Wanna A Bet
Betting on binary outcomes—such as the outcome of a drug trial—introduces a fundamentally different risk profile to most forms of trading. In conventional market environments, trades tend to fail gradually.
Prices move against the position in increments, allowing the trader to respond: stops can be adjusted, positions reduced, or risk reassessed. Losses unfold over time, and with discipline, they can be contained within predefined limits.
Binary events remove that luxury.
The recent collapse of Immutep provides a stark illustration. The company had promoted its lung cancer therapy, Efti, as a potential breakthrough that could extend patient survival. Expectations were high, and significant capital had been committed by sophisticated investors, including Regal Partners. Yet, following the recommendation of an independent committee, the trial was abandoned. When trading resumed, the market did not decline in a measured fashion—it repriced instantly. The stock fell approximately 90%, erasing more than $500 million in market value in a single move.
This is the defining characteristic of binary risk: discontinuity.
In a typical trade, price behaves as a continuous variable. Even sharp sell-offs tend to exhibit some degree of liquidity, allowing exits to occur across a range of prices. Risk models—ATR stops, position sizing, portfolio heat—are built on this assumption of continuity. They assume that adverse movement will occur in a way that allows intervention.
Binary outcomes violate this assumption entirely. These sorts of trades are little better than betting on the outcome of a coin toss.
There is no “path” to manage—only a gap between two states. Before the announcement, the asset reflects optimism, uncertainty, and probability. After the announcement, the distribution collapses into a single realised outcome. The transition between the two is not tradable. No stop-loss order can protect against a 90% overnight revaluation. No incremental scaling can soften the impact. The trader is not managing risk in the usual sense—they are underwriting an event.
This creates several structural problems.
First, position sizing becomes deceptive. A trade that appears small relative to capital can, in reality, carry disproportionate tail risk. The apparent volatility prior to the event understates the true risk because it excludes the binary jump component. Traders who anchor their size to historical price movements are therefore operating with incomplete information.
Second, diversification offers limited protection when portfolios are concentrated in similar event-driven exposures. Multiple “independent” biotech positions, for example, may all be subject to the same binary dynamics. Correlation is not the issue—shared structure is.
Third, psychological framing becomes distorted. Traders often treat these setups as high-probability opportunities based on narrative—promising trial data, strong management commentary, or prior success in similar therapies. However, the underlying reality remains unchanged: the outcome is discrete and largely outside the trader’s control. Conviction does not alter probability.
Finally, binary trades encourage a mindset closer to speculation than systematic trading. They shift focus from process to outcome, from risk management to prediction. This is a subtle but important drift. The trader moves from managing distributions to betting on singular events.
In contrast, gradual trade failure preserves optionality. It allows for feedback, adaptation, and control. Binary outcomes remove all three.
The lesson is not that such trades should never be taken, but that they must be recognised for what they are. They are not simply higher-volatility trades—they are structurally different instruments of risk. To treat them as ordinary positions is to misunderstand the game being played.
