Beyond Faster (T+1) Trade Settlements: The Hidden Costs of Optimization
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Walk in the money for the rest of us. This is a personal financial on money, how IT works, how to invest IT and how to live without worrying about IT. I'm your host of David time. Today is episodes eighty. It's title beyond faster t plus one trade, the hidden costs of optimization beginning today in the us trades for stocks, corporate bonds, exchange trade funds, mutual funds and options.

We will settle in one day instead of two, and by setting, we mean that the exchange of dollars for the particular security will will clear, and the seller will receive the money they got, and the buyer will get the security they got. IT will be reflected in their account, S, C, C, commissioner gary gancy lor said. For everyday investors who sell their stock on a monday shorts, ending the settlement cycle will allow them to get their money on tuesday.

Shortening the settlement cycle also will help the markets, because time is money and time is risk. IT will make our market pluming more resilient, timely and orderly. Back in the late nineteen sixties, stocks and other securities took a week or more to settle.

We discussed this an episode to eighteen, because when you purchase a security, you received a stock certificate. And there was a paperwork crisis because trading volume went from three million stockmarket irs a day in one hundred and sixty, the twelve million in nineteen nineteen seventy. And the paperwork would get so backup.

They would have to shut down trading and take a day off so they could catch up with the work. They solve that problem by depositing all these stock certificates in a central depository known as the depository trust account. And then the stock certificates were held in the name of the brokers.

So instead of having to trade paper certificates, there is book keeping entries as trades are made. And IT dramatically increased th Epace o f i ts t rade s ettle. In nineteen ninety three, U.

S. Exchanges went to t plus three. So trades were settled in three days.

In twenty seventeen, trades started settling in two days. And now it's one day. This was some rules at the S. A. C. Put in place. And the reason comes out of what happened in twenty twenty and early twenty twenty one, with a lot of the meme stock trade, the volume got so high, many of those stocks trades happened on Robin hood.

These brokers have to post collateral for trades in case there are some type of trade fail or the broker fails, which they don't, but they to put up collateral and the volume got so high. And because they took two days to sell, Robin hood didn't have enough capital to put up his color or to settle the trade. And so they limited the ability of their customers to trade certain securities, which LED to a congressional stigmata.

And ultimately, the move by the S, C, C to shorten the settlement window to one day. In fact, it's not even one day in terms of twenty four hours, but with the market closing at four clock trade, affirmations need to take place by nine P. M.

So it's really a five hour window to settle these trades. The brokers and and other entities involved in trading are oh understandably worried about the transition, particularly because not every country is adopting t plus one. There are international exchanges that still have t plus two, which means that someone purchasing a security there doesn't necessarily have to put up the money right away yet.

If it's U. S. Security, the, the broker might have to come up with money to settle the trade even before they get the money from their customer.

Eventually, all countries will move to tea. Plus one, india is already there. Canada, mexico n argentina are moving to t plus one this month. U. K, in twenty twenty seven, european unions been slower to adopt IT.

Adam Watson, who is head of commercial products at B, N, Y, melon, said, the move to tip us one is the right thing to do. IT reduces counterparty risk, reduces the risk of failures, but he also points out we will see short term fails an increased funding cost. As the trading mechanism is more optimized, the transition will lead to glitches and failed trades.

And that sort of the concern with with this transition starts today, this is tuesday, may twenty eight, wednesday, the day this podcast to be released to be pretty important because we have the U. S. Holiday on monday. We'll see how many trades fail, whether there are unintended consequences.

A survey that I saw by coalition gr inch in April, may said that nine percent of cell side wall street firms thought that t plus one switch would go smoothly and said that thirty eight percent that a byline manager. So essentially asset managers are unprepared. We'll see. But the theme is faster trade settings, which means the system IT is more optimize, there is less slack, and will discuss some of the chAllenges with optimization in this episode.

Before we continue, let me pause and share some words for one of these weak sponsors, yahoo finance, if I want to see what's going on right now in the market, the top news stories, what the financial indexes are doing, I go to ahoo finance just there, could see the consumer confidence unexpectedly ly rebounded in the latest report, pulled up the article to read more about that. Could see what the S. N P is doing non us markets, oil, gold.

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Now why don't trade? Settle immediately. Tea plus zero. Apparently the the underlying plumbing isn't there yet. Even with the current system, some trades do fail and there needs to be time to reconcile. And if there's a chance of a of a trade fAiling, then we can get the tip zero. But there is a way to actually get to t plus zero.

It's toga ization using the blockchain to think we've covered in the past and and there are traditional investments out there on the black chain earlier this year, black rock and reduce the U. S. dollar.

Institutional digital liquidity fund goes by. B, U. I, D. L is an institutional fund.

As investors, we can invest, but to invest in this fine money is sent to the custodian to purchase shares, but those shares are recorded on the black chain, the syrian black chain, and so the actual shares are tokens on the a theory book chain. The the money is invested in U. S.

Treasury bond. It's a way for participants, institutional participants in the egypt market, instead of holding a stable coin, bacon hold shares of B, U, I, D, L and an interest on a token ize security. That's no this point.

There's four hundred million dollars or more invested in this fun, and another close to four hundred million dollars invested in a similar fund by Franklin templeton. Trades of these funds settle effectively immediately. Just need to be verified on the theory um network rf kubi is a board member at the association.

This is a switzerland based blockchain project, says there will come a point when the current technology set up is not going to work in terms of traditional settlements. The way is done now IT will move to the black chain because there is now this toko ize security invested in treasury bills and bonds earning yield. Participants in the crypto spaces are using that these build B U I D L tokens as collateral to facilitate other trades.

So that's what's going on in the trading front, t plus one settlement for traditional E, T, F bind stocks, some t plas zero settlement initially on the black chain with traditional securities. I thought about this in the context of a book I just finished by coco chrome title, the false promise of optimization. Chrome is an applied mathematician as a doctor from M.

I, T, and has worked an optimization except now SHE doesn't SHE does some consulting. He lives in a cabin on a remote island in the pacific northwest. I think it's one of the sand, one islands.

SHE talks about IT in her book, and he describes an optimization as a metaphor of how to organize the world. A traditional optimization function is a mathematical function, trying define the best solution to a problem. Given certain constraints in criteria, usually there's a goal.

The goal could be to minimize cost, or in the case of training, the goal could be to minimize the time he takes to settle trades by its definition. And optimization is a simplification of the world. IT flattens the world.

It's A A view of the world. In order to distill IT into a mathematical formula, optimization has been incredibly successful. Think about IT in agriculture.

Through optimization, productivity has increased as farmers have been able to work with Better optimize seeds to get greater yields. They're able to plant more efficiently through G, P, S enabled tractors. All of the elements of agriculture have been optimized to wear.

Between one thousand hundred and fifty thousand thousand seventy. The agriculture workforce fell by half, even though total production increased forty percent. And we've benefited from that because food, as of twenty twenty costs, about a third of what I did one hundred years earlier, cheaper, is more abundant because of optimization.

But there are trained s crime writing a book. Optimization flattens s the complexity of agriculture into a formula. IT turns a field of beat into a blank canvas to be engineered. The result is a world that may look familiar to one several generations ago. The flat plane is still there, the barns, the roads, but much the property lines that once have been a families history have faded.

Writing over with the record of crop fields, the fields look flatter, spare, hello, although they're producing more beats than never, what are some of the downside risks to optimization? This simplification is metafor as the optimizes focus on maximizing something or minimizing something within the given constraints. There's three that chrome mentions there, slack place and scale slack or abundancy.

As things are optimize, there's less slack. Think about in terms of t plus one trade settlement, if there's less time slack, the potential for trade fails is higher, at least in the transition, and ability to reconcile problems is more chAllenging because there's just less time slack in the system come rights. The more tightly rod our systems get, the more razor than our margins, the more fragile we become.

Over optimization can lead to fragile ity. Think about flying. There's a storm.

We just had a memorable day weekend in the U. S. As our headlines about all these delays.

And because of storms, the system of travel, the airplane is incredibly optimized. There's just not as much slack. And as result, when there's a disruption, IT cascades through the system.

Second chAllenge with optimization is place what chrome describes a specific knowledge. There is a lack of diversity. Things become amazing ous.

It's all the same in the interest of optimization. There's less localization, more globalization. Things are more connected. SHE mentioned in the farm belt, you lose the richness of small town community as these towns are hold out because there's just less farmworkers.

There's less of A A sense of place as you travel because many cities have the same retail storm because the entire retail system has been optimized to lower cost and maximize profits. And we've seen that keep growing faster and faster and faster episodes on shine and timo. Well, now if you want to buy something, you order IT on one of those sites.

A manufacturing in china makes IT and send IT to your home directly. Superfast product cycle. There is cost to that, but that's the optimization.

In one thing that get lost is a sense of place, the ability to to go to a store in a local town and see something different, something unique. Now we still have art, but we can lose our sense of place with optimization. And if there's less localization, there's a greater risk of contagion as more things are connected.

Think about of the pandemic, greater connectivity, LED to the widespread of covin. A third chAllenge with optimization is what chrome describes as a sense of scale, the connection and understanding between how we, as a part, fit into the whole things get to an even greater scale. Farms get bigger, companies get bigger, the transportation system gets bigger.

And we can lose meaning because everything seems so optimized and we lose our sense of place in the world. One of the the threats that effectively is an optimization function is A I I have conversations with ChatGPT all the time in preparing for this podcast or really learning anything. I like the blank screen of ChatGPT。 There's no ad.

I can ask a question, I can get an answer. I can assess whether that seems correct or not. I can do follow up.

IT remembers the context. It's like talking to a person, except it's not a person. It's an optimization function.

Function is to generate, and this is according to chat. G, T, P is to generate the most relevant, accurate and cohere response to a given prompt. The goal is the maximized quality of those responses based done.

Relevance, accuracy, coherence and IT does IT through tokens. These tokens are word or sub words that a ciller really and large language models of actually are predicting what token should follow next. And the largest language models have been trained on massive data sets to be Better at predicting the right token given the contextual preventers.

Now there's some constraint. This grammar, there's accuracy is important. There is some ethical guidelines, but it's an optimization process.

And they're trying to improve these large language models by having the tokens not just represent a sub word or a small piece, but bigger chunks maybe to paragraph or sentence or multiple words in order to improve the accuracy and the the relevantly of the end. That's an optimization and IT can feel threatening. Before we continue, let me pause and share some words from this week.

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David, that's M O N A R C H M O N E Y dot com. Lh, David, for your extended thirty day free trial. There was a academic paper released this month by three academics with the university of chicago. The papers titled financial statement analysis with large language models, they used ChatGPT to predict earnings for companies, and they just uploaded the financial statements and asked IT to predict whether the earnings will increase in the next year. Just based on those financial statement, just did a simple prompt.

Its accuracy was about the same as human analyst in their predictions, but when they did what they call a chain of thought prompt, essentially asking ChatGPT to pretend there a research journalist predicting whether earnings will increase for these companies based on the financial statements. Turns out when they asked me to do human reasoning, its accuracy was sixty percent, about eight percent higher than humans, which got earnings predictions right. About fifty two percent.

Sixty percent is Better. But IT shows you the chAllenge in predicting earnings. But if my job is, as a research journalist, forecasting earnings, i'm concerned now the academics point out that human analysts have things beyond just financial statements.

They can pull from a broader information set, soft data quality native assessment, something that a large language model, at least now can do as well at. And so by an it's gonna a combination. And hopefully using a large language model like ChatGPT will help analysts make Better predictions.

We use analysts predictions and asset camp. We use them in generating expected returns for different areas of the stock market. We use historical earnings, will use forecasts the earnings by short term and long term. And so we want those earnings to be accurate so that we can assess reasonable returns for the stock market.

We also use IT to figure out whether the consensus is overly bullish or not or overly barry shed, when IT comes to earnings, that's a new type of optimization, large language models and IT is an opportunity, but I can feel like a threat in her book, coco crime compares optimization with capitalism. He points out that optimization is asked to its context, the mathematical formula focusing on optimizing some area. Where is capitalism? SHE says it's a philosophy.

IT favors profitability as a measure of success, but optimization is topped down. The formula is a simplification. Where is capitalism is bottom up with many, many inputs, many, many companies, individuals seeking to create something, a value that people want.

And it's not easy optimization, and sometimes is easy because it's a simplification. The mathematical function, figuring out what people want to buy and making people aware of IT to tell their friends really chAllenging. We're seeing IT in the podcast space.

We is so appreciate. And I ask you please share money for the rest of us with your friends because the algorithms don't recommend IT like I used to, because there are so many more ad cast word. A mouth is so much more effective if someone says, hey, a really cool podcast I like, you should take a listen.

But capitalism, in some ways, running a business is more chAllenging than optimizing because IT is bottom. And we don't know. There's a lot of uncertainty related to IT, which is why optimization consumed simpler because that, that uncertainty in some ways is eliminated because of the simplification that comes with optimization.

One of the other chAllenges with optimization when IT comes to scale in place is there's a lacked in effect because optimization tends to ignore the variables that aren't included in the formula. Once something is optimize, say, our system of agriculture, big egg, bigger farms, G M O seeds, it's very, very difficult to the optimize to go backwards in time because of the locking. The metaphor of optimization is showing ruptures precisely because of the paradox at its core, the more we optimize, the less were able to do and see things any other way.

IT becomes the effect way of approaching the world. And much of a book is about trying to figure out how do we weigh the baLance. There's a desire sometimes to just go off and live on a remote island like he does and avoid optimization altogether.

But he admits SHE can't do that either. Amazon still delivers to her remote island in today a highly optimized delivery system. We can just go backwards, but there are these downsides to optimization.

Murban king and his book the end of alchemy points out that as as humans, we don't optimize. We cope because of the uncertainty. And as a result, we do is known as satisfying a term that herbert Simon developed, an american economist psychologist.

Satisfying means because we don't have all the information, because we don't have to necessarily even the mental capacity to optimize. We choose good enough solutions because of the limits to our information. We use rules of thun horst tics.

That's how we cope, tell we cope in investing, not knowing what's going to happen. Even A I doesn't know exactly whether earnings for a given company will increase, why we invest in asset classes. We aggregate companies stocks into an index fund or etf.

And because were able to aggregate the data with some of the the positive things are all set by the negative. And then we focus on the satisfying answer, the underlying drivers, the income, the cash low reason, expectations for that cash for growth and looking at what investors are paying for that cash flow. In the case of stocks, the Price earnings to issue is that greater than average or less than average? Try to understand the context behind IT.

That's what we do at acid camp and in our monthly weapon are trying to understand the underlying drivers of the stock market. We do IT another asset classes on money for the rest of plus. We don't know the answer, but we know where we are today and what the drivers are.

And then we come up with a satisfying answer in terms of our allocation that's different than modern portfolio theory, the optimization that I grew up with as an investor professional investor adviser at all these inputs, expected return one number, volatility one number, maximizing the return for a given level of risk. Garbage, jan, garbage job. Now ranges are much more important, being able to stress test, use different options to come up with A A reasonable range of returns.

That's how I approach investing now. It's a satisfying good enough approach, is not an optimized approach because capitalism, bottom up is too complex to come down to a simple formula. I'm grateful that we now have t plus one settlement looking forward to t plus zero, but that's just one little aspect of finance.

Most of the world can be optimized. The world we have to cope with. We often have to step back and not buy in to the opto.

My system, I was that whole foods the other day aren't amazon, don't hold foods, says I can pay by scanning my palm. Not a chance. We don't have a lexis by amazon in our house listening to us.

I don't use theory. But you don't have to buy into every optimization as company seek to optimize the profit. We can step back.

We need to step back. We need to take breaks. Cakewalks recognize ChatGPT isn't a person. IT feels like a connection as i'm going back and forth, but it's not it's a statistical optimization that's different than having dinner with a friend, hanging out with family, being in nature, telling a story, reading a novel, trusting someone, letting them trust you. That is real life and it's not optimized.

And for that, i'm glad I love the unpredictably of the world that makes IT exciting, interesting, sometimes scary. But i'm glad everything is an optimized, because that would be a boring world indeed. That episode four eighty, thanks for listening.

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