I've seen people working in finance or interested in finance on this board, so I thought I may ask.
According to you, what are some open problems in finance, old or new? I am especially interested in quantitative finance.
I would ultimately like to come up with a list of them, a little bit like we do in mathematics, physics and computer science.
Thanks and have a great day!
These models are used to determine the probability of an account/customer/contagion risk group defaulting (aka PD) and the loss incurred, given a default (LGD).
The current models require a lot of historical data to train them, and need to incorporate economic cycle factors.
There are some vendors in this space, but their products are very dated, expensive and leave a lot to be desired. Also the products really provide a platform for an actuarial team to build upon, rather than having an out of the box solution (which is probably desirable in the banking space)
List of Unsolved Problems in Econ:
https://en.wikipedia.org/wiki/List_of_unsolved_problems_in_e...
What happens when central bankers run out of ammo and realize monetary policy may not be an ideal path to fiscal stimulus? Or having the bright idea of devaluing your currency to depreciate your outstanding liabilities results in a mutually assured destruction scenario when every sovereign on earth implements the same idea simultaneously? And when "too-big-to-fail" entities amass derivative exposure that is 100X global GDP does it become time to panic yet?
But still its innovations like ZeroCoin and SmartContracts that give one hope that out of the rubble, creative solutions will arise. As long as they are grounded in economic reality and not fantasy, humanity will abide...
One thing that I think is missing from that list is how to factor in technology into economic models or measurements like GDP.
Right now this dark horse which in my view have the biggest single impact on our world is mostly left out as an externality which if you think about it is not just absurd but straight out irresponsible.
Politicians listen to economists and their models and as long as it's kept out of those models they can't react politically to it. And thus technology will keep moving faster than legislation.
But pinning risk down "mathematically" is kind of tricky. There are several proxies for risk under modern portfolio theory, including variance, standard deviation, shortfall, half-normal variance. Why are there so many different measures? If analytical tractability was not a concern, what should risk models look like?
2. Multi-horizon portfolio optimization. Portfolios are typically optimized one time step (horizon) into the future. However, if one wishes to optimally allocate a portfolio with extremely long-term investment periods (think Berkshire), one needs to subdivide that period into multiple horizons and optimize over these together. This is computationally expensive - is there a way to do this efficiently?
#2 has already been solved: One formulation is here: https://stanford.edu/~boyd/papers/pdf/dyn_port_opt.pdf There are optimizers out there already on the market with these capabilities.
2: My biggest concern here is that the data isn't really reliable in extremely long-term investments, MPT mostly runs on historical data, if you're wanting to pick stocks to invest in 10 years from now on today's data, it's like investing in today's stocks on data from 1996-2006, which is pretty silly. Such very long-term models are just not very feasible. The weather is a great example, I think. We're pretty good at calculating patterns an hour or a day into the future, two weeks into the future is extremely hard. There's just too many small things that can explode into significant changes.
You mentioned Berkshire as an example, they're pretty much the opposite of modern portfolio theory. They look first and foremost at fundamental business analysis, i.e., is it a good business, is there a solid management etc... MPT disregards virtually all of that.
Every model has assumptions, MPT relies pretty heavily on the notion that 'all knowledge is priced in', so that analysing businesses and building portfolios like Berkshire is not going to get you anywhere. Rather, you're left with looking at historical data and building a portfolio like that, assuming that this data includes all information in the market, because it's price data and everything is priced in, so it gives the most accurate reflection of the market. Lots of counterexamples show this isn't the case, it's still a nice theory but it does better in the short (or medium) than the long term imo, and not because it's computationally expensive.
Obviously a standard would be nice but in practice I'm sure each institution would come up with their own or embrace and extend the standard. e.g. FIX with trading.
And of course https://www.quandl.com/
1) "Finance" is extremely fluid because of the speed with with transactions are conducted...(e.g., the stock market)...during the course of a day's trading market reports are given minute by minute, but the most useful "summary" of "performance" is often available only at the end of the day when the market closes...
2) Entities derive a capitalistic advantage by protecting their own data, until, and unless, they're given sufficient incentive to share it...
To me this implies that a system sufficiently complicated enough to provide "meaningful" data captures might have to be nearly as complicated as the field of finance itself...the best we seem to be able to do just now is provide snapshots--AKA, the "leading indicators", etc...
4) There are many (MANY!) financial standards and formats. But at the end of the day, a payment is a payment. There are only so many different kinds of financial instruments and transactions.
There's a lot of noise, but the signal is still there. And solutions exist to make sense of it all.
The "signal" is there, I agree...I used the word "snapshot" and I'm guessing that we mean something similar...
Global finance is a moving target...gleaned information is useful one minute, sometimes meaningless an hour later...
I could consider cryptocurrency as the ultimate solution but online if everywhere its being used in equal importance and liquidity. For more traditional money, banks are squeezing fees & spreads out of regular people. Companies like TransferWise are trying to resolve some of these problems but still they rely on the existing banking system to move the funds around.
So there you go - open problem!
The most telling one, for me personally, is the human condition of the bottom 20% of the residents.
This is true of GDP as well, since GDP only includes final goods. I.e. if a farmer produces wheat, and the wheat is then used to produce bread, the farmer -> baker transaction is excluded from GDP. Only the baker -> consumer transaction counts towards GDP.
If you want to try and measure utility, your metric should be based on consumption - e.g. mean(log(after tax consumption)). Income isn't utility, it's only potential utility.
If we used income, your metric would unfairly penalize volatile income. I.e., a person with a stable income of $50k/year would be considered 70% better than a person who earns $100k then $0k (saving $50k in the first year and spending it in the second while having an identical lifestyle.
The distinction between consumption and income is not significant for a large fraction of the population, and if you are going to track just one number, it really shouldn't be consumption. If you do that, you have no hope of tracking changes in social structures or inequality or wealth accumulation. You would have to track wealth or income too.
Addressing your concern over volatile income is not that important and could compromise the usefulness of the metric. If you propose using GDP or any other linear function instead (rather a logarithm or power-law) then you cannot approximate utility and your number will be insensitive to changes in inequality. If incomes go up for the bottom half by 10%, then GDP would not change by much, though many would be better off. Income taxes are already calculated annually to smooth out these income fluctuations for seasonal workers.
But you wanted to measure 'average "utility"', not "social structures". Utility comes from consumption, not income. You are right that tracking consumption would fail to be a proxy for income inequality (as you now seem to want it to be) because consumption inequality is vastly lower than income inequality.
At this point, your metric sounds less like an improvement on GDP, and more like just some other random thing you want to track.
That said, you criticized log(consumption) above because it doesn't measure "social structures" and "inequality". Those things are pretty explicitly not how the economy is serving the population.
Income is easily measured for individuals, and aggregate consumption is easily measured by merchants. This is why we have a progressive income tax and not progressive consumption taxes. It could be done, it is just more difficult.
You can repeat as often as you wish that "inequality" is not relevant, but you are wrong. Utility is increased more if $1 is earned/spent by a poor person than a rich person, ipso facto inequality is bad for utility, all else being equal. My reference to the economy serving the population, is just a reference to utility, as opposed to any other linear measure such as GDP.
Personally, I cringe when I hear talking heads correlating then Fibonacci number with the stock market.
And I've come to realize, if Jim Crammer recommends a stock, don't buy it. I would like to know which professional out there has the best track record in stock speculation. It seems like something that we could accurately study, and publish the data?
I don't have the money to speculate in the stock market. It just seems like it's as bad as gambling at this point in history. It interests me though. If I had money it would go to realestate speculation. I'm so wrong on my stock picks, I've though about contrarian investing. Supposedly, there are such people?
Just like everybody else, even most professional fund managers, although they wouldn't like to admit it.
A good start would be a readable and round-trippable format that Excel documents can be saved as
What happened to CSV?
Edit: Maybe you want to be able to save the equations etc?
[1]https://en.m.wikipedia.org/wiki/Texas_Instruments_Business_A...
There is no consistent mathematical standard of measurement by which money is created. Instead, the monetary value of some good or service used as capital for a loan is largely up to the arbitrary appraisal of the bank.
You make money first by creating the tangible / intangible artifacts of that exchange, like currency, systems of accounting, and such. You then get other people to use the system to exchange goods and services.
This typically requires a government, but other entities have made money in the past, and even today. Bitcoin satisfies all the criteria of money.
The practice of fractional-reserve banking is another example of money creation. Most banks will lend out more money than they have access to in deposits, as a relatively safe form of leverage.
This has the effect of slightly expanding how much money is available to the economy, aggregated over all the banks and loans being made by those banks, the expansion is significant.
Things like video game currencies also satisfy all the criteria of money, though the things you can buy with them are limited, sometimes you can trade them for other currencies.
So there's lots of ways to make money.
In fact, I suspect there's a Superpac somewhere that would fund research showing the net effect it might have. Or some organization that would want to know what that does to algorithmic trading.
I'm guessing though, the likelihood of a bill like that making it all the way is pretty low.
http://qed.econ.queensu.ca/pub/faculty/milne/322/IIROC_FeeCh...
http://www.publications.gc.ca/collections/Collection-R/LoPBd...
The net result is that institutional investors (Goldman) won, retail investors (grandma) lost and spreads (the cost of trading) increased 9%.
I haven't been paying close attention, but I thought Bernie was contrasting himself against Hillary who is supposedly in the pockets of banks. That image doesn't really fit with such a policy.
"Has proposed a financial transaction tax which will reduce risky and unproductive high-speed trading and other forms of Wall Street speculation; proceeds would be used to provide debt-free public college education."[1]
[1]https://berniesanders.com/issues/reforming-wall-street/
I'm trying to avoid getting into a debate about whether it's a good idea. If you think, though, it has some chance of happening...it does specifically become an "Open Problem in Quantitative Finance", which is what the OP is asking for.
The "open problem" I guess will be improving the existing tax avoidance software for traders?
[1] High speed trading is extremely non-risky. Look at graphs of the most extreme HFT incidents: https://www.chrisstucchio.com/blog/2012/flash_crash_flash_in...
don't big traders use HFT as a market advantage over retail?
One description of the HFT (from the always thought provoking Matt Levine): "It's an incremental efficiency improvement, with some opportunity for gamesmanship, that overall allocates some money out of the pockets of banks and hedge-fund managers and into the pockets of exchanges and HFT technologists."
That's basically correct. And as a bonus, the small retail investor buying twenty shares of Apple now gets his shares very slightly cheaper, which is kind of nice I suppose. (Unless you work for a large Wall Street firm who's revenue depends on retail investors paying high margins. But in that case my sympathy is quite limited.)
Concretely speaking, HFTs price discriminate when providing liquidity. Grandma gets a good price to sell her 2 lots of GOOG, but Bill Ackman and George Soros need to pay more to sell 20000 lots.
The same problems will not be necessarily manifested if the law is applied in the US, especially if Canada has similar laws. However, the points of the first link seem to hold.
The fact that one can shift trading in cross listed symbols to other venues doesn't mean that supply&demand also doesn't reduce market making (thereby increasing costs). In fact, Bernie Sanders explicitly hopes the tax will do exactly that.