The Halva Index

Picture a walk through the Machane Yehuda shuk on a Thursday afternoon, weaving through the crowds and the shouting vendors until a block of halva at a stall catches your eye. You buy it and walk away with the quiet satisfaction of a good buy in a market built on haggling and instinct, convinced you paid less than the next person would have paid.

Now picture something that doesn’t exist in any Middle Eastern shuk: screens flashing all around showing the last price paid for any item, updated constantly with every sale. The instant one seller sells for less, every screen updates and the other vendors quickly sell off at that new price. There is no such thing as finding a vendor that will sell for less than the figure on the screen because the whole market quickly trades off at that one price, the one that was flashing on all the screens.

In a shuk like that, you would pay the exact same price everyone else is paying at that moment, no matter which stall you walked up to, no matter how good a negotiator you are. The market has assigned a transparent value to “halva,” and that is the price you are going to pay.

The stock market runs on that same idea: a number flashing across a screen that everyone trades off at once, except with far more machinery behind it than the screen in our imaginary shuk. Thousands of professional analysts, many backed by their own research teams, spend entire careers studying a single company, building models precise to a fraction of a cent in projected earnings. Trading firms run automated systems that read a filing or a headline the instant it posts and update prices within microseconds, faster than a person could finish loading the page. There is no two-minute walk between stalls in this market. The number changes for everyone, instantaneously.

Keep this in mind the next time someone grabs you by the arm with a “can’t-miss” stock tip or you discover a product and figure you found out about it before anyone else. Somewhere out there an analyst covering this company knows the CFO well enough to send his kids birthday cards and modeled the company’s next move to the last decimal point months before you heard the tip. Believing you spotted a bargain because you know something about a company is really believing you outsmarted the market itself. It already knew what you know, and priced accordingly, long before you entered the picture.

There are no deals sitting around waiting to be found in a market that updates itself in milliseconds. Economists even have a name for it: the efficient market hypothesis, the theory that prices reflect all the available information as soon as it appears. This theory was developed by Eugene Fama, who won the Nobel Prize in Economics in 2013.

That theory held up for decades before anything came along to push it even further. Over the past year, Kalshi and Polymarket have grown into the dominant prediction markets, letting investors bet on real-world events from elections and sports to the weather, or on subjects as specific as how many rockets a company launches in a month.

As information about a company becomes more widely accessible, the price of its stock becomes more accurate, and that is exactly why prediction markets matter here. Information used to mean filings, earnings calls, and analyst reports, things that were always public but required someone to go dig them up and interpret them. A prediction market, like Kalshi, makes a different kind of information accessible: the raw, real-time odds of the political and economic events swirling around a company, translated instantly into a single number anyone can see rather than sitting scattered across opinion pieces, polls, and speculation. Google Finance now displays these odds right alongside ordinary stock quotes, so the same process that has always priced a company’s earnings also prices the odds of the events that will produce those earnings—before the earnings report is even released.

Analysts modeling every input they can find, algorithms reacting just as fast, and now prediction markets pricing the probability of the events themselves, all feeding into one continuously updated price leaves very little room for anything to slip through the cracks. Calling a stock undervalued in a market like that is a claim that the market assigned it the wrong transparent value. It is a narrower and harder bet than most people realize: not that you noticed something, but that the whole informed crowd behind that price missed it as well.

That is what market efficiency actually looks like, and it leaves an individual stock picker far less room than instinct suggests. Picking an individual stock stops looking like “insight” and starts looking like a bet against a remarkably well-informed crowd, built from more data, more speed, and more probability pricing than any single person could match. But efficiency does not mean there is nothing left to do. It means the risks worth getting paid for are already identified and can be built into a portfolio on purpose instead of stumbled onto by picking a name and hoping. That is the actual work: not out-guessing the shuk, but owning the right slice of it, deliberately, for as long as it takes to pay off. If you want to see what that looks like for your own money, let’s talk. n

Jack Strulowitz is a Financial Advisor at Bernath & Rosenberg in Cedarhurst, NY, where he helps high-net worth individuals and families manage their investments and build comprehensive strategies for retirement, tax, and estate planning. For questions or to schedule a consultation, please contact [email protected] or 847-962-3352.

The opinions voiced in this material are for general information only and are not intended to provide specific advice or recommendations for any individual. All performance referenced is historical and is no guarantee of future results. All indices are unmanaged and may not be invested into directly.

Investing involves risk including loss of principal. No strategy assures success or protects against loss. 

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