Comments on Ray Dalio's post on Monetary Policy 3 and MMT

Ray Dalio's comments are always well researched and interesting. For starters, I think, Principles for navigating Big Debt Crises is must read. (Its free PDF). His recent post on his LinkedIn blog is about Monetary Policy 3.0 and MMT. 

Some fundamental comments about present crisis:

1. QE only creates a space for fiscal response: Central banks and governments alike misunderstood the role of monetary policy in the 2008 financial crisis. The crisis was different than others we have faced since Great Depression. Per my reading of Keynes (which seems to different than Keynesians and neo-Keynesians both), in such crises, the proper response has to be from fiscal side. The monetary policy merely creates space for the fiscal response or accommodates the fiscal response preventing untoward consequences. The response had to be holistic - a coordinated and sustained monetary and fiscal policy response.
2. Fiscal policy amplification mechanism is broken: Broken may be a harsh word, we may choose "has become messy" in its place. The point is, fiscal policy needs an amplification mechanism. When government starts infrastructure spending, it needs some real value-creating sector to take it from there and start driving the economic engine. At present we do not have such "real value-creating sector" that can boost employments and wages generally. In 1980s we had tech, in 2000s we had internet, now we need something. In absence of a big driver, we need many small ones. If such capability is difficult to create in one sector it is quite difficult to create in more than one sectors too. The solution is to let inherent advantages play out.
3. Inherent advantages are muzzled: Inherent advantages have stopped driving international trade since east asian crisis, and at a larger scale with China's entry to WTO. Instead, we have pegged exchange rates (soft/hard/overt/covert), manipulated tariff and non-tariff barriers, and, in general, non-transparent trade policy. Until that is fixed we cannot have trade based on pure competitive advantage.
4. Small business innovations are indefensible: When people talk of China usurping Intellectual property they usually talk about submarine plans etc. But I am talking of something very basic. Check out new funding projects on kickstarter - innovative shoes, innovative bags, innovative pens, anything that takes your fancy. Just search on alibaba or just wait for few months you will see some products like those (invented by kickstarter entrepreneurs) in the market on mass scale. These products are not sold by those companies who invented them on kickstarter or such platforms. This is IP theft that hurts the most. It removes new business competitiveness right at its infancy.
5. Trickle-up always works; trickle down some times: Monetary policy practitioners and academic economists in general prefer trickle down economics. But empirical evidence says reverse is true. Trickle-up works all the time. Thus, when there is a choice of bail out, we must lean to lower strata. (A) It is more fair and just, (B) better optics and (C) right incentives. But MAIN reason it works because it balances the bargaining power of both sides. Bail out the top and they lean on to regulation to prevent or constrict trickle down stifling the economy. Bail out the bottom and lo and behold all the incentives align beautifully.
6. Certainty of employment and wages is the one super-indicator: The best solution to any crisis is to get certainty of employment and wages going, rest follows from that. Today we have almost full employment but it is uncertain. Wage predictability is also uncertain. That's why the lack of demand is so persistent.
7. Interest Rates are like friction: Too much and too little friction are both bad. Sames goes for interest rates too much is bad, too little is ALSO bad.

Some comments about Monetary Policy 3:

1. Debt financed Fiscal spending financed by QE: I don't agree with Ray Dalio that this was pursued after 2008 financial crisis. The fiscal spending was essentially going to the same group who could access the QE funds. Yes, there was fiscal deficit and increased fiscal spending and yes there was QE to finance it. But this is exactly the wrong kind of stimulus as I have written since 2009 itself.
2. Giving $10,000 to one person Vs $100 to 100 persons Vs $1 to 10,000 people: Helicopter money is not easy to design. The behavioral response in each of three cases varies drastically.The range of outcomes possible is mind boggling.
3. Spending conditions interfere political rights: If I am tasked to spend $10,000 can I give it to someone from my family to pay down her loan? Does that amount to spending? Should I buy something? What thing? These questions are difficult to answer, monitor and control. 
4. A little inflation is necessary: People will spend when they can surely afford it (condition above - certainty of employment and wages) and it will get costlier tomorrow. Inflation is important, zero inflation may not be that great.

The examples of Monetary policy 3.0: 

The best part of the analysis is the historical perspective Ray Dalio gives. Sharp readers of this blog will immediately note that there are fundamental differences between the conditions in various situations described and those existing now. That is acceptable difference.

Particularly interesting is the Roosevelt response in 1930s. It still forms the basic template for solution today. However, we are at a slightly different position today than in 1930s. So we have to make more adjustments than Dalio may seem to suggest. [Dalio is NOT suggesting it - it appears simple but it is incredibly complex - politically, fiscally and economically]

In Sum

Do not understand these comments as put down of Ray Dalio (as if he cares what I think!). I admire the man because he is being honest and creating a framework to solve the crisis. Good intentions and honest efforts deserve praise - even if the guy making those efforts is one of the richest.

From my side, I solved this crisis puzzle back in 2009 itself.

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What should Twitter be?

Twitter is in the news for the wrong reasons. On one hand, the subscribers growth is slowing, and profits are not up to the mark. There is confusions as to the business model and if it can ever make money. Google, Salesforce, Disney and others were mulling acquiring Twitter. I think Twitter is more valuable than even Facebook (if you ask me) and it will be a core-architecture for the social web. Here are my thoughts on Twitter's business model and how. 

[Shameless plug: The background for the discussion is my interest in business models and my ideas of firms and how they create value. The frameworks are detailed in my book "Understanding Firms: A Manager's model of the Firm" - please buy it. ;-)]

About my twitter use first

I have been a twitter user for some years now. I don't over-tweet but I guess I should be in the approximate middle as to tweeting. But when it comes to consuming the tweets, I think I am a super-user. I have neatly segregated lists and I scan them using Flipboard and Tweetdeck. I also like to share what I read on / through Twitter. You can find/follow me @rahuldeodhar by clicking my username. So let us begin.

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Tweets fall into following categories -

1. Link to content from the web - example linking to videos etc. [Sharing domain]
2. Comment on content on the web (on twitter / outside twitter) [ Commenting domain]
3. Opinion/Views about things - including witness view, etc. [Content domain]
4. Personal updates - status updates [ Personal domain]

The Twitter Stream is like a river with all these mixed up from various sources. It is impossible to make head or tail of it if you want to read it. It is like watching the river from a bridge. It is all ok for some time but is not critical - it is a leisure activity. If you really want to do something interesting with it - you can't. If you want to track trouts - well from your perch you cannot. If you are a master user you are like a diver facing the current trying to analyse the water. Whatever analysis you do is useless because the stream has changed by then. 

So that is why advertising on Twitter is so damn difficult. As difficult as it is to interrupt a diver studying water with a TV commercial. The diver doesn't dive that often, and when he does, he doesn't want to look at your TVC. It is very difficult to read the twitter stream - ads make it worse.

Twitter is like a monologue for most of the people, most of the time till others start commenting, sharing and you start getting reactions (not the button based reactions but real comments). Then it becomes interesting. If you are too popular, it turns nasty (sometimes) and resembles a bar fight or a cake fight from Charlie Chaplin movies.

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But Twitter can become more relevant

Twitter can become the default commenting engine of the web - become disqus++. Twitter sits at the junction of comments and sharing. This is win-win for websites that generate comments as well commentators and for twitter. If someone is posting a long form comment, the first 140 characters will only form part of the tweet. This will force people to summarise their comments and it will be easier for authors and really interested parties to parse the detailed long-form reply at the web-page itself. [swelling the stream]

It can also become default Reviewer of choice. Reviews are essentially comments to something - either product, services etc. Ease of being able to pinpoint what we are reviewing remains a challenge. So say when you are reviewing a Phillips table lamp should it be tagged to product page in your country or to product page of Phillips international - well those things is what Twitter R&D spend of $800m should be used for. It can substitute product reviews in amazon, sites like good reads etc. [swelling the stream]

But it may be better to avoid hosting content. A few good things Twitter has done is to integrate photographs and videos into the stream. Twitter can choose to partner with YouTube and Google Photos or say Flickr for it or it could go on to become a content development platform - like medium (say). To me, there is value in letting content reside with YouTube or Flickr and using the Tweets itself to gather data. There are many arguments as to whether sequestering content behind login walls is good or bad. (Facebook likes it, google is fairly open). I prefer open architecture. It is like building cities v/s building walled communities - cities are much nicer. [swelling the stream - though not too much]

If you note carefully, Twitter can address two strong models - create once publish everywhere (COPE) and Diverse Information Sources in one stream (DISOS). I concocted the last one so apologies if it sounds clumsy. While the first allows easy of creating content, second allows ease of consuming content. Remember for advertising models consuming content is important. 

Twitter also need to universal Tweeting, specialised Stream reading. It already has universalised tweeting. You can tweet from any app/webpage etc from phone or computer. Or you can go to the Twitter website or its app and tweet from there. I use the Twitter website / App for reading the stream rather than tweeting itself. But reading is cumbersome. Tweetdeck is one way of segregating content based on usernames and hashtags. But even Tweetdeck is difficult to parse. Flipboard is easier to parse but a  bit weird in formatting. Twitter needs to develop apps that help user read the twitter stream better. [Reading the stream]

Twitter stream-reader, must complete the information picture the way Microsoft's Photosynth compiles the photographs from various sources. Twitter is it's information equivalent. If I pivot the twitter stream on a person, it should give me the subject-clustering of tweets of that person. If I pivot the twitter stream on a topic, it should people-cluster the tweets into groups - my followers and within that based on my lists. In both these views we should have ability to go back at least one day (for consumers). [Reading the stream]

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How to Generate Revenues

Twitter has been a platform of choice for news-dissimination. Twitter must take it to its logical conclusion. Twitter can replace the newswires - all of them in one go. For this, Twitter needs to use pre-identified usernames. It already does that with verified accounts. It will need a customised App for distributing and reading newswires. I cannot see why it cannot be done. By itself newswire business is about $3-5 billion with possibly about 12-14% profitability. For twitter, it may be more profitable. [separate newswire business]

Twitter based News channel is also a possibility since the news is there in the stream, videos are there and you can combine those using pre-selected usernames (handles) and tags. It can set up programming automatically just by relevant people tweeting about it. Facebook and YouTube have started live video dissemination, but in a stream they make no sense. But curated videos allow you to create topical channels. Twitter should also be able to hash YouTube existing video library into a proper playlist of sort. Advertising through this will be easier. [reading news stream]

Twitter Stream-Reader Pro can be a fully loaded stream-reader that can help clients get easier view on the data stream in terms of their relevance. Imagine Ford Mustang Twitter Stream-REader Pro (FMTSR Pro), it will read the streams about Ford Mustangs and then give you detailed analytics. If I was Twitter, I would hard code "Ford Mustang" into the this FMTSR-Pro and charge Ford for yearly use. The same App with modified hard codings can be deployed for others say Lego. For Glaxo or Pfizer it can drill down doctors and non-doctors into the categories. Twitter currently does sell the stream analytics but the revenues from that is quite low - about 10% of the revenues. I would presume it should account for 80% of the revenues. So there is a lot of potential in this. [ corporate stream reading]

Customer Service Pro can mine the stream for companies listen for customer complaints and engage the customers using DM. This can be even now but I can see Twitter being able to add analytics to aid the customer services. Personally I had super experience from Hyatt who solved my problem through twitter. From then on I personally air my grievances on Twitter so that if any company is listening then I can get help quickly. Indian ministers use twitter to solve emergencies - Railways and External Affairs ministries are quite active. I presume companies would love to use Twitter to solve their customer's problems. This function should ping companies when a customer tweets about bad experience he is having with the company. It should allow the companies to set criteria as to when alerts are triggered from the stream reader.

Twitter Topic Tracker can be a reader that tracks specific topic - say wind surfing, pottery or something. At present users have to create the lists as per their own specification and these lists can be public. The problem is in a list of economics we get general tweets (say happy birthday to my daughter) by economists but miss the economics tweets by other people who are not in the list. There should be some way of fixing this. Advertising in the viewer of this Topic Tracker will be more relevant and therefore more lucrative and sensible. [ to curate better advertising]

Twitter can create publicly sourced Subscription Magazines just like Flipboard or Paper.li with relevant tweets compiling into readable magazine. Twitter can take share of these subscription through a twitter-owned store and distribute subscription to contributors (original and those sharing them), using some acceptable equation. (So content creators take 75% of the revenue based on reads, clicks, shares etc. the individual share of creators can vary While those sharing get 1% of share of the content creators and Twitter takes 20%). Using the stream, Twitter can compile edited-book like special editions giving complete spectrum of opinions on selected topics. There can be advertising within these magazines and revenue sharing with content creators. So for example, Twitter can compile a special edition on "Manufacturing Policy" or "Dodd-Frank Bill" by experts and add value to the journalistic discourse. [content curation and advertising]

Twitter can also give a Event Live-view using tweets by general public (those by reporters go through the wire I am presuming) and create a Stream reader view that gives overall picture based on live tweets as to what exactly is happening. This might require integration with AI algorithms to parse value of information shared by a particular Tweet. Currently, search results that give "top tweets" tends to tell us this but it needs improvement. [Stream Reading] 

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Now with all these developments, I think Twitter should have been more valuable to news websites. It is indeed sad that Twitter cannot monetise itself better. In the present post I did not want to consider the operational parts of Twitter strategy because John Hampton has already considered them in his two fantastic posts Some comment on the Twitter buyout rumours and here Measuring how bad Twitter is. I hope Twitter heeds them. John Hampton is seldom wrong. Fred Wilson and Union Square Ventures were early investors in Twitter. I hope they understand the possibilities and take corrective actions.

 

Disclosures: I have no investment in twitter. 

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Why is resolving Non-Performing Loans (NPL) is so difficult?

The management/resolution of NPLs has acquired renewed focus with banking sector under stress for many years. The Economist comments on it this time about Italy's NPL problem. More significant is the commentary on various approaches, IMF recommendations, KKR's Pillarstone initiative etc. making it a must read. But it misses some quite important issues with respect to NPLs in general.

Failure of NPL liquidation - some blame lies with Accountants

The PwCs, EYs, Deloittes and their ilk must take some blame. Many of the bad loans have accounting folly at its heart - some deliberate and some not, some before loans are made and some after. Time and again, accounting firms have washed their hands off their audit responsibility and liabilities arising therefrom. Recently some firm has sued PwC for their failure to report material issues. If auditors completely trust the company managements they are auditing, then the purpose of the audit is not satisfied. 

The shady entrepreneurs

The proportion of shady, shifty characters in this distressed assets pool is quite high. Some distressed loan assets are deliberately impaired on the books for tax fraud or money laundering. Data mining algorithms cannot detect this - even analyst cannot easily detect this. Such frauds have to be sniffed out - at least till Artifical intelligence becomes more robust.

Slow courts and costly Alternate Dispute resolution (Arbitration, mediation etc.) mechanisms

Invariably, a fair proportion of the distressed asset pool goes for legal resolution. NPL problems are higher in countries with weaker judicial controls, higher cost dispute resolution. The process of dispute resolution quickly unravels both the ability to pay and gives a remarkbly clear insight as to the intention to repay. However if the process is too slow and too costly, it defeats the purpose. This is a problem in Italy and also in India.

Much blame lies on Incompetent Banks

The substantial blame though must lie with the bankers:

1. Lack of accounting analysis skills: Many banks which make loans cannot make proper assessment of accounting statements. Data mining algorithms are good at assessing the "ability to pay". They cannot assess the "intention to pay". Lack of Intention to Pay has created many NPLs.
2. Illogical the use of collaterals: Banks are notorious in having collateral that is highly correlated with loan asset itself, over-valued or pledged in part to many. This is a childish mistake to make for a professional setup. At times, an intellectually superior form of syndicated lending (the whole syndicate holds one collateral) is used. When trouble strikes the legal disputes arise within the syndicate itself. 
3. Poorly-constructed contracts with borrowers: Such contracts make the payments unpredictable in quantum and timing thus surprising the borrower. It quickly cascades into penalties and surcharges and it goes downhill from there.
4. Too Centralized decision making as to loan eligibility: Most borrower eligibility tests are done centrally these days. Thus it leaves no incentive for the bank manager / officer to dig deeper into the borrower's records. It makes the incentives wrongly aligned.
5. Flawed loan portfolio construction: Loan portfolios are too correlated This is a result of too much market focus. Banks push certain products that they find easy to sell - consumer loans, credit cards, personal loans etc. When the lending starts concentrating they do not quickly take corrective actions to balance the portfolio. If the banks' entire portfolio comes under stress at the same time, it cascades into more distress.

Basics of borrower assessment

Any borrower assessment has two component - ability to pay AND the commitment or the intention to pay. Sometimes the last two differentiated. The ability to pay is well understood which refers to  the capacity to bear the repayment of the loans. The intention to pay tries to determine if the borrower intends to cheat or not. The commitment to pay points to whether the borrower intends to pay  but disputes the computation of the payment and hence may have withheld the payments - committed but not paying, or the borrower does not intend to pay at all and is finding loopholes to delay the foreclosure process.

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Is assessment of risk a function of interest rate?

The interest rate that can be charged by the bank has  two limits.

The Lower bound equals what the central bank charges the bank. Any lower and the bank will make a loss on its lending portfolio.

The Upper bound is the ability of the risk taker to bear the burden of return. Thus, if a bank lends to a business that makes 10% return on capital employed - it cannot charge more than 10% else it will be unviable for the borrower to seek the debt at all.

The Actual interest rate charged is determined by a combination of the following factors:

1. An assessment of returns of the business based on the economy and her business 
2. Income of the borrower in total 
3. The value of the collateral pledged against the loan as a security should the borrower be unable to bear that return 
4. The demand for loans AND/OR
5. How well the other loans are doing (health of bank's loan portfolio) AND/OR
6. A combination of these along with global factors

Spread

Bankers think of returns as spread they make on top of the lower bound, i.e. rate set by the central bank. 

Risk V/s Spread

Now, in the mind of the banker risk is correlated with the spread. When the banker perceives higher risk she fattens the spread. This "risk" we talk about is risk resulting to the banker. It does not mean risk of the borrower alone. So if the bankers' portfolio is turning bad, the banker will still increase the spread - partly to compensate for the loss she suffers and partly because she assesses the general economic environment to be more risky. Thus, even if the central bank reduces the benchmark interest rate, the banker is reluctant to pass it on if she can avoid it. This creates tighter conditions putting more stress on the borrower. This is why Scot Sumner argues the monetary conditions were actually tight when we were almost at ZIRP.

In an economy that is weak, it acts as a stronger head wind for borrowers. It reduces their ability to borrow and to service their current borrowing. They want to pay down their debt and reduce their loans. Therefore, the economy contracts further. The banks seem happy at first, but soon realise that other borrowers who are not prudent are pushed to default. The implication of this on the bank depends on the mechanics of the process - the proportion of those who default v/s those who pay back, the chronology in which it happens etc.

In the next phase, the economy recovers, predominantly with equity capital. Equity can absorb the losses since it is built for higher risk. The surviving firms and individuals are left with core strength to  thrive in intense competition and are more prudent with capital allocation. The banks thereafter can lend to these survivors to help them scale up.

What does this mean?

This means, 

1. There is inherent value to competitiveness that signifies its ability to survive and repay the debt and repay the equity at decent returns. This ability reduces with increasing leverage by the borrowers. Thus when Anat Admati suggests investment banks have capped leverage ratios to 20 or 10 it makes sense.
2. Banks' business model seems to encourage the use of debt only to amplify equity returns. It is fine in a way but if that is the objective then banks should reduce/cut lending at lot earlier than they do. Naturally, in times of distress when the return ON capital matters lesser than the return OF capital, banks get into big trouble. It seems they get confused about what is their business model. 
3. Maybe, better than ZIRP, unleashing a new Government-backed Good Bank to pick up assets at distressed prices at lending rates with narrow and fixed spreads can work better. If the size of this bank is large enough in relation to the banking system, it may result in a lesser shock to the economy.

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Of Free drinks and negative interest rate policy...

If soft drinks (Coke/Pepsi/tea/coffee etc.) were freely available would you tend to have more of it? Often I end up having one extra coke. If its tea/coffee I end up having even more. I will have to work it off that day through exercise or it will cause some harm in the long term. 

Zero interest rate policy (ZIRP) is like that - if you already wanted Coke and it was easily available you end up having a little more Coke. Likewise, if you already wanted debt, and it was easily available at almost zero cost, then you will have a little more. But not a lot more - coz you have to work it off.

But what if you don't want them?

Say your doctor told you to not have soft drinks at all - no tea/coffee too. Now will you have that? NO? Even if I give you some money - say 2 cents - to have these soft drinks? Still NO? 

Well, me giving you some money is similar to Negative interest rate policy (NIRP). Or similar to one aspect of NIRP. You get a tiny advantage if you take on debt. Is it that difficult to understand why it doesn't work as central bankers hope?

But may be NIRP could work...

Now some will agree that ZIRP may not work, but, they say, NIRP could work. They point to the second aspect of NIRP which is that if you save you get taxed extra. Now if I have $100 in cash in a bank, next year I will have only $98 so next year I will be able to spend less than I can do today. Isn't that an incentive for spending now rather than next year? I say not always!

There are a few reasons:

1. If the trends are deflationary your $98 next year may be able to buy as much as $100 today - sometimes even more. If the efficient market hypothesis* were working prices would adjust to reflect the new purchasing power. NIRP would create some deflationary force as well. Yes, it is small but it is deflationary never the less. So unless the NIRP was creating an overwhelming inflationary force, it may push a precariously balanced economy into deflation. 
2. The NIRP tax does not affect those paying down an earlier debt. In fact, it encourages people to swap new debt for old debt. Debt repayment helps you avoid the tax. This is even more deflationary.
3. NIRP does not work if I anticipate unpredictable cash requirements - say because I want to keep some money to invest when prices correct, or I think my business loan may need to be repaid if my business does not do well in next quarter, or I expect health care costs etc. In fact, it works reverse - in such cases, I would be encouraged to save $102 or $104 just to keep a buffer.
4. NIRP may push those with huge cash balances to move cash abroad. Do you think Apple and Google will bring that extra cash into a country with NIRP? No way! They might move it to a destination where it will be easier to hold cash. So is this what you want to happen? NO! Who gets affected is the individual who keeps getting taxed extra.
5. I may not want debt or I may not want to spend at all. I have the clothes, I have the phones, computers, TV, house, car, swimming pool etc - all the goodies I can spend on when you nudged me to spend the last time. Now I have mostly everything I need. So why should I spend on something I am not excited about? Beats me!

* I don't think Efficient market hypothesis works on a "point-in-time" basis - though it works on an average basis.

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Hussman's timing may be wrong again!

John Hussman predicts epic stock crash in his recent newsletter. He says:

The financial markets are establishing an extreme that we expect investors will remember for the remainder of history, joining other memorable peers that include 1906, 1929, 1937, 1966, 1972, 2000 and 2007.

He follows up with another gem:

Enlightened members of the FOMC should even question the theoretical basis for their actions. The Phillips Curve is actually a scarcity relationship between unemployment and real wage inflation – basically, labor scarcity raises wages relative to the price of other goods (see Will The Real Phillips Curve Please Stand Up and the instructive chart from former Fed governor Richard Fisher in Eating our Seed Corn). That’s the only variant of the Phillips Curve that actually holds up in the data, and there is no evidence that this or other variants can be reliably manipulated through monetary changes.

Only long-term sustainable, predictable employment creates a turnaround. Till this I agree with him. Now comes the crucial issue of timing. Here he says:

They want to believe that the Federal Reserve has their backs; that as long as the Fed doesn’t explicitly hike interest rates, the market will move higher indefinitely. We saw one question last week that asked “What if the Fed doesn’t raise rates for another 20 years?” Let’s start with an aggressive, optimistic estimate. If we assume that despite conditions warranting two decades of zero interest rates, nominal GDP and corporate revenues will grow at their long-term historical norm of 6% annually over the coming 20 years, we would expect the total return of the S&P 500 to average about 5.5% annually over the next two decades (see Ockham’s Razor and the Market Cycle for the arithmetic behind these estimates). Even in this optimistic scenario, to imagine that this path would be smooth would have no basis in history, requiring the absence of any external shock for the entire period (and I’ve already demonstrated, I hope, that many of the worst market declines in history have been accompanied by Federal Reserve easing).

If Fed hikes, it will interfere with the risk equation causing "a breakdown in market internals" as Hussman calls it causing precipitation. But it is unlikely that Fed will hike. Fed may experiment with a token hike but may quickly reverse. Or, more likely, Fed will signal a prolonged pause (lasting more than a year or two). 

If Fed does not hike, things won't be as simple as 5.5% annual growth. It will be more. The past data behind this calculations comes from low monetary expansion era. When there is a flood of money, prices should inflate commensurately. Thus, if Fed does not hike,  S&P may average annual growth of ~10% or more for few years. 

Hence, S&P may double from here before Hussman's prediction comes true. We, no doubt, are establishing an extreme. We are confounded by its extremity.

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What we need to estimate effects of multi-country QE?

I was thinking about ways to estimate impact of QE on potential offered by different equity markets in general or asset markets in general.

Currently we do not have money inflow metrics (i.e. indexed price and volume data) for all asset classes. Nor do we have an exhaustive asset class database (types of asset classes e.g. art). Without these metrics it is difficult to construct a true impact of QE on global markets in general and specific markets in particular. Maybe someone can construct some sort of blended index.

I suspect when we do construct some quasi-indicators we will find that M3 has grown disproportionately with GDP and the difference can be explained by blended asset class inflation.

Once the global effect is understood, the specific country level effect can be understood using a parametrized gravity model. Such model will tell us how the excess liquidity will move. 

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Yen Vs. RMB - China crippling Japanese companies?

Yves Smith asked "Has Chinese Currency Manipulation Succeeded in Breaking Japanese Manufacturers?" bringing out the effects of currency management. You can read the sorry strategic choices facing the Japanese regulators.

China is buying yen forcing appreciation that renders Japanese companies less competitive. China is also buying Japanese bonds. Now Japan must buy US Dollar to keep their exports competitive. Now, both countries are dependent on US/EU/developed world demand and hence they are fighting amongst themselves to capture the reducing developed world consumption share.

This is a problem you face when the market country undertakes QE. The supplier country has no choice but to undertake its own QE without which it suffers loss in competitiveness. The quantum of QE the supplier country must undertake is not merely equivalent to QE undertaken by market country but must also adjust for QE by other supplier countries and relative competitiveness between suppliers inter se. Thus, the supplier countries must do a lot more and therefore must face correspondingly lot more risks.

Thus, my advice to Japan would be to print till balance is restored. (This is not my optimal recommendation but I believe this will be best way to achieve their intent.

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Dow Jones Industrial Average since 1900

Barry Ritholtz links to this awesome chart from J.P.Morgan. It tells us so many things when you look at real long term. Have a look and my comments are below this:

The graph tells us so many things:

1. Before anything else, I must highlight that the average line for 1937-49, 1966-82 and 2000- present are drawn wrong. They have a positive bias. 1906-24 seems to have a negative bias.
2. More importantly, we seem to have ~20 years of stability and ~20 years of secular bull runs. By that measure, somewhere after 2015 we will see the start of the next bull run.
3. But we must correlate these with actual developments. If you draw some key developments on the charts we will see better picture. 
• Periods of technology development
• 1930s and 1940s period signifies the development of US highways and railroad. This is phase where Americans were still exploring new frontiers within their country.
• Similarly 1966-82 period was time when computing technology was taking shape.
• Similarly, 2000- present internet technologies are taking root.
• Productivity increase periods. These periods are different from technology development periods. Here known technologies are being exploited to create new thresholds for efficiency and productivity. Concurrently, new technologies are being incubated but those are not the dominant forces as yet.
• 1949 onwards was post war reconstruction. Here known things were required to be produced in ever increasing numbers to satisfy the demand in Europe and Americas itself.
• 1982 till 2000 was a period when IT came of age. Computing allowed wider management control, better designs, higher efficiency etc.

Overall quite an interesting chart. What do you think?

update: I made a appalling mistake of commenting on exponential line which I have deleted. The graph is in log scale.

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Explaining Indian Policy Paralysis

A lot of recent comments, including mine, have pointed out the lack of policy commitment from the government. I believe there is a reason to this policy logjam and it may reverse quite quickly, to surprise of many, making the current time most critical time to invest in the country. To warn this is a conjecture.

1. Indian politics has undergone a change of mechanism in financing. A significant (non-trivial) percentage of money deployed in politics comes from stock markets where it remains invested in distributed accounts. 
2. This implies that the stock markets must have a good peak about a year before the election. Year being the approximate time required to oil the election machinery of the political parties.
3. This also implies that there should be a good opportunity to invest around 2 years before the election without which the peak referred above will have no meaning. 
4. Political money is gained from rent-seeking and corruption and not invested in first three years as it is being collected at that time. It is usually available around 2 years after new government takes office, the bulk being available around 3 years time. (term of government = 5 years in India)
5. Insiders inform me that Late Mr. Pramod Mahajan (parliamentarian of BJP) was amongst the pioneers of such strategy around 2002-03. Subsequently ruling party Congress, inducted relevant talent into this strategy. Some say, former finance minister P. Chidambaram, known for his investment sense, may have used this means earlier. Though I have heard conflicting reports that state branches of parties in South using similar means since 1998-99.
6. While earlier efforts benefitted from a global bull market, current efforts require ingenuity to create returns in an adverse global macro environment. 
7. I hear that ruling party has taken an ingenious approach to current problem. The first phase of the strategy is to create policy misdirection, increase rhetoric and in general cause panic and injure investor sentiment (only enough to create a equity market). The second phase is to establish policy direction and build credible reform base that should lead to uptick in equity markets.
8. The magnitude of money involved is not small. Even small district magistrates have wealth in excess of INR 50 million. Politicians have access to money in excess of INR 200 million each. There are tons of them. However, substantial amount of this money is in black (cash not accounted or declared) and thus cannot be funneled into the equity markets. However, the numbers are mind-boggling.

Thus, I expect:

1. Reform process to gather steam from current levels.
2. Increasingly positive policy news of reform and clarity coming from governments.
3. In general improving investment climate.
4. Proactive and improved response from government to cushion or even counter negative news coming from global economies.
5. Government may talk the market up.

Implication for Equities:

1. I believe this current level is a bottom for next year or more.
2. From this point we will move up is a sustained manner till beyond March of next year (around).
3. At that point we may see a sharp correction as money starts being pulled out of the markets.
4. So, this is time to be long India and get out by March next year.
5. Risk is that if all start working on the same strategy exit needs to be critically examined.

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My book "Subverting Capitalism & Democracy" is available on Amazon and Kindle.

Deploying Public Assets (spectrum, coal blocks, etc.)

One of the important functions of the government is to deploy public assets for public gain. However, selling these assets or renting them has landed many a government in a soup. Be it the mill-land fiasco in Mumbai, spectrum auctions for 2G or coal block allotment, governments seem to fumble at every step. And this is not the only problem with deployment of public assets. Let us look at problems and solutions to selling or deploying public assets in the interest of public.

The problem with deploying public assets
The process of deploying public assets is difficult. Inappropriate deployment usually turns into allegations of scams and threatens the political order.

1. An infant nation is compelled to deploy the assets it owns in a legal environment that is not yet sophisticated and evolved. Thus, such a nation is faced with immediate prospects of inappropriate deployment and therefore political disorder.
2. Asset deployment theories themselves are still evolving. Thus, the jury is still out on whether renting is better than sale of assets in conditions of uncertainty, how long should lease durations be,etc.
3. The asset pricing mechanism is ill-developed for untested or new technology. Here, it is difficult to estimate the present value of the asset. These new technologies are sensitive to choices and, in scientific parlance, to initial conditions. thus, what may be a good technology elsewhere,and therefore priced at premium, may become a failed idea at high costs. In such cases it is nearly impossible to estimate in advance and accordingly price such assets.
4. The question of opportunity cost is of prime importance. If I sell an asset to a firm and the firm does not develop it but simply sits on it. That may be advantageous for that firm but it defeats the purpose of sale of assets by the state.
5. The risk being taken in new development must be paid for. In other words, when the entrepreneurs bid for a technology that has not established itself, they are taking risk. If the government starts demanding higher initial payments, the entrepreneurs' risk is amplified resulting in under-developed sector. A better way is to let the initial payment be lower while gain from profit sharing or revenue sharing mechanism.

Two types of asset sale problems or mistakes
Even when there is no corruption, there are two types of problems or mistakes government can face or make with asset deployment. 

1. The government sells the asset at lower than market value thus resulting in loss for the exchequer. This is usually because the government cannot value the asset correctly. Alternatively, government is advised to "leave some value on the table". In all these circumstances, the exchequer is the loser. 
2. The second type involves selling the asset at market price but to someone less qualified or simply, preferring one buyer over the other. Here the problem is not for exchequer directly. Here the shareholders of the company denied the asset end up losers while those of winning company gain windfall profits. It is possible that the preferred buyer may not have technical capabilities to effectively deploy the investment thus resulting in second order loss for exchequer. 

Out of the two types of problems with asset deployment, first is detrimental to the exchequer but the second is indifferent (at least directly). It follows that the level of tolerance for first type of mistake should be lower than the second one.

Types of Asset pricing
Asset pricing depends on various mechanism for cash flows and availability of asset itself. 

1. One-time sale - this transfers public asset to private ownership: This involves higher risk to government as the real value of the asset may not be correctly assessed at the time of sale. However, once sale has concluded there is not much that can be legally claimed from this type of transaction. 
2. One-time payment for right of usage for few years and renegotiated every few years: This is capitalized rent and the value of this changes as perception of risk changes. The risk involves depends on what the asset is and how long is the first lease period. E.g. Mumbai Mill lands have been leased to companies on 99 year leases. Recently 99 year period has expired but the ownership of those lands has not reverted back to government.
3. One-time license-fee payment followed by share of revenues/profits: Here the one-time component is lesser to account for untested risk that entrepreneur must take. Thus, this option is less risky for entrepreneur as well as government. There are sub-categories within this option depending on where the government takes its cut - at revenue stage or at operating profit stage or net profit stage.
4. Only share of revenues or profits: Technically Taxation achieves this effect either through general tax or specific industry based levy, either in the form of excise, cess etc.

The first three methods are used where the asset is scarce (usually resources like spectrum, mines, land etc.). The fourth method is used for everything else.


Structure of Corruption around these problems
Corruption is structured around these potential problems to aggravate the loss to exchequer. Following problems occur generally:

1. Asset is impaired and sold thereafter: Impairment can be positive act or negative acts. Positive act means the asset is deliberately impaired wherein losses increase and asset appears hopeless. A negative act means allowing the asset to degenerate without actively doing so.
2. Mechanism of Asset pricing is changed midway: Here the original intention of pricing the asset is ignored. First, the asset is priced lower to encourage investment by lowering the risk in the asset deployment. Thereafter, an argument is evoked at the deployment is only profitable at such low prices and hence the asset value is actually low. Thus, Mill lands went from following method 2 above to method 1 without commensurate payment.
3. Concessional rate for PSU buyers: In this form the government allots a public asset to a public sector undertaking (PSU) company. This seemingly benevolent act can be hideously corrupt. Unless the PSU is 100% owned by the government, it is reducing public gain and has same effect as selling the asset at throw-away prices. A PSU in receipt of such asset must not complain if the government caps the prices of the end-products it produces.
4. Concessional allocation to PSU and subsequent divestment: This is modified part of third problem in which asset is alloted to a 100% government owned PSU and thereafter the ownership is divested. This buries the asset under the PSU performance and makes it less valuable to lay-person. 
5. Asset Valuation is not proper: In this case, the sum-of-parts value of the asset is higher than the asset itself. Thus the parts must be valued appropriately. Thus the land owned by a specific PSU that is divested may be of more value for other use than for use of PSU itself.
6. Profitability Estimation is impaired: This form works with assets like airports and roads where the right to collect toll or charge for services is leased to private entities. Recent experience suggests the estimation can go wrong in both ways as has happened in toll-roads and airports privatized recently.
7. Arbitrarily choosing pricing mechanism for two similar assets (Inconsistency): For reasons unknown, without effecting a policy change, government allots one asset in one manner and other using different pricing mechanism.
8. Granting asset to unqualified buyer: When asset is granted to an unqualified buyer who sells the license to other party at substantial profit, there is ground for doubt to believe that asset is underpriced and opportunity exists for arbitrage trade.

Note: The list is not exhaustive as people are infinitely more creative than anyone can anticipate.

The solution
The real solution is not a model for asset pricing but one of transparency. 

1. Conservative approach: I believe, from the exchequer's point of view the risks associated one-time outright sale are quite high. Instead, a non-trivial license fee in addition to share of revenues forms a better alternative. It allows for future adjustments of asset value and exchequers share in the same.
2. Transparency: If the process is transparent and mechanisms are fair, there is not much corruption that can happen. 
3. Changes to reflect true assessment of changing value of asset: If it so appears that initial payments were underpriced, then subsequent revenue sharing could be raised and net effect can still be adjusted.
4. Consistent changes: Any policy driven choice must be applied consistently. Thus if government chooses auction method then auction should be followed everywhere. If First-come-first approach is used it should be used consistently and fairly.
5. Principles of natural justice and equity: Any solution accepted by government must abide with principles of justice and equity enshrined in the constitution. Thus, if all qualified parties are given equal opportunity to bid for asset, there is not much scope of corruption.

In Sum

The focus of asset deployment is to get best value for the asset being deployed for public interest. The duty of the government is to deploy public assets for public gain. So long as basic principles are adhered we can have a flexible system that can account for past mistakes in an on-going manner.

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My book "Subverting Capitalism & Democracy" is available on Amazon and Kindle.

Sticky Wages, Prices and effects of pouring money

Scott Sumner has a post about pouring of money - i.e. effects of expanding money supply. He disagrees with the metaphor that money pours into certain asset classes. While I agree with the principles behind Scott Sumner's post, I find most of times the metaphors send better signals for interpretation. But my main point is about prices and wages.

Prices and wages are embodiment of information - historical, present and future. If they change too quickly then the historical aspect is lost. For better or worse, our scale of value are anchored to the past. It does get influenced by present and to a less degree by expectations of future. But if we lose our anchor point or the reference scale then our mental models collapse and we lose our sense of reality. Thus, if we get paid $30,000 in year 1, $3,000 in year 2 and $3million in the next year, we will develop a sense of confusion.

Then comes the question of pouring. What pouring refers to is change in the relative value of asset classes. Imagine a spread of assets along a value spectrum, sort of a hierarchy (with sometimes assets jointly occupying a hierarchal position). 

If money increase does not modify the hierarchy then it does not impact much. If it does then it creates gainers and losers just because money is created. For example, if a really thirsty person would rather be just under the tap than away where water will eventually get to him. 

The argument therefore is whether the government or central bankers be allowed to create such distortion that has no grounding of productivity or real value creation.

One can argue that over long term the asset hierarchy goes back to a certain mean. But during the time a distortion is set in motion and the time we get back to time-tested mean we can extract advantage. Finance is prepping to do just that.

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My book "Subverting Capitalism & Democracy" is available on Amazon and Kindle.

Forecasting equity prices in turbulent times

The markets have been very volatile over the past few years. Investing in these times has been fraught with risks. In such a market, it is very difficult to make investment decisions based on valuation models. Almost always these models indicate that stocks are over priced. Equity fund houses are adding to the confusion with their near-random buy-sell ratings. There seems to be little logic behind these recommendations.

However, there is a method wherein we can logically explain the variations in valuations. We can look at equity prices as composed of two components, a value component and an asset inflation component.

Value component can be expressed as a price band based on fundamental assumptions. The output of most models is usually a price band. These assumption are dependent on the company and economic situation. As we tweak these assumptions for a base case, bull case and bear case we end up with a price band. The price or value is based on various valuation models such as sum-of-parts, residual income, etc. Normally, prices should vary within these bands and the inflation component should be bare minimum. However, in recent years the prices have moved out of the valuation range.

The movement is because of asset inflation because of the high liquidity being pumped into the market. Those are not the only reasons and each market has a different variables that influence the asset inflation for that market. The role of equity analyst, therefore, also includes forecasting the expected asset inflation. From a first principles, in a market influenced by foreign capital flows, average daily volume should be a good indicator. For example, in India, the asset inflation component for large cap stocks with high volumes could be to the tune of 35-40%. For mid-caps or firms out of favour the range may be 20-30% while small caps may have inflation factor of 10%. As the global picture changes, the macro analyst can thereafter adjust the asset inflation component at the country level. I believe this is a better way to present equity research prices.

Let us take an example.  Let us say that the value component for stock like Bharti Airtel comes to INR 300 per share. Now telecom as a sector is a little out of favour and the inflation factor for Bharti Airtel would be lower than usual 35-40% for large-cap stocks. Let us say it is 20-25%. Therefore, the expected price range for Bharti Airtel will be INR 360-375.

Disclaimer

Long Bharti

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My book "Subverting Capitalism & Democracy" is available on Amazon