US Finance System
Hyperinflation Caused "Transaction Processing Failure"
Systemic Risk Assessment
Where the vast bulk of today’s money is not physical, but
electronic, however, chances of adapting to Hyperinflation here
are virtually nil.
In terms of hyperinflation, there have been a variety of
definitions used over time. The circumstance envisioned ahead is
not one of double- or triple-digit annual inflation, but more
along the lines of seven- to 10-digit inflation seen in other
circumstances during the last century. Under such circumstances,
the currency in question becomes worthless, as seen in Germany
(Wiemar Republic) in the early 1920s, in Hungary after World War
II and in the dismembered Yugoslavia of the early 1990s.
Where the US Federal Reserve may hold roughly $210 billion
in currency outside of $50 billion in commercial bank vault
cash, the bulk of roughly $780 billion in currency outside the
banks is not in the United States. Back in 2000, the Fed estimated
that 50% to 70% of U.S. dollar cash existent was outside
the US. That number is higher today, with perhaps as little
as $200 billion in physical cash in circulation in the United
States. No matter how you run the numbers, there is not enough
cash available for a US economy in a hyperinflation mode.
Think of the time, work and effort that went into preparing
computer systems for Y2K, or even problems with the recent early
shift to daylight savings time. Systems would have to be adjusted
for variable, rather than fixed pricing, credit card lines would
need to be expanded daily, the number of digits used in tallying
dollar-denominated transactions would need to be expanded sharply.
It is understood that a number of businesses have
accounting software that can handle any number of digits, but
probably most of the US (and Canadian or NAFTA "banking
infrastructure" in general) is not ready.
Before we go further, let’s be clear about what a hyperinflation
really means in practical, every day terms
- Imagine taking every long term contract in your file
cabinet – your mortgage, auto loan, student loan, insurance
policy, health care insurance, and so on – and ripping them
up. There is no insurance or credit in a hyperinflation. All
transactions are cash or barter.
- Imagine an ongoing public panic into non-paper
assets. In the early stages of a hyperinflation, the most
efficient inflation hedges, due to their compact size and
liquidity –- precious metals -- disappear in a few weeks. At
extremes of hyperinflation, over 1000% per year, hoarding
becomes absurd, with items of seemingly little value used as
stores of value, such as copper plumbing fittings and brass
- Anything made of copper, brass, lead, aluminium that
is not either nailed down or guarded is stolen and used as a
substitute for cash.
- Imagine society breaking down. Money based
relationships disintegrate. As the purchasing power of
everyone’s savings is gone, everyone becomes completely
dependent for cash for day-to-day survival from income earned
from whatever they can do or sell.
- Sensible employers will index salaries to inflation.
Yet this will not stop the economy from coming to a standstill
with output collapsing. The unemployment rate will probably
- Without tax revenue, state and local governments are
crippled, and the police are as desperate as everyone else.
Crime flourishes. (A friend recently back from Argentina told
me that he was repeatedly stopped by police on the street and
asked for money.)
On the international scene, for any country that uses the US
dollar as a nominal anchor to stabilize its own currency: US
dollar hyperinflation will mean almost certain hyperinflation.
Countries will quickly delink their currency's exchange rate from
the dollar before that happens. Countries that use the dollar for
international trade will drop the dollar.
Important hardware and
Floating-point numbers are typically packed into a computer datum
as the sign bit, the exponent field, and the significand
(mantissa), from left to right.
For the IEEE 754 binary formats
they are apportioned as follows
||total buts used
|Half (IEEE 754r)
Coprocessor theoretical model
||science oriented programs,
||has never really been used
in hardware or software
|used in science and global
finance, unpredictable and unstandardized
While the exponent can be positive or negative, in binary
formats it is stored as an unsigned number that has a fixed
"bias" added to it. Values of all 0s and all 1s in this field
are reserved for special treatment. Therefore the legal exponent
range for normalized numbers is [−126, 127] for single
precision, [−1022, 1023] for double, or [−16382, 16383] for
As described earlier, when a binary number is normalized the
leftmost bit of the significand is known to be 1. In the IEEE
binary interchange formats that bit is not actually stored in
the computer datum. It is called the "hidden" or "implicit" bit.
Because of this, single precision format actually has a
significand with 24 bits of precision, double precision format
has 53, and quad has 113.
Arbitrary-precision arithmetic, also called bignum arithmetic, is
a technique whereby computer programs perform calculations on
integers or rational numbers (including floating-point numbers)
with an arbitrary number of digits of precision, typically limited
only by the available memory of the host system. Using many digits
of precision, as opposed to the approximately 6–16 decimal digits
available in most hardware arithmetic, is important for a number
of applications as described below; the most widespread usage is
probably for cryptography used in every modern web browser.
It is often implemented by storing a number as a variable-length
array of digits in some base such as 10 or 10000 or 256 or 65536,
etc., in contrast to most computer arithmetic which uses a fixed
number of bits in binary related to the size of the processor
registers. Numbers can be stored in a fixed-point format, or in a
floating-point format as a significand multiplied by an arbitrary
exponent. However, since division almost immediately introduces
infinitely repeating sequences of digits (such as 4/7 in decimal),
should this possibility arise then either the representation would
be truncated at some satisfactory size or else rational numbers
would be used: a large integer for the numerator and for the
denominator, with the greatest common divisor divided out.
Unfortunately, arithmetic with rational numbers can become
unwieldy very swiftly: 1/99 - 1/100 = 1/9900, and if 1/101 is then
added the result is 10001/999900.
An early widespread implementation was available via the IBM 1620
of 1959-1970 which was a decimal-digit machine that despite using
discrete transistors had hardware that performed integer or
floating-point arithmetic (via lookup tables) on digit strings of
a length that could be from two to whatever memory was available,
though the mantissa of floating-point numbers was restricted to
100 digits or less and the exponent of floating-point numbers was
restricted to two digits only: the largest memory supplied offered
sixty thousand digits. Compilers for the IBM 1620 (Fortran),
however, settled on some fixed size (which could be specified on a
control card if the default was not satisfactory), such as ten
digits. IBM's first business computer, the IBM 702, which was a
vacuum tube machine, implemented integer arithmetic entirely in
hardware on digit strings of any length from one to 511 digits.
The earliest widespread software implementation of arbitrary
precision arithmetic was probably that in Maclisp. Later, around
1980, the VAX/VMS and VM/CMS operating systems offered bignum
facilities as a collection of string functions in the one case and
in the EXEC 2 and REXX languages in the other. Today,
arbitrary-precision libraries are available for most modern
programming languages (see below). Almost all computer algebra
systems implement arbitrary-precision arithmetic.
Arbitrary-precision arithmetic is sometimes called
infinite-precision arithmetic, which is something of a misnomer:
the number of digits of precision always remains finite (and is
bounded in practice), although it can grow very large. Aside from
the question of the total storage available, the variables used by
the software to index the digit strings are themselves limited in
size. Arbitrary-precision arithmetic should not be confused with
symbolic computation, as provided by computer algebra systems. The
latter represent numbers by symbolic expressions such as πsin(3),
or even by computer programs, and in this way can symbolically
represent any computable number (limited by available memory).
Numeric results can still only be provided to arbitrary (finite)
precision in general, however, by evaluating the symbolic
expression using arbitrary-precision arithmetic.
Reach of computer numbers.
1 = 1!
2 = 2!
6 = 3!
24 = 4!
120 = 5! 8-bit unsigned
720 = 6!
5040 = 7!
40320 = 8! 16-bit unsigned (devices using this math will be the first to fail)
362880 = 9!
3628800 = 10!
39916800 = 11!
479001600 = 12! 32-bit unsigned (failures will take longer, but it will be universal)
6227020800 = 13!
87178291200 = 14!
1307674368000 = 15!
20922789888000 = 16!
355687428096000 = 17!
6402373705728000 = 18!
121645100408832000 = 19!
2432902008176640000 = 20! 64-bit unsigned (last hardware and software to fail)
51090942171709440000 = 21!
1124000727777607680000 = 22!
25852016738884976640000 = 23!
620448401733239439360000 = 24!
15511210043330985984000000 = 25!
403291461126605635584000000 = 26!
10888869450418352160768000000 = 27!
304888344611713860501504000000 = 28!
8841761993739701954543616000000 = 29!
265252859812191058636308480000000 = 30!
8222838654177922817725562880000000 = 31!
263130836933693530167218012160000000 = 32!
8683317618811886495518194401280000000 = 33!
295232799039604140847618609643520000000 = 34! 128-bit unsigned (unimplemented)
10333147966386144929666651337523200000000 = 35!
Known probable risk factors (unweighted)
- lack of software updatability
- lack of hardware updatability
- lack of transaction processing product design object
orientation, albeit this is subject to interpretation
- use of coins
- producer or maintainer bankruptcy, software or hardware
- supply chain unreliability, that is to say transaction
processing devices in remote areas will not be able to adapt
as quickly or even not at all
Social modelling assumptions for failure, that would contribute to
List of classes computer money transfer systems in the USA
that will fail, with general rankings in terms of
probabilistic fitness for sustained US hyperinflation.
Highest on the list, predicted most immunity; lowest on the list
subject to near immediate failure.
- Handwritten cheques, they are essentially custom "single use"
currency issues: scientific notation can save the day.
- FOREX trading systems (both consumer and finance sector,
cause: Yen and use of FOREX software in the
developing world) -- if an only if there is a continuous audit
process in effect and debugging and codebase redesign possible
out of country
- Most online shopping cart systems that have no centralized
code management or dynamically up-datable API parameters or
- Most accounting and tax software that is specific to the US
economy, where no Yen / etc ... versions exist or where no FOREX
orientation exists in the program
- Cash registers at US fast food chains
- Cash registers at US supermarket chains, universally said to
- ABMs or ATMs as they are called in the US -- unless the
computer can get its software / firmware updated nightly, and
even fit ABMs will fail if the overall software architecture and
codebase is iffy or sub-par for general global use
- Parking meters and parking systems, electronic EFT types
- Coin based vending machines of any kind from Washer / Dryers
to Cigarettes to who knows what. Coins become moot within the
1st year of hyperinflation as a general rule.
It has been posted to COMP.RISKS many times about
a number of gas stations having older gasoline pumps that
cannot register more than two digits’ worth of dollars in their
totals -or- more than $4.99 per gallon of gas.
From a practical standpoint, the electronic quasi-cashless
society of today also would shut down early in a hyperinflation.
Unfortunately, this circumstance rapidly would exacerbate any
ongoing economic collapse. With standard currency and electronic
payment systems either non-functional or randomly function or
malfunctioning ... it would not take too long for commerce to
quickly devolve into black markets for goods and services and
a barter system.
Unlike Zimbabwe, the United States does not have "widely
available (for circulation) backup reserve currency" [short of
full blown use the Canadian Dollar, or Mexican Peso] for
general use in place of an inflating domestic currency.
22 August 2008
20 September 2012 (minor fixes)