Earlier this year, Interactive Brokers suggested that we initiate a blog series entitled “How To Trade The News. for their Traders’ Insight blog channel. The idea was simple: provide traders with clear guidance on how to generate alpha and hedge against news-driven market volatility. BCMstrategy, Inc. dove into the project by providing 1000–1500 words nearly weekly throughout the spring.
The posts generated the most traffic for a new contributor at Interactive Brokers, illustrating that quite a bit of demand exists for concrete guidance on how to make sense of the news cycle. The strong reception inspired the book, which consolidates in one place (40+ pages) all the blog posts in the series and adds a few elements (like YouTube videos).
High demand for this content should come as no surprise. With policy volatility hitting record highs in the #Brexit, #trade policy, and #FinTech policy arenas this year (not to mention #cryptocurrency regulation), professional investors naturally seek more advanced ways to measure and manage their exposure to headline risks generated by the public policy process.
Our core recommendation is that capital market participants should treat public policy risk as if it were an asset class.
Algorithmic traders have been executing trades based on headline risk for over a decade. Some commentators believe this activity accentuates (and possibly drives) market volatility. However, public policy and market activity were intertwined long before algorithmic trading existed.
Capital market participants consistently rely on public policy developments to guide their investment strategies in order to generate alpha and hedge downside exposure from headline risk. This is why capital market participants have been early adopters of various communications technologies from the telegraph and ticker tape to Bloomberg and the Blackberry to the smart phone.
Check out our new YouTube video, which traces the evolution of communications technology in the capital markets in less than 30 seconds:
The vast majority of news-related market activity is reactive as traders race to be the first to price in the implications of new developments.
The ensuing volatility has generated the perception that policymaking is unpredictable, random, and volatile. A career in various aspects of public policy and the law teaches a different lesson.
Policy decisions rarely surprise advocates and policymakers.
Why? Because policymakers and advocates effectively treat policy risk in the same way that traders treat market risks. They follow developments relentlessly, strategically, and comprehensively.
Technology (particularly Natural Language Processing) now makes it possible to translate the language of public policy risk into structured data and adapt the policy monitoring process to the market context. Capital markets need data the way people need oxygen. Information about the public policy process and headline risk are part of that data stream. But only recently has it become possible to transform all that unstructured verbal data into structured integers that are amenable to data visualization and predictive analytics, as we recently discussed HERE and HERE.
Smarter ways exist to monitor, measure, and manage public policy risks than tracking the tickertape or staring at a screen in order to pounce on a headline.
The days of successful trading based on headlines are numbered.
Advanced technology (including our patented process) delivers enhanced cognition, making it possible for day traders and small asset managers to generate the same if not better access to concrete facts and predictive analytics from the news cycle than their larger counterparts that traditionally have relied on armies of human intelligence.
Advanced mechanisms for monitoring public policy risk provide a fringe benefit for market participants and advocates.
A laser-like focus on concrete facts provides a powerful antidote to reaction function powered by rumor, innuendo and fake news. Stay tuned for more on this theme as the summer unfolds
Access to quick, transparent, analytical data regarding policymakers activity globally on a 24/7 basis, empowers market participants to read smarter, mute the noise the news cycle, and generate returns by acting strategically while others are reacting.
We hope that our new ebook helps traders break the reaction cycle associated with headline risk. We also hope it helps accelerate their ability to take advantage of the data revolution to build smarter strategic investment strategies.
Barbara C. Matthews is Founder and CEO of BCMstrategy, Inc., a start-up technology company delivering predictive analytics regarding cross-border public policy with a patented process that measures public policy risk. She spent the prior two decades of her career immersed in private and public sector leadership positions in global financial and economic policy.