (transitory) inflation. We believe the resilience of the sector, the non-discretionary nature of healthcare spending, and the operational excellence of some of our high-moat holdings help position us for unforeseeable market conditions.
Investors' outlook for financial stocks looked bleak when the pandemic hit but fears did not materialize but rather the sector performed well. In our view, a strong economic recovery bodes well for continued strong M&A activity. Additionally, the global normalization of monetary policy and rising yields and term premia will drive stronger earnings. Over a longer horizon, we expect the increasing adoption of technology in insurance and asset management workflows will continue to drive efficiency improvements and lower intermediation costs.
Our analysis from a sample of actual live accounts confirms that client accounts closely track the simulation results from our backtesting framework. This is great news! Even more important, the accounts closely tightly track each other, despite the over 25x difference in average balance between the largest and smallest! Lastly, the introduction of fractional trading by our primary brokerage partner halved the tracking error between accounts leading to even higher operational efficiency.
Our macro outlook remains positive despite the downside risk posed by the pandemic and its influence on consumer behavior and Fed policies. In all, we view inflationary risks as transitory.
For investors, the recent pace of advancements in the field of genomics could present unique opportunities for above-average returns in the near term. Our task remains unchanged: identify these opportunities focusing on those with favorable risk-reward profiles for our clients. Naturally, we anticipate the continued non-linearity in the pace of advancements in this sector through the convergence of the fields of CRISPR and mRNA. In the near future, we might be close to making genetic diseases a thing of the past.
Our business cycle prediction models that predict the probability of a recession helped us limit downside risk during the 2020 recession. While no forecasting model that depended on traditional macro data—which often arrive with a lag—could have caught an out-of-sample event like COVID-19; our quantitative approach helps reduce sentiment in risk management.
Maturing green technologies and rapidly falling costs continue to drive investment flows to renewable energy globally. The regulatory push by policymakers has also accelerated the decommissioning of coal and gas plants as the world gets greener. However, all that glitters is not gold.
Our breakdown and expectation of the American Jobs Plan including views on sectors that will likely benefit from its tailwinds if passed.
When should I invest and how often? Should investors wait for a market dip? In this paper, we explored various approaches used to deploy capital: from dollar-cost averaging (fixed amount on monthly or quarterly schedule), to lump-sum (once a year), and timing for when the market dips. We conclude that the most important thing is to have a plan and stick with it. More importantly, attempting to time the market results in subpar performance.
Enabling short sales in this investment framework underperforms the benchmark configuration in a risk-unadjusted sense. Our strategy's performance with the alternative configuration will need to be optimized by hyper-tuning several parameters. Additional considerations need to be made for the investable universe especially given the structural and secular tailwinds for the timeframe explored. Shorting universe of winners is a poor exercise as most have better than average growth prospects. Implementing trailing stops or developing an event-driven framework might yield better performance.
We share quantitative tools we use to manage downside risk in face of changing macroeconomy and the efficacies of those tools in predicting the probability of business cycles transitions.