Tagged: Renaissance Technologies

Proportional Response

Proportional Response is the art of defusing geopolitical conflict.

Proportional Response is also efficient effort. With another earnings season underway in the stock market, efficient effort should animate both investment decisions, and investor-relations for public companies.

I’ve mentioned the book The Man Who Solved the Market, about Jim Simons, founder of Renaissance Technologies. There’s a point where an executive is explaining to potential investors how “RenTec” achieves its phenomenal returns.

The exec says, “We have a signal. Sometimes it tells us to buy Chrysler, sometimes it tells us to sell.”

The investors stare at him.

Chrysler hadn’t been a publicly traded stock for years (they invested anyway – a proportional response).

That executive – a math PhD from IBM – didn’t care about the companies behind stocks. It didn’t bear on returns. There are vast seas of money rifling through stocks with no idea what the companies behind them do.

RenTec is a quant-trading firm. Earnings calls are irrelevant save that its models might find opportunity in fleeting periods – even fractions of seconds – to trade divergences.

Divergences, tracking errors, are the bane of passive money benchmarked to indexes. If your stock veers up or down, it’ll cease for a time to be used in statistical samples for index and exchange-traded funds (ETFs).

And hedge funds obsess on risk-adjusted returns, the Sharpe Ratio (a portfolio’s return, minus the risk-free rate, divided by standard deviation), which means your fundamentals won’t be enough to keep you in a portfolio if your presence deteriorates it.

Before your eyes glaze over, I’m headed straight at a glaring point.  Active stock-pickers are machinating over financial results, answers to questions on earnings calls, corporate strategy, management capability, on it goes.

On the corporate side, IR people as I said last week build vast tomes to help execs answer earnings-call questions.

Both parties are expending immense effort to achieve results (investment returns, stock-returns). Is it proportional to outcomes?

IR people should have their executive teams prepared for Q&A. But let’s not confuse 2020 with the market in 1998 when thousands of people tuned to Yahoo! earnings calls (that was the year I started using a new search engine called Google).

It’s not 2001 when about 75% of equity assets were held by active managers and some 70% of volume was driven by fundamentals.

It’s 2020. JP Morgan claims combined indexed money, ETFs, proprietary trading and quant funds are 80% of assets. We see in our data every day that about 86% of volume comes from a motivation besides rational thought predicated on fundamental factors.

Proportional Response for IR people is a one-page fact sheet for execs with metrics, highlights, and expected Q&A.  The vast preparatory effort of 20 years ago is disproportionate to its impact on stock-performance now.

Proportional response for investors and public companies alike today should, rather than the intensive fundamental work of years past, now incorporate quantitative data science on market structure.

IR people, don’t report during options-expirations. You give traders a chance to drive brief and large changes to options prices. Those moves obscure your message and confuse investors (and cause execs to incorrectly blame IR for blowing the message).

Here’s your data science: Know your daily short-volume trends and what behaviors are corresponding to it, and how those trends compare to previous quarters. Know your market-structure Sentiment, your volatility trends, the percentages of your volume driven by Active and Passive Investment and how these compare to past periods.

Put these data in another fact sheet for your executive team and board.  Provide guidance on how price may move that reflects different motivations besides story (we have a model that does it instantly).

Measure the same data right after results and again a week and a month later. What changed? If you delivered a growth message, did growth money respond? That’s quantitatively measurable. How long before market structure metrics mean-reverted?

Investors, data science on market structure isn’t another way to invest. It’s core to predicting how prices will behave because it reflects the demographics driving supply and demand.

There are just a thousand stocks behind 95% of market cap. You won’t beat the market by owning something somebody else doesn’t. You’ll beat it by selling Overbought stocks and buying Oversold ones.  Not by buying accelerating earnings, or whatever.

The stock market today reflects broad-based mean-reversion interspersed with divergences. RenTec solved the market, we’re led to conclude, by identifying these patterns.  The proportional response for the rest of us is to learn patterns too.

Hummingbird Wings

I recall reading in high school that the military’s then new jet, the FA-18 Hornet, would fall out of the sky if not for computers.

Could be that’s exaggerated but the jet’s designers pushed the wings forward, creating the probability of continual minute turbulence events too frequent for human responses.  Why do that? Because it made the plane vastly nimbler in supersonic flight.

You just had to keep the computers on or the craft would go cartwheeling to earth.

As we wrap a remarkable year for stocks in a market too fast for humans and full of trading wings whipping fleeting instances of turbulence, we’re in a curious state where the machines are keeping us all airborne.

I don’t mean the market should be lower.  Valuations are stretched but not perverse. The economy is humming and the job market is great guns. And while the industrial sector might be spongy, the winds in the main blow fair on the fruited plain.

So why any unease about stocks, a sense the market is like an FA-18 Hornet, where you hope the computers keep going (ironic, right)?

It’s not just a feeling.  We at ModernIR as you longtime readers know are not touchy-feely about data. We’re quantitative analysts. No emotion, just math.  Data show continual tweaking of ailerons abounds.

You see it in fund flows. The WSJ wrote over the weekend that $135 billion has been pulled from US equities this year. Against overall appreciation, it’s not a big number. But the point is the market rose on outflows.

And corporate earnings peaked in real terms in 2014, according to data compiled by quantitative fund manager Julex Capital. We’ve got standouts crushing it, sure.  But if earnings drive stocks, there’s a disconnect.

I’m reading the new book on Jim Simons, the “man who solved the market,” says author and WSJ reporter Greg Zuckerman. Simons founded Renaissance Technologies, which by Zuckerman’s calculations (there’s no public data) has made more than $100 billion the past three decades investing in stocks. Nobody touches that track record.

It’s a riveting book, and well-written, and rich with mathematical anecdotes and funny reflections on Simons’s intellectually peripatetic life.

Renaissance is not a stock-picking investment firm. It’s a quant shop. Its guys and gals good at solving equations with no acumen at business or income statements proved better at investing than the rest.

It’s then no baseless alchemy to propose that math lies at the heart of the stock market.

And son of a gun.

There’s just one kind of money that increased the past year.  Exchange Traded Funds (ETFs). This currency substituting for stocks is $224 billion higher than a year ago and about a trillion dollars greater the past three years.  As we learned from Milton Friedman and currency markets, more money chasing the same goods lifts prices.

Stocks declined in 2018, yet ETF shares increased by $311 billion, more than this year.  In 2017, ETF shares increased by $471 billion.

Behind those numbers is a phantasmagorical melee of ETF creations and redemptions, the ailerons keeping the market’s flight level through the turbulent minutia flying by.

I’ve explained it numerous times, so apologies to those tiring of redundancy. But ETFs are substitutes for stocks.  Brokers take a pile of stocks and give it to Blackrock, which authorizes the brokers to create and sell to the public a bunch of ETF shares valued the same as the pile of stocks.

If you sell ETF shares, the reverse happens – a broker buys the ETF shares and gives them to Blackrock in trade for some stocks of equal value.

This differential equation of continuous and variable motion doesn’t count as fund-turnover. But it’s massive – $3.2 trillion through October this year and $10.7 trillion, or a third of the market’s total value, the past three years.

Why the heck are there trillions of ETF transactions not counted as fund flows? Because our fly-by-wire stock market is dependent on this continuous thrum for stable harmonics.

That’s the hummingbird wings, the Butterfly Effect, for stocks.

We can see it.  In July a seismic ripple in behavioral patterns said the market could tumble. It did. Dec 3-5, a temblor passed through the movement of money behind prices. The market faltered.

If the ETF hive goes silent, we’ll cartwheel.  It won’t be recession, earnings, fundamentals, tariffs, Trump tweets, blah blah.  It will be whatever causes the computers to shut off for a moment.  It’s an infinitesimal thing.  But it’s why we watch with machines every day.  And one day, like a volcano in New Zealand, it’ll be there in the data.

Jim Simons proved the math is the money. It’s unstable. And that’s why, investor-relations pros and investors, market structure matters.