Back

Well, sort of. As some of you already know, I was in transition between two jobs this summer. I took some time off and travelled for several weeks. I drove close to 2,000 miles and saw some great mountainous, green, sunny, empty and desert landscapes as well as monuments, in Europe and America; I disconnected from the financial world and relaxed – which is something I really needed. Now I’m back and started my new job. I’m pretty excited but this also will have impacts on my other activities.

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It is unclear what this is going to mean for this blog, as well as for my contributions to the Cato Institute’s Alt-m website. It’s going to take another couple of months before things get clearer. Hopefully I will be able to resume my Alt-m contributions.

What I believe is that, due to the nature of my new job, I will have less time to work on blog posts on weekdays. Therefore I am unlikely to publish more than a single blog post a week from now on; perhaps fewer. I have a few in the pipeline; so keep posted.

Oh and thank you again for your support over those past three years!

Why the money multiplier remains so low

George Selgin’s latest monetary policy primer was a very good explanation of the money multiplier in fractional reserve banking systems. He also suggested that a number of factors may be affecting the current surprisingly low level of the multiplier; a fact that prompted a number of endogenous money theorists to (wrongly) assert that the multiplier was ‘dead’.

In this post, I wish to elaborate on the reasons behind the low multiplier. And those reasons are, in my view, related to banking mechanics and regulatory dynamics.

Let’s first start with a little bit of history to put things in perspective. Some time ago, and following one of my blog posts on the topic, Levi Russel from the Farmer Hayek blog – who is much better than I am at manipulating FRED data – kindly sent me the following chart representing the M2 multiplier (‘MM’) since 1920:

IMG_20160715_175807

As you can see, the MM also experienced a huge fall during the Great Depression. It then took about forty years for the MM to progressively get back to its pre-Depression level.

Independently of regulatory frameworks, there is a simple underlying reason behind this long recovery time: banking mechanics. As corporations, banks are subject to operating constraints that limit the short run supply of credit. Banks employ a number of bankers, analysts, risk experts and so forth that are in limited numbers and already working full time to extend loans to creditworthy customers in adequacy with the bank’s risk appetite. The client onboarding process, the analysis of his risk, as well as the negotiations of legal agreements, aren’t instantaneous. The funding process itself isn’t either: despite what endogenous money experts assert, extending new loans still require looking for additional non- central bank funding before or shortly after putting the credit line in place.

At any point in time, it is likely that banks are close to the microeconomic equilibrium ideal of having marginal revenues equal to the marginal economic costs of employing staff and retaining adequate levels of capital and liquidity, and that its managers decided not to extend credit further on purpose: additional revenues were not attractive enough to justify the costs of acquiring them.

The implication of a fall in the MM is that liquidity (under the form of bank reserves/high-powered money) is now abundant in the system relative to the amount of bank money in circulation. Liquidity cost not being an issue anymore, banks nevertheless remain subject to operational and credit risk constraints, implying that they cannot put this liquidity to work rapidly.

Indeed, this situation is amplified during a crisis, as the number of creditworthy borrowers falls and banks lay off some of their employees to offset the fall in revenues and rising loan losses. Moreover, liquidity costs also rise and banks decide to hold on to higher liquidity buffers than they used to, mechanically lowering the MM. Consequently, there is no way the MM can rapidly rise. It takes time.

And this was the mistake made by a number of economists who wrongly predicted that hyperinflation would strike in the years following the implementation of quantitative easing policies. Credit cannot mechanistically and instantaneously grow. The financial system is a source of sticky constraints and rigidities. Of course we did see periods of above average MM growth (like just before the Depression or between 1980 and 1987*). But even if those particular growth rates were applied to today’s world, it would take more than twenty years for the MM to get back to its pre-crisis level.

Some could reply that banks don’t need extra resources to invest their liquidity into government bonds. While this is true some constraints remain in place: 1. the supply of government bonds is limited, and buying large quantities of them would become uneconomical for banks’ margin as bonds yield fall towards zero; 2. only a handful of governments have top credit ratings, and this rating fall as they issue more debt; 3. banks want to diversify their portfolio and certainly do not wish to only be exposed to sovereign risk.

The description above effectively applies to banking systems free of exogenous regulations. But regulatory dynamics can dramatically hinder the money creation process and hence the return of the MM to more normal levels.

Following the 2008/9 crisis, the Western world has been quick at altering regulatory requirements despite the weak economic recovery. In the decade following the crash, Basel 3 (implemented in the US under Dodd-Frank and in the EU under CRD4) built on previous versions of the Basel framework to progressively tighten operating restrictions – thereby reducing banks’ ability to generate marginal revenues – as well as capital, liquidity and funding requirements.

This regulatory package made it even more complex for bank to engage in lending. These are some of the steps that bankers now typically have to take in order to set up a new committed credit line:

  1. Client onboarding/Know-Your-Customer, which is getting increasingly tightened by authorities due to international sanctions, tax evasion and terrorism
  2. Credit analysis/risk assessment facility type/comparison with risk appetite and internal risk management guidance
  3. Estimate what the regulatory liquidity (LCR) and funding (NSFR) requirements are going to be for this specific credit facility.
  4. Estimate the cost of getting hold of the specific liquid assets and funding instruments (which both are in limited supply on the market and hence costly to acquire) that rules require
  5. Estimate the amount of regulatory capital (also in limited supply) required for such a facility
  6. Estimate total risk-adjusted revenues of the new credit facility (plus any other revenues from this customer), deduct total costs, and compare with required regulatory capital
  7. If return on capital too low vs. management policy, decide whether or not to extend credit based on relationship
  8. Negotiate loan agreement/covenants

Those steps require human resources in relationship management, risk management, legal and treasury. As the process has been lengthened and complexified by Basel 3 in the post-crisis years, it is unsurprising that banks, already facing declining revenues and costs-cutting (i.e. staff), haven’t been able to grow their balance sheet as rapidly as bank reserves were flowing into the system. Moreover, faced with harsher capital regulations and unending litigation costs in a world of low or negative interest rates, banks found it extremely hard to find remunerative lending opportunities. Consequently, many banks have now entirely exited a number of lending products whose marginal costs have been pushed up by regulation above their marginal revenues. They have deleveraged in order to be compliant with capitalisation rules rather than raise capital to avoid diluting shareholders already suffering from  zero return (therefore at risk of exiting their investment altogether). I guess I don’t have to explain that a deleveraging banking system is antithetical with a rising MM.

Finally, I shall include monetary policy in the ‘regulatory dynamics’ category, and more particularly the decision by a number of central banks to pay interests on excess reserves. It is not the purpose of this post to focus on this rather strange monetary tool; George Selgin wrote plenty of excellent posts deconstructing its rationale.

A last note however. While we’ve mostly been describing the factors influencing the supply of credit, let’s not forget to factor in the other side of the equation: demand for credit. During or following a credit crisis, borrowers often attempt to repair their balance sheets by deleveraging, affecting the demand for new loans.

In the end, it looks unsurprising to see the money multiplier remaining so low and taking decades to recover following a rapid fall. As history shows, this is a recurring fact, dictated by the day to day operating rigidities of the business of banking, and with consequences for the bank lending channel of monetary policy. Our dear multiplier isn’t dead; it is just sleeping and merely unlikely to reach pre-crisis levels for another few decades.

 

*Such rapid growth rate in the 1980s is probably linked to banks trying to add more remunerative lending to their portfolio as rapidly as possible. This is because, as both nominal interest rates and inflation were shooting up, banks’ margins were becoming rapidly compressed due to legacy lending extended in earlier periods of lower nominal rates.

This post was re-published on Alt-M.

Brexit regime uncertainty: some evidence

Following my latest post on the regulatory regime uncertainty caused by Brexit, evidence of the damages has started to emerge.

Unsurprisingly, and in line with the studies mentioned in my previous post, uncertainty is affecting both the demand and supply sides of credit.

On the demand side, the FT reports that

like other small British companies … longer term prospects have been altered by the EU referendum. Last month’s vote has dramatically increased uncertainty on issues ranging from regulatory standards to supply chains. […]

Other local companies have reported laying off staff, raising prices, or scaling back on investment plans, among a range of responses that also include seeking to take advantage of the weaker pound, in a survey compiled by Business West, a lobby group in the south-west of England.

This is evidently not conducive to borrowing and investments, and City AM reports that the number of M&A deals in Britain indeed significantly dropped in the first half of the year. Furthermore, the FT also reports that large British banks “expect demand for credit from businesses and households to fall as a result of post-Brexit economic uncertainty, according to a Bank of England review.”

The same article seems to show that, on the supply side, banks are for the time being only tightening commercial real estate lending given their pessimistic view of the sector (which also was a major contributor to UK banks’ losses during the financial crisis).

Finally, another FT article shows that

An index tracking sentiment in the European banking sector has reached an all-time low, even surpassing levels seen in 2012 when Mario Draghi promised the European Central Bank was prepared to do “whatever it takes” to stabilise the bloc and protect the euro.

European banking sentiment index

This is likely to affect the supply of credit in medium-term across the whole of Europe as Brexit uncertainty exacerbates already-existing European banking issues. The shorter this lasts the better.

Sadly, this situation could take up to six years, according to the UK foreign minister

Brexit: the consequences on lending

The British voted in favour of leaving the European Union at the end of last week. Whether the UK effectively leaves the EU and what sort of arrangement emerges is yet to be determined. What is certain is that the business world now finds itself in the most uncertain of political environments: no one knows what kind of ruleset is actually going to be put in place and how long this state of limbo will last.

The whole situation is likely to prove damaging for the UK economy as businesses freeze hiring and investments until they have a better understanding about the rules they’re going to have to comply with. Brexit is in effect a typical case of what Robert Higgs named ‘regime uncertainty’.

Higgs described how regulatory regime uncertainty considerably hampered private investments in the US in the 1930s, which in turn affected economic recovery. This period saw Hoover and then FDR’s New Deal make considerable changes to the US legal and regulatory frameworks. According to Higgs:

given the unparalleled outpouring of business-threatening laws, regulations, and court decisions, the oft-stated hostility of President Roosevelt and his lieutenants toward investors as a class, and the character of the antibusiness zealots who composed the strategists and administrators of the New Deal from 1935 to 1941, the political climate could hardly have failed to discourage some investors from making fresh long-term commitments … there exists a great deal of direct evidence that investors did feel extraordinarily uncertain about the future of the property-rights regime between 1935 and 1941. Historians have recorded countless statements by contemporaries to that effect; and the poll data presented earlier confirm that in the years just before the war most business executives expected substantial attenuations of private property rights ranging up to “complete economic dictatorship.

Seen in light of modern expectations framework, Higgs’ theory does make sense: businesses are unlikely to engage into activities whose legal treatment is uncertain. In one of my first ever posts I wrote that, given the uncertainty inherent to a productive process that takes time, a stable ruleset and predictable property rights treatments were fundamental features of intertemporal coordination between savers/investors and borrowers/entrepreneurs.

Stable rules provide a clear guide to entrepreneurs: constraints are known in advance allowing them to anticipate future demand and plan accordingly with the understanding that their investments are protected as long as they remain within legal boundaries. The Rule of Law – what Hayek described as a ‘meta-legal’ framework that spontaneously and progressively emerged, and which is mostly incarnated today by the Common Law – represents the most effective instance of stable rules. But even the less stable Civil Law – which is mainly comprised of what Hayek called ‘legislation’ – can represent a relatively effective legal framework as long as rules aren’t changed on a regular basis. Surprisingly however, the academic litterature on regime uncertainty remains rather thin.

Coincidentally, a paper published earlier this year by Bordo, Duca and Koch (Economic Policy Uncertainty and the Credit Channel: Aggregate and Bank Level U.S. Evidence Over Severa Decades, also available on NBER here) adds extra empirical evidence to Higgs’ original findings. Basing their research on a recently published ‘economic policy uncertainty index’ (EPU thereafter), and controlling for other macroeconomic indicators, they look at how regime uncertainty affects bank lending in the US between 1961 and 2014. Overall, they find that

policy uncertainty significantly slows U.S. bank credit growth, consistent with it having an effect on broad loan supply and demand. We find that lagged changes in the EPU index are negatively and significantly linked to the growth rate of bank lending both at the aggregate and cross-sectional levels.

image

They also find that this effect is more pronounced for larger, less well-capitalised banks, as well as banks holding smaller amounts of cash reserves, and that the effect is likely amplified in Europe*:

The results have several important implications. First, statistical evidence suggests that economic policy uncertainty has affected bank lending in the U.S., which other studies have found to have important effects on economic activity and which we also find. This could have implications for Europe, where the Baker-Bloom-Davis (BBD) index of economic policy uncertainty rose more than in the U.S. during the post-crisis slump and the economies are more bank dependent. More recently, the EPU index in Europe has not recovered as quickly as in the U.S., where the subsequent recovery in bank-lending growth has been stronger as has been the overall recovery in GDP growth.

Given that London represents a substantial share of Europe’s financial activity and is the main Euro clearing centre (a situation that the ECB has fought for years), the implications for a post-Brexit Europe are clear. Domestically, the demand and supply of loans in the UK are likely to remain subdued as long as the legal framework that will apply to British banks and corporations in the future is unknown. The uncertainty is also going to hurt foreign banks, which have large operations in London thanks to the UK’s ‘passporting’ rights (which allow financial firms based in the UK to offer services throughout the EU under single market rules). Many of those institutions are unsure whether to move operations to other EU jurisdictions as nobody knows if the UK will be able to retain single market access and Euro clearing. This paralyses business-making in a period of already heightened regulatory uncertainty.

image

Legal uncertainty affecting the financial sector is of the worst kind given its repercussions on economic activity. It is therefore unsurprising that, following the Brexit vote, stockmarkets in the EU have fallen more than those in the UK. The announcement even triggered the worst fall in EU banks’ share price in history.

Brexit will have repercussions on lending and investments both in the UK and in the EU as long as this state of uncertainty lasts. And it can even end up being more damaging for other EU countries, already suffering from low economic growth and constantly-changing banking regulation. Of course, politicians seem unaware of this issue: some of the top ‘Leave’ campaign leaders mentioned triggering the article 50 of the Lisbon Treaty (which brings about the departure of a member of the EU) only in… 2020.

Given that it takes two years of negotiation following the trigger for a country to be formally out of the union, and that undoing EU laws while negotiating new trade deals can last many more years, it is clear that those politicians are at best – some would say unsurprisingly –  completely ignorant of the damages they are making. It took Greenland, which withdrew from the pre-EU in 1985, three years to negotiate the terms of its exit with the union at a time when EU laws were not as invasive as they are now. Good luck to Europeans.

*They also question the timing of the implementation of new harsh banking regulations (i.e. Basel 3) which may have delayed the post-crisis economic recovery in their view (a point I have made in a number of posts over the years).

PS: Bordo, Duca and Koch also provide further evidence of the 1990s deregulation myth:

image

It wasn’t a subprime crisis

The term ‘subprime crisis’ is still widely used to describe the recent financial crisis. Yet it gives the impression that the crisis emanated from a very narrow asset class (i.e. subprime mortgage lending) that somehow managed to spread throughout the US economy and the wider world and knock down most Western economies. The narrative is that financial innovation and engineering fuelled this process by creating products like RMBS and CDOs.

On closer examination, this story cannot hold. Real estate markets boomed and fell simultaneously around the world despite no subprime lending going on in these other markets. Mortgage lenders in countries such as Spain, Ireland and the UK suffered or even collapsed when falling house prices forced them to provision huge amounts, damaging their balance sheet and ability to lend.

Even in the US, the crisis wasn’t triggered by subprime but by an unsustainable allocation of resources towards the entire real estate sector. New research adds further evidence to this view (Loan Origination and Defaults in the Mortgage Crisis: The Role of the Middle Class). In this paper, Adelino, Schoar and Severino demonstrate that “mortgage originations increased for borrowers across all income levels and FICO scores” and that “middle-income, high-income, and prime borrowers all sharply increased their share of delinquencies in the crisis.” This conclusion is in stark contrast with that of Mian and Sufi’s famous 2009 article (which they reformulated in their book House of Debt), which had fuelled the theory of a subprime origin to the crisis (I had already voiced doubts about their theory here).

More precisely, Adelina et al find that credit flowed towards all sorts of borrowers in the years preceding the crisis, and not just disproportionately towards subprime ones:

between 2002 and 2006 mortgage origination increased for borrowers across the whole income distribution, not just for low-income or subprime borrowers. In line with previous years, the majority of new mortgages by value were originated to middle-class and high-income segments of the population even at the peak of the boom. Similarly, the share of originations to subprime borrowers (those with a credit score below 660) relative to high credit score borrowers remained stable across the pre-crisis period. Although the pace of origination rose in low-income ZIP codes, this increase did not translate into significant changes in the overall distribution of credit, given that it started from a low base (borrowers in low-income and subprime ZIP codes obtain fewer and significantly smaller mortgages on average).

They also find that non-performing loans rose across the board, implying that losses were triggered by all sorts of real estate loans:

We show that the share of mortgage dollars in delinquency stemming from the lowest income groups decreased during the financial crisis. In contrast, middle- and high-income borrowers constituted a larger share of mortgage dollars in delinquency than in any prior year. The magnitudes are large: for the 2003 mortgage cohort, the top quintile of the income distribution constituted only 13% of mortgage dollars in delinquency three years later, whereas for the 2006 cohort, the top income quintile made up 23% of the delinquencies three years out. In contrast, over the same period, the contribution to delinquencies from the ZIP codes in the lowest 20% of the income distribution fell from 22% to only 11%.

We find a similar pattern when we look at credit scores: the share of mortgage defaults from borrowers with high credit scores increased during the crisis, whereas the share for subprime borrowers dropped.

Mortgages US crisis

Adelina et al therefore provide evidence that links the US real estate crisis with that of other countries: same roots, same consequences. The US did not experience a crisis because of a sudden and sharp increase in subprime borrowing. Subprime merely was a bystander; a symptom of deeper economic problems. Rather, the US experienced the same sort of crisis as its European counterparts: an overall debt-fuelled rise in real estate prices.

And this makes perfect sense: I keep emphasising the role played by Basel’s capital regulation in inflating the housing bubble. Low capital requirements on real estate loans provided bankers an incentive to maximise profitability within regulatory boundaries, directing the flow of credit towards housing, inflating the bubble. A purely subprime story with relatively low or no effect on other types of borrowers would not really fit this theory and would not match the experience of other countries.

Do not get me wrong though: subprime lending probably amplified the losses that some banks experienced, and did spread the crisis abroad to some extent. While the German real estate market remained roughly stable throughout the period, a number of German Landesbanks that had invested in tranches of structured products based on US subprime or near-subprime mortgages did suffer quite badly when the market price of those products radically fell.

Another very recent publication (The effect of bank shocks on firm-level and aggregate investment, by Amador and Nagengast) looks at what happened to lending and investment in the Portuguese economy following bank shocks during the 2005 to 2013 period. While I am not aware of similarly-structured studies of bank shocks in the US economy, this paper does seem to be in line with empirical results obtained by other researchers focusing on countries as diverse as Japan, Germany and emerging markets. They found that

credit supply shocks have a strong impact on firm-level investment in the Portuguese economy over and above aggregate demand conditions and firm-specific investment opportunities. In addition, we also consider how the effect of credit supply shocks on investment varies with the capital structure and size of firms. We find that firms with access to alternative financing sources are generally less vulnerable to the adverse effect of bank shocks on investment and partially manage to offset their shortfall of bank credit by increasing their financing from other sources. Larger firms also appear to be in a better position to cope with the unfavourable effects of bank shocks mainly since their banks do not curtail their credit supply as much as for small firms.

Those results look unsurprising to me and surely amplified by Basel rules that stipulate that small firms require proportionally more capital than large ones (a requirement that is hardly justified).

But combined with the empirical evidence provided above by Adelina et al, they allow me to reiterate my doubts regarding the claim that NGDP targeting would have merely led to a mild recession. This is a view of the crisis that some market monetarists accept, and which was summarised by Beckworth and Ponnuru in an NYT column earlier this year:

In retrospect, economists have concluded that a recession began in December 2007. But this recession started very mildly. Through early 2008, even as investors kept pulling money out of the shadow banks, key economic indicators such as inflation and nominal spending — the total amount of dollars being spent throughout the economy — barely budged. It looked as if the economy would be relatively unscathed, as many forecasters were saying at the time. The problem was manageable: According to Gary Gorton, an economist at Yale, roughly 6 percent of banking assets were tied to subprime mortgages in 2007.

I wrote elsewhere why I believe this view is inaccurate. But this new evidence provided by Adelina et al adds strength to my previous arguments by showing that the crisis was a full-scale real estate collapse rather than a mere and ‘manageable’ subprime-focused crisis. It should also make us think twice about the ability of NGDP targeting to cope with a situation during which banks’ balance sheets are highly damaged, leading to reduced lending and aggregate private investments throughout the economy.

That said, I do view NGDPT as a much better alternative to our current monetary arrangement. While it could potentially have alleviated the worst symptoms of the crash, I believe it is quite a stretch to think it could have led to a merely ‘mild’ recession. Please bear in mind however, that my reasoning only applies within the current institutional constraints on the implementation of monetary policy.

Were those constraints lifted, NGDP targeting could be more effective in stimulating the economy post-crash. Whether this is desirable is another issue altogether, and I tend to adhere to Salter and Cachanosky’s view that the composition of NGDP also matters*. After all, NGDP growth was roughly stable for the decade preceding the crisis, yet hid some unsustainable allocation of resources. Consequently, it seems to me that distortionary regulatory frameworks limit the effectiveness of a stable NGDP path. But would we even need NGDP targeting in a free market?

US NGDP

 

*As a side note, an interesting paper published last year seems to provide some evidence of the distortionary effect on relative prices of the usual monetary injection channel of monetary policy (i.e. Cantillon effect). This is only a lab experiment, but its conclusions are clear:

Although the theoretical model predicts, in line with mainstream economics, that the process of monetary injection is irrelevant and neutral, the experiment shows that credit expansion exerts a significant distortionary effect on resource allocation. Credit expansion also has a redistributive effect across subjects in favor of those who have a high consumption preference for the good whose production is stimulated by credit. The allocative effect of credit expansion comes from the fact that the increase in money is injected into the credit market, whereas lump-sum transfers affect all sectors evenly.

This finding is reminiscent of the insights of Cantillon (1755), who emphasised that an increase in money primarily affects relative prices rather than all prices to the same extent because money enters the economy at a certain point. This suggests that the process of monetary injection and its economic consequences should be addressed in implementing specific monetary policy measures or, more importantly, in designing the monetary system as a whole.

PS: This is my first blog post in a while. I am currently transitioning between jobs, and am pretty busy as a result.

Misunderstanding the net interest margin

Lately, there have been a lot of discussions in the media and in the academic sphere surrounding banks’ net interest margin in the low (or negative) interest rate environment. I have explained before how lowering interest rates below a certain threshold led to ‘margin compression’ (see here), which in turned depressed banks’ profitability and hence their internal capital generation, solidity and ability to lend.

The net interest margin (NIM thereafter) is roughly the difference between the average interest rate earned on assets and the average interest rate paid on funding, and is usually defined as

Net interest income / average earning assets, with NII being the difference between interest income (from loans and securities mostly) and interest expense (on deposits and other types of debt/funding instruments)

We now see conflicting articles and research pieces on the effects of low rates on banks’ NIM (see two of the most recent ones by the St Louis Fed here and other Fed researchers here). But, to my knowledge, most, if not all of those pieces make the same fundamental mistake: they do not look at risk-adjusted NIMs.

‘Risk adjustment’ is a critical concept but sadly often overlooked in the literature. I once defined the interest rate on a loan as the following:

LR = RFR + IP + CRP – C,

where LR is the loan rate, RFR is the applicable, same maturity, risk-free rate, IP the expected inflation premium, CRP the credit risk premium that applies to that particular customer and C the protection provided by the collateral (which can be zero).

As I explained elsewhere, margin compression occurs when the risk-free rate declines so much that interest rates banks pay on their funding reaches the zero lower bound while their interest income continues to decline (which led me to hypothesise that the zero-lower bound was actually a ‘2%-lower bound’ in the case of the banking/credit channel of monetary policy). This however assumes no fundamental change in the rest of the economy’s credit (or default) risk.

Indeed, in bad economic times, the CRP usually increases for most borrowers, partially offsetting the effects of the decline in the risk-free rate on new lending. Moreover, bankers can easily boost their NIM by lending relatively more to higher-risk customers or investing in higher-risk projects, even in good economic times. Consequently, it looks like the headline NIM isn’t suffering or declining that much. It can sometimes even improve, in particular when economic conditions are benign. For instance, emerging market banks often boast high NIMs, but also high default rates (and high ‘losses given default’). In such cases, margin compression seems not to be occurring. But this is just an accounting illusion.

See the example in the chart below, which represents the hypothetical evolution of the different components of a given unsecured loan rate throughout a long recession:

NIM components

Once you adjust the NIM for the loan book’s underlying risk, the story is different. Banks’ interest income can rise but the risk of default on new lending, as well as that of their legacy loan portfolio, also rises. Because the CRP is often fixed at inception, legacy lending now underpays relative to its risk profile, potentially implying economic losses down the line.

Most studies don’t factor this phenomenon in. They look at unadjusted NIMs, which in many cases do not provide any useful information.

A very good and quite recent paper on banking mechanics by Claudio Borio and his team (The influence of monetary policy on bank profitability), which looks at the impact of the shape of the yield curve on margin compression and banks’ profitability, does understand that accounting plays a significant role:

The second form [of dynamic effects in the transmission of the level of interest rates to net interest income], which is more relevant, relates to accounting practices. Any interest margin on new loans also covers expected losses. But provisions in the period we examine follow the “incurred loss model”, so that, in contrast to interest rates, they are not forward-looking. As a result, extending new loans raises profitability temporarily, since losses normally materialise only a few years later at which point loans also become non-performing, eroding the interest margin. This also  means  that  if  lower  market  rates  induce  more  lending,  they  will  temporarily boost net interest margins. The strength of this effect will depend on background economic conditions. For instance, it is likely to be weak precisely when interest rates are unusually low and the demand for loans anaemic.

However, they stop short of providing a solution, or a correction, to this effect. To be fair, risk-adjusted NIMs are not directly observable and very difficult to estimate, given that disclosures about banks’ loan portfolio are very limited and that only some of their customers (i.e. large corporates) have bonds or credit default swaps traded on the secondary market. Therefore, some analysts use the following ex-post adjusted NIM ratio:

(Net interest income – loan impairment charges) / average earning assets

Default risk, expressed in the income statement by loan impairment charges (LICs – also called loan-loss provisions), is directly deducted from net interest income, making the NIM easier to compare across banks or countries. But even this version can be highly inaccurate, as LICs are backward-looking and depend on each bank’s accounting policies. In the short-run, some banks tend to over-provision, others to under-provision.

You’ve reached the end of this post perhaps wondering whether I had a solution to this problem. Unfortunately no, I don’t. But I believed that a clarification was in order. In finance, or economics in general, any decision involves risk-taking, and studies that do not take risk into account must be taken with a pinch of salt.

PS: The inflation premium is stripped out of the risk-free rate in this post, but in practice benchmark market rates such as Treasuries already factor in inflation expectations.

This post was re-published on Alt-M.

On ‘shadow money’

The shadow banking literature has vastly and rapidly expanded since the financial crisis, and has produced some interesting pieces, as well as some exaggerated claims, in my view. While I am not writing today to address those claims, I still wish to question a closely linked concept that has simultaneously sprung up in the literature and in particular in the post-Keynesian one: shadow money.

One of the most elaborated and comprehensive academic research papers on this particular topic is the recently published Gabor’s and Vestergaard’s Towards a theory of shadow money. It’s an interesting and recommended piece. But while I agree with some of their writings, I have to find myself in disagreement with a number of their points and examples* and in particular their central claim: that repurchase agreements (‘repos’ thereafter) are shadow money; that is, a type of monetary instrument used within the shadow banking system.

For some readers that might not know how a repo works, below is a concise definition provided by the IMF:

Repo agreements are contracts in which one party agrees to sell securities to another party and buy them back at a specified date and repurchase price.48 The transaction is effectively a collateralized loan with the difference between the repurchase and sale price representing interest. The borrower typically posts excess collateral (the “haircut”). Dealers use repos to borrow from MMFs and other cash lenders to finance their own securities holdings and to make loans to hedge funds and other clients seeking to leverage their investments. Lenders typically rehypothecate repo collateral, that is, they reuse it in other repo transactions with cash borrowers.

Given repos’ (and their asset counterpart: reverse repos) properties, my view is that repos aren’t shadow money but a shadow funding instrument. While it might not sound such a big issue, I believe the distinction is important from an analytical perspective as well as to avoid confusion. Let me elaborate.

Gabor and Vestergaard define shadow money as “repo liabilities, promises backed by tradable collateral.” According to them, shadow money has four key characteristics:

a) In modern money hierarchies, repo claims are nearest to settlement money, stronger in their ‘moneyness’ than ABCPs or MMF shares.

b) Banks issue shadow money. The incentives to issue repos are incentives to economize on bank deposits and bank reserves.

c) Shadow money, like bank money, relies on sovereign structures of authority and creditworthiness. The state offers a tradable claim that constitutes the base asset supporting the issuance of shadow claims.

d) Repos create (and destroy) liquidity at lower levels in the hierarchy of credit claims.

They offer this chart of ‘modern’ money hierarchy:

Shadow Money

I have to object to repos being classified as ‘money’.

Money, as typically defined by economists, has three characteristics: it is a medium of exchange, a unit of account and a store of value. High-powered money (the ‘outside money’ of the financial system) currently fits this definition, as a final settlement medium.

The ‘moneyness’ concept, a term now popularised by JP Koning’s excellent blog, asserts that various types of assets have various degrees of money-like properties. In this quite old but classic post, JP argues that anything from beers and cattle to deposits benefits from some degree of moneyness. In another old post, Cullen Roche provided the following good ‘money spectrum’ chart (although I’d disagree with his outside money/deposit ranking):

scale of moneyness

Therefore, most goods and assets have some monetary properties: some can be used as media of exchange or store of value. All represent a claim of some sort on money proper. As a general (but inaccurate) rule, the more their price in terms of outside money fluctuate, and hence their conversion risk raises, the further away they are on the moneyness scale. But conversion (almost) on demand also implies that, in order to have some money characteristics, a good or asset needs to be tradable.

Now let’s get back to repos as shadow money.

Repos are a liability issued by the debtor in exchange for high-powered money, of which reverse repos are the asset counterpart held by the creditor (and hence the claim on the high-powered money originally transferred, plus interest). The debtor also transfers an extra asset (i.e. the collateral) to the creditor for security purposes at a pre-agreed haircut depending on its credit quality and market risk sensitivity.

We get here to the main point of this post: repos have little money-like property due to their non-tradability and lack of on-demand convertibility.

Indeed, a repo liability is of course non-tradable, in the same way that any debt that one owes cannot be traded for another type of liability. It can only be refinanced and/or extinguished. A reverse repo (or repo claim) however, could potentially have tradable properties, allowing a creditor to exchange his claim almost instantaneously on the market. Problem is: this does not happen. Unlike bonds or other assets, and due to the very specific features of such private agreements, there is no secondary market for repo claims. Once a repo has been agreed upon, the contract is fixed between the two parties until maturity (or default). Consequently, repo claims can effectively be assumed to have no liquidity.

Seen this way, it is hard to classify repos as ‘money’, and they certainly do not deserve their third place in the moneyness hierarchy above. So what are repos? As I previously said, they are a funding instrument. Given that the shadow banking system makes use of repos on a large scale, we can potentially call them a ‘short-term secured shadow funding instrument’. And please note that repo issuance isn’t limited to banks and broker-dealers; other institutions also use them.

You’ll be tempted to reply: “what about deposits? They have no secondary market and are not tradable either.” This isn’t strictly accurate. While they are both promises to pay a certain amount of money proper at a certain date, there is a very specific difference between deposit liabilities (‘on demand’ ones especially) and repo liabilities. Banks themselves are deposits’ secondary market: deposits can be ‘traded’ within the bank’s own balance sheet and swapped for cash on demand. And when dealing with a counterparty that does not hold an account with the same bank, banks take over the responsibility of transferring the underlying funds (i.e. high-powered money).

If repos aren’t ‘money’, what else could be considered ‘shadow money’? Well, assets provided as collateral do have liquidity, tradability, and therefore some ‘moneyness’. Those assets can sometimes be used in further transactions. This is why I am wondering whether or not there isn’t some confusion with ‘shadow money’ proponents’ terminology. While their writings clearly emphasise the ‘shadow money’ nature of repos themselves (and Poszar seems to be using the same definition here), many other academic authors have instead referred to the most commonly-used types of repo collateral (high quality and highly liquid sovereign and corporate bonds) as ‘shadow money’ (which indeed makes more sense to me, although I do not fully adhere to this concept either).

There are plenty of things worth discussing regarding this theory of shadow money and the use of repos in general, but the money-like properties of repurchase agreements isn’t one of them. Let’s focus on their funding properties instead.

 

*I also believe that their shadow money expansion theory is subject to the same critique as other endogenous outside money theories, such as MMT’s.

PS: the fact that repos are backed by marketable collateral does not confer any specific monetary property to repo claims. Marketable collateral is used in many other types of lending transactions, in particular in private banking-type lending. Also, repos and any other collateralised lending are expected to be repaid at par, independently of the valuation fluctuations of their underlying collateral.

PPS: Baker and Murphy build on Gabor’s and Vestergaard’s piece and just published a blog post that argues for a new ‘investment state’, in a typical post-Keynesian interventionist fashion.

This post was re-published on Alt-M.

What China can teach us about the future of banking

A few weeks ago, Citi published a quite fascinating 100-page report on financial innovations, from blockchain to P2P lending, in various regions of the world. It’s a highly recommended and very comprehensive reading that I won’t be able to summarise in a short blog post.

From this report, it is clear that China’s financial system has adopted innovations at a much faster pace than the Western world. And if there is a defining characteristic of the Chinese system, it is its very erratic and repressive regulatory framework, which made me once call China a ‘spontaneous Frankenstein banking system’:

Financial regulation in China is quite a mess. China seems to be the world testing ground for some of the most ridiculous banking rules. With all their related unexpected consequences.

In an earlier post, I also highlighted that

China is an interesting case. Underneath its very tight government-controlled financial repression hide numerous financial experiments aimed at bypassing those very controls. The Chinese shadow banking system is now a well-known financial Frankenstein, with multiple asset management companies, wealth management products and other off-balance sheet entities providing around half the country’s credit volume. The more the government tries to regulate the system, the more financial innovation finds new workarounds and become increasingly more opaque.

We already knew that the Chinese financial system was completely distorted from years of regulatory repression and crony capitalism, as a whole new report on finance in China by The Economist demonstrates (see the editorial here, and the report starting here). Echoing my worries, The Economist calls for China to ‘free up’ its ‘financial jungle’. Citi’s and The Economist’s reports now allow us to quantify the effects of those distortions. Indeed, China leads the world in fintech and digital disruption in general; it has some of the largest fintech firms and, as Citi said, it is now ‘past the tipping point’.

While its very large e-commerce has been a strong driver of the rise of alternative payment providers in the country, Citi points at a number of other factors that have facilitated the rise of those third-party payment companies, among which an under-developed banking system viewed by the public as quite unreliable (unsurprising given how tightly controlled banking is in China, which has stifled customer-oriented innovation), and ‘relaxed regulation’. Citi points out that Chinese regulators have now proposed new tightened rules for the payment sector, so brace yourself for further innovations in this space. For now, Alipay handles more than three times the volume of transaction that Paypal does, and payment firms have more retail customers than banks have and are now expanding into offline payments.

China bank customers

China payment methods

China also has the largest P2P lending market in the world, four times bigger than that of the US. Citi analysts forecast that P2P loans are going to represent a sizeable 9% of total retail lending in China by 2018.

The driver of this growth is, typically, mostly regulatory constraints on traditional banking that triggered regulatory arbitrage:

P2P lending platforms target segments that are unserved or under-served by existing banking system such as consumer credit and small and micro business lending. Traditional banks are not particularly good at serving this customer segments due to tougher Know Your Client/Anti-Money Laundering (KYC/AML) requirements as well as tightened lending standard post global financial crisis.

And one would add that capital requirements on certain category of customers (such as SMEs) play a large role here too, as I keep pointing out on this blog (see at the end of this post). The same reasons are behind the development of such lending platforms in Europe and the US. And indeed, as Citi writes:

According to China MSME Finance Report 2014 by Mintai Institute of Finance and Banking, almost 80% of SMEs were not served by the banks. The explosive growth in the P2P lending has met the needs of SMEs which cannot get formal financing.

And:

Chinese banks are under tight regulations such as reserve requirement, loan-to-deposit ratios (LDR), KYC, AML, and so on. There was however little regulations for the P2P lending sector. There is also no capital requirement.

Furthermore, Chinese monetary repression is also a driver, as P2P lending allows savers to earn higher returns. Here again, Chinese regulators are looking at ways to scrutinise and more tightly control the sector.

What are the effects of all this? As The Economist points out, China’s shadow banking sector is the largest and possibly the fastest growing in the world:

China total debt

China shadow banking

There is a fundamental difference between the Chinese banking system and the Western one however. Chinese banks, despite being extremely large, have historically had no ability to grow outside of the Communist party’s grip and no ability to adapt to consumer demand as a result. Citi points out that there were only 8.1 bank branches per 100,000 adults in China, vs. around 30 in the Eurozone and the US. With little banking presence, fintech firms have found it easy to rapidly grow.

Yet, developed economies do have a lesson to learn from the Chinese experience. The more regulatory constraints are put in place on banks, the more innovative ways around them will spontaneously emerge and the more complex and opaque (‘Frankenstein-like’) the financial system will become. And sadly, it looks like Europe and the US have decided to follow China’s footsteps.

 

PS: The following chart is revealing. Most of the financial products that are at most risk of disruption (SME and personal loans, deposits…) are also those that are the most affected by regulatory requirements and low interest rates.

Fintech disruption by product type

PPS: A very good introduction to the Chinese financial mess is Walter’s and Howie’s Red Capitalism. However the book was ‘only’ updated in 2012, and plenty has happened since then, in particular in the fintech portion of China’s shadow banking sector.

PPPS: Apologies for not posting more regularly at the moment, but I ended up being busier than I thought I would be.

This post was re-published on Alt-M.

Bank regulators are confused by their own mess

Regulators are getting confused by their own reform package. After years of promoting contingent convertible bonds (CoCos) as a good alternative to pure equity capital, and basing a number of their regulatory changes on them, they are now backtracking, as the FT reports (at least in the case of the ECB):

Cocos are a key pillar in the regulatory regime drawn up to strengthen banks’ capital levels and prevent taxpayer bailouts after the financial crisis. But while they are supposed to increase financial stability, concerns about them helped whip up market volatility in February.

Senior executives at several large banks have told officials at the [Single Supervisory Mechanism] that the rules for cocos are too complicated and they could undermine a bank’s financial position rather than strengthen it in a crisis.

CoCos are a form of hybrid debt that converts into equity when a bank’s regulatory capital ratio falls below a certain threshold. They are currently accounted for as ‘Tier 1 capital’. On paper, they sound quite straightforward.

In reality, they are quite opaque. Nobody really knows how to accurately value them. They have both equity and debt-like properties: cash flows are less recurring than debt but more than equity. Nobody really knows how those instruments will fare from a legal point of view when a firm goes into administration. Regulation in some jurisdictions also prevent coupon payments in some unclear cases, even when the bank isn’t about to fall into bankruptcy.

The market has boomed over the past few years as rates on offer looked attractive in a low interest rate environment that pushed many investors to search for yield. CoCos, apparently safer than stocks, seemed to be the easy choice. Some commentators started to worry that interest rates on new issues were way too low for an equity-like instrument (yields fell to about 6% and remained there since 2013, see The Economist chart below, whereas the required return on equity is usually estimated around 11 or 12%). And indeed, CoCos’ valuations suffered during the bank sell-off earlier this year as investors suddenly woke up to the fact that they actually didn’t fully understand those instruments. This CoCo sell-off actually endangered the stability of the banking system, at odds with regulators’ original aim.

CoCo yields

Regulators are also backtracking on capital requirements, as they see how damaging they are for smaller banks. Reuters report:

The European Union will propose changing the bloc’s rules on bank capital requirements to ease the burden on smaller lenders in a bid to boost growth, EU financial services chief Jonathan Hill said on Thursday.

In a speech in Amsterdam where EU finance ministers are meeting, Hill said he wants to lighten reporting and disclosure requirements for smaller banks.

“I also want to see whether the intricate calculations banks have to do to comply with prudential rules could be simplified. And whether there is a case for small banks with limited trading activities to be exempt from capital requirements for trading book exposures,” Hill said.

Hill’s speech underscored the willingness of the EU to deviate from globally-agreed capital norms to encourage more banks to lend more.

What the EU is proposing to create is a multi-speed regulatory framework. And we know how damaging multi-speed systems are: firms and individuals engage in regulatory engineering or even stop or reduce their activities in order not to move into the next, more burdensome and constraining, bucket, as this could imply larger additional marginal costs than marginal revenues.

We all know that small banks suffer from those misguided regulatory packages that Basel 3/Dodd-Frank/CRD 4 are, but the best solution is to repeal them for all banks, not create a multi-speed system and introduce further distortions and regime uncertainty that paralyse lending and prevent economic recovery. We’ve had enough of this mess.

PS: Bloomberg reports that Credit Suisse is looking to issue a new type of fixed income instrument that would cover potential operational losses due to rogue trading, fraud or cybercrime, in cooperation with the Zurich Insurance group. As Bloomberg says:

Regulators require banks to hold funds as a safeguard against various kinds of vulnerability, leaving them with less money to build the business.

Here again this potentially difficult to value instrument emerges from the willingness to offset the often unnecessary costs of capital regulation. But it doesn’t take a genius to figure out that those ‘solutions’ create problems of their own.

Update: Regulators are also about to introduce a new capital requirement for interest rate risk, which is likely to seriously weigh on banks’ profitability. It is funny that central bankers, who ow also often are regulators, decide to boost the economy by pushing rates down as much as possible, but then penalise banks for the same reason. Such incoherence is not going to help lending volumes, I’m telling you.

Academics’ unhealthy obsession with bank opacity

I just read a January 2015 paper (not very recent, I know, but my reading list is huge) that was not only curious, but also plain wrong. The paper, titled Understanding the role of debt in the financial system and written by Bengt Holmstrom, illustrates a curious belief among a number of academic economists: that banking, in order to be stable, should be opaque.

The abstract sets the tone:

Money markets are fundamentally different from stock markets. Stock markets are about price discovery for the purpose of allocating risk efficiently. Money markets are about obviating the need for price discovery using over-collateralised debt to reduce the cost of lending.

Later, he adds that

Without the need for price discovery the need for public transparency is much less. Opacity is a natural feature of money markets and can in some instances enhance liquidity

His views about the stock market/money market differences are summarised in the following table:

Holmstrom money markets

Now let me say that there is virtually nothing in his arguments that is grounded in reality. This theory is completely disconnected from the day-to-day routine of finance workers.

Let’s start with Holmstrom’s definition of ‘money markets’. Following his paper, money markets only involve repurchase agreements. This cannot be further from the truth. Money markets (which we can also call interbank markets) not only involve repos, but also uncommitted and unsecured interbank placements (which include Fed funds). In fact, for many banks, those placements represent the bulk of their money market exposures. For instance, according to the financial database Bankscope, JPMorgan’s assets comprised $213Bn of reverse repos and $340Bn of interbank placements. Citigroup: $120Bn and $112Bn. Deutsche Bank: EUR107Bn and EUR13Bn. HSBC: $147Bn and $96Bn*. Small banks, that have very limited trading activities, have almost no reverse repo transactions outstanding.

So the unsecured, relatively longer-term, interbank market is at the least a sizeable portion of money markets. And it is completely ignored by Holmstrom’s generalisation. Given that his arguments rest on the ability of the lender to over-collateralise his exposure, they suddenly weaken considerably.

More fundamentally, Holmstrom really misunderstands the differences between stock and money markets. In reality, both markets are very information sensitive and require transparency. Both markets rely on fundamental financial analysis to assess the riskiness of any investment. Equity markets are more liquid because they involve only a single instrument by issuing firm; instrument whose value is highly sensitive to the profitability of the firm because its yield depends on it.

Credit markets are much, much, larger and involve a multitude of instruments by issuing firm, covering a broad spectrum of hybrids from pure credit to almost equity-like debt. Those debt instruments are ranked differently in the hierarchy of creditors. Senior creditors, including unsecured money market placements, have the first claim on a bankrupt firm’s assets. Does this mean they are information insensitive? Certainly not. But the market value of a firm’s assets fluctuates less than the same firm’s profits/cash flows. Price discovery is continuous; either at issuance (the higher the risk, the higher the interest rate), or on the ‘secondary’ market: given that interest rates on issues are usually fixed, a decline or improvement in the risk profile of the issuer triggers a change in the market price of related issues. Therefore information, and indeed transparency, is crucial in this continuous risk assessment process.

So Holmstrom’s generalised arguments about ‘money markets’ are simply wrong. But are secured credit markets, including reverse repos, devoid of the above rules? Does collateral-posting allow the lender to avoid assessing the inherent riskiness of his counterparty?

While it is true that collateral mitigates risk, no serious lender would ever blindly lend merely on the basis of collateral availability. There are a number of reasons for that. First, collateral is also subject to credit risk, and needs separate assessment. Second, collateral is subject to market risk (i.e. market price fluctuations), requiring the application of a haircut. Despite the haircut, when a crisis strikes and markets all fall simultaneously, the value of your collateral can potentially collapse as fast, if not faster, than the amount you lent. Third, legal risk means that there can be a delay between the insolvency event and the moment you can legally take possession of the collateral (depending on the original contract). And fourth, the news that you had exposure to a collapsing firm, even if you were secured, can easily raise risk-aversion towards you and trigger financial difficulties.

In the end, even in the case of secured lending, fundamental analysis, which relies on transparent information, is necessary. Opacity, unlike what our economists believe, is usually ‘credit negative’ and accentuates the compensation and/or the collateralisation that the lender requires. Moreover, how can the collateralisation level of a transaction be determined without some sort of initial price discovery? Holmstrom does not answer this question.

Unfortunately, Holmstrom’s piece is full of facts that are grounded in an imaginary world. For instance, see his claim that

When new bonds are issued, the issue is typically sold in a day or less. Little information is given to the buyers. It is very far from the costly and time-consuming road shows and book-building that new stock issues require in order to convey sufficient information.

Please, I beg you never to say that sort of things at a financial conference if you don’t want to get laughed at. The truth is that specific roadshows targeting fixed income investors are regularly organised by companies. Fixed income managers also employ buy-side analysts who spend their day analysing those firms, as well as reading pieces of financial research published by sell-side analysts. According to Holmstrom, those people do not seem to exist.

He also claims that bond ratings are ‘coarse’, and that this is “another example of what appears to be purposeful opacity.” I find this amazing, given that rating agencies have about 22 different base rating notches, to which a multitude of extra ratings are added in order to provide the information Holmstrom believes is opaque. Now compare this with the usual three-notch stock rating system of Buy/Hold/Sell and you might conclude he got seriously mixed up here.

This tendency to believe that opacity ‘helps’ markets seems to be spreading. In 2014, Gorton et al (which included, unsurprisingly, Holmstrom) published a very weird paper titled Banks as Secret Keepers, which argues precisely that:

Banks are optimally opaque institutions. They produce debt for use as a transaction medium (bank money), which requires that information about the backing assets – loans – not be revealed, so that bank money does not fluctuate in value, reducing the efficiency of trade. This need for opacity conflicts with the production of information about investment projects, needed for allocative efficiency. Intermediaries exist to hide such information, so banks select portfolios of information-insensitive assets. For the economy as a whole, firms endogenously separate into bank finance and capital market/stock market finance depending on the cost of producing information about their projects.

The paper is based on a mathematical model that seems unable to describe what happens in real financial and deposit markets. And indeed they don’t bother providing much empirical evidence of their claims (as I am writing this post, Kadhim Shubber of FT Alphaville quotes the exact same paper rather uncritically).

At the end of the day, Holmstrom’s and Gorton’s theories seem to justify government intervention in deposit and money markets. But as Kevin Dowd just brilliantly reminded us, those ‘opacity’, ‘information asymmetry’ and ‘market failures’ in no way justify banking regulation, unless you disregard all empirical and historical evidences. And, of course, unless you don’t believe in government failure. Sadly, it seems that imagination wins over reality nowadays in academia.

 

*Moreover, some of the ‘reverse repo’ figures might include collateral posted against other sort of trades, as well as transactions with non-financial counterparties, implying that the ‘pure’ money market reverse repo portion mentioned here is likely smaller.

This post was re-published on Alt-M.

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