How To Trade The News — Rule 4

You have your investment thesis. You are committed to being objective (Rule 1) and strategic (Rule 3). You are disciplined about understanding that The Trend is Your Friend (Rule 2). You have a mechanism for tracking news developments.

Then a blockbuster economic data point is released, which generates substantial market volatility. What do you do? Hope for the best? Take the ostrich strategy and pretend the data don’t exist? Rationalize that you are only trading the news so the data is irrelevant?

The right answer is: none of the above.

Economic data releases are always relevant and important. The key is to understand the relationship between specific data points and specific news-driven trading exposures. Data releases and the news cycle have an obvious symbiotic relationship. Data releases generate news cycles, as well as trading opportunities. You cannot ignore the data. Instead, you need a strategy for how to read data in the context of the news cycle. Welcome to Rule 4.

Why Economic Data Matters

Economic data obviously sends important directional signals regarding the economy. Economic data thus has a direct and important impact on asset classes particularly important to macro traders (FX, sovereign bonds, corporate bonds). The market reaction function to data releases can spill over into other asset classes when the data release demonstrates unexpected outcomes (positive or negative). The reaction function thus generates the incorrect perception that economic data always drives policy risk.

Reality is more complicated. When trading the news cycle with an eye on geopolitics and policy risk, economic data can create distractions. Economists and pundits will pounce on data releases to declare that policymakers “must” take a particular action in light of the released data. However, the correlation between policymaking and economic data releases is far from direct in most non-crisis situations.

Minimize headline risk with respect to economic data releases by taking five simple steps.

Step 1: Identify in advance which specific economic data points will have a material impact on your position. For example, a strategy focused on trade policy news will be directly impacted by trade deficit/surplus data releases but not necessarily by inflation data.

Step 2: Automate the tracking process. Identify release dates from all relevant sovereigns. This is a fairly straightforward calendaring function since most jurisdictions publish economic data releases well in advance. RSS feeds and enhanced cognition platforms make tracking the release process easy, eliminating the risk of being surprised by the timing of a data release. Automated ingestion of data releases into spreadsheets immediately upon release of the data turbo-charges the data acquisition process, effectively turning the data release and analysis function into an IoT activity. The magic occurs not in being the first to acquire the data but in being the first to understand what the data means. See Step 3 below.

Step 3: Identify specific values for economic data points which will create adverse downside risk for your chosen time horizon/holding period. Automate the alerting function by requiring your spreadsheet to notify you when specific or anticipated threshold values appear in the released economic data. For example, if you know that trade negotiations between two countries are politically sensitive to specific deficit or surplus levels at the bilateral level, then set up an alerting function to trigger when those levels have been breached.

Step 4: Update/refresh your data expectations and alerts following data releases.

Step 5: Ignore all other data releases when making decisions about the position.

Portfolio structure and investment theses in other asset classes require meticulous preparation to identify potential pressure points from market data in order to structure stop-loss orders and other trading thresholds. The news cycle is no different.

The corollary to market data in this context is economic data. Economic data will accelerate or constrain policymaker choices. But only specific data releases will impact specific policies. So being strategic and thinking it through at the beginning will minimize downside risk from headlines regarding irrelevant data points.

Rule 4 does have limits, however.

If you are treating the news cycle as an asset class, it is therefore necessary to understand the nooks and crannies of that asset class in the same level of detail as an FX position or a bond position.

Traders at large firms will have access to economists as well as outside experts who can provide guidance on which threshold levels will impact specific policy choices. The process can become complicated quickly. Solo traders must personally invest their time and effort to understand at a minimum which data points are important to a news cycle trading strategy in order to avoid being whipsawed by unrelated volatility.

Due diligence can help solo traders at least automate alerting functions when data releases indicate a reversal of direction and the impact a reversal would have on their position so that their own reaction function decreases. For example, in the trade context, if a bilateral trade deficit is expected to grow, a rudimentary alerting function could be triggered if instead a surplus develops.


Economic data releases drive news cycles, creating the news even when they deliver directional indicators regarding real growth prospects. Any effort to trade the news cycle must incorporate a strategy regarding economic data releases in order to minimize adverse impact on a position from headline risk driven by data releases. Approaching the news cycle as if it were an asset class helps define which specific economic data releases will be important to a trading strategy.

The complexity of the economic data tracking and signaling process will be determined by the resources available to any given trader. The key is to implement a disciplined, consistent process for assessing the impact of data releases when preparing to trade the news. Even the simplest process will deliver enhancements in risk profiles (and possibly alpha), especially if the rest of the market has not yet implemented Rule 4.

Barbara C. Matthews is Founder and CEO of BCMstrategy, Inc., a start-up technology company that quantifies public policy risk using patented technology. She is a former U.S. government official and a respected global thought leader regarding geopolitics and cross-border regulation. Beyond the company, she is non-resident senior fellow at the Atlantic Council, a member of the Council on Foreign Relations and the Bretton Woods Committee, and an occasional blogger on FinTech regulation at her graduate school alma mater Duke Law School. An earlier version of this post first appeared on the Traders’ Insight blog hosted by Interactive Brokers.

Quantifying cross-border policy risk using patented tech Founder & CEO #Data #NLP #geopolitics #DigitalCurrency #PredictiveAnalytics

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