And so it begins. Japan today continues the global trend of electing to leadership another outsider whose views on a range of issues run counter to conventional wisdom. Prime Minister Ishiba takes office styled as an outsider despite having spent decades holding various elected and ministerial offices.
This is not the first unexpected electoral outcome this year. Consider:
European Parlaiment: The center of gravity in the European Parliament shifted right in June as voters expressed dissatisfaction with the high cost of the green transition.
France: The far right and the far left duelled to a draw, delivering a divided government and possibly stasis in France.
UK: The Labour Party trounced the Tories, taking office promising to reverse direction across a brod range of policies.
Germany: This week, the leaders of the Green Party resigned after failing to win seats in three state elections voters in three state elections.
Electoral dramas shift to North America as the autumn arrives. Canada's long-serving Prime Minister barely survived a confidence vote this week. More challenges are expected. And, of course, the United States elects a new President in November. With razor thin margins in both the House (Republicans) and the Senate (Democrats), dramatic shifts remain possible in the Congress.
This is just the prelude. In January 2025, all the G7 except Italy will begin to implement the new policies that won them office.
Their decisions regarding fiscal policy, environmental policy, blockchain/digital currency policy, trade policy and countless more policies will change the trajectory of economic growth domestically and internationally in addition to changing peoples' lives.
And all of this is before we start discussing geopolitical pressures on global supply chains and intensifying armed conflict both in Europe and the Middle East.
Whether you seek strategic opportunities from the incremental daily moves or you seek to play through the shifts in order to maximize for medium-term macro advantages, established assumptions about policy trajectories will be up-ended.
Your journey to explore how to manage global macro policy volatility starts now, with the next generation of alternative data and ML/AI training data that listens to, and illuminates, the volatility signal. How you react to the signal depends on your target time horizon for realizing value. We support both alpha generation and smart beta priorities in capital markets and advocacy.
Listen to the Volatility Signal
Volatility portfolio managers and government relations professionals know a few things that the rest of the world finds hard to believe:
volatility is not necessarily a bad thing
volatility is the norm when public policy and markets intersect with each other
volatility provides important information and data
volatility is not always random.
key is learning how to listen to the signal. Quantitative metrics make it possible literally to see the signal as it appears. Structured language data paired with the quantitative data powers additional insights when used as inputs within advanced technology.
PolicyScope data has been designed from the beginning to capture and measure amplitude in the policy process. Designed by experts that have worked within public policy at the leadership level for decades and backed by a fully issued US patent, the data enables users to get past the shock-and-awe reaction function often triggered by the news cycle.
The technology measures the pulse of public policy daily, automatically, and objectively so that strategists can make better decisions based on hard data. They can compare action levels across years. They can see the action levels rising and falling. They can identify breaks in the time series as policy formation shifts to a different plane using different words.
We serve up the data in packages designed to align with existing automated work flows. Three main package types currently exist:
.csv files: For financial market quants and data scientists who seek to train ML/AI-powered predictive analytics, perform trend identification and anomaly detection, and to identify correlation and covariance patterns with tradeable assets.
Tableau-based dashboard: For knowledge professionals, investment advisors and policy advocates seeking to navigate and personally read the underlying words in addition to seeing the data visualizations.
Structured, Tokenized Language: For chatbot architects seeking to build automated research assistants focused on public policy issues.
The time to start working with the data is now, before policymakers start taking action.
BCMstrategy, Inc. generates training data for a broad range of ML/AI applications and use cases using award-winning, patented technology that converts the words of the public policy process into notional volume measurements and signals.