Words ought to be a little wild, for they are the assault of thoughts on the unthinking
- J.M. Keynes

Sunday, 23 October 2016

Who's winning the Brexit game?

My latest article on Brexit published in Mint this Sunday which takes a slightly contrarian tack to the reports and opinion pieces grabbing the headlines.

Only the opening moves have been made on the Brexit chessboard but judging by the reaction from spectators, the UK is inexorably heading towards checkmate by the EU. The Bremoaners have seized on the less than sterling performance of the British pound as proof that the armageddon they predicted is not going to be long in coming.

The post-Brexit fall of nearly 19% in the pound and forecasts of another ~10% decline have been spun as evidence of a weak position. The recent wild swings have added to the sense of unease and have led to calls for Prime Minister Theresa May and her government to sue for an honourable draw.

However, focusing on the gyrations of the pound is akin to looking at the clock in a chess game. Screaming that it is running down is factually correct but completely useless. Moreover, it detracts from focusing on the board and coming up with a winning strategy.

As with any price, that of a free floating currency in forex markets depends on demand and supply. Simply put, demand for the pound comes from exporters, tourists, UK residents earning foreign income and foreign investors. Supply comes from importers, UK citizens going abroad, repatriation of earnings by foreigners and UK investors investing abroad. While speculators tend to weigh in on one side or the other based on their beliefs about future demand and supply, over time the price is determined by non-speculative flows.

Therefore confusing a weakness in the currency with a weak position on the Brexit chessboard is a mistake for three reasons.

First, rather than being the “de-facto opposition” to the government signalling wrong policy choices, a falling pound is a great ally by making the UK economy more competitive and allowing it to rebalance.

The strength of the pound over the past decade and a half was primarily due to capital inflows into the UK as foreigners bought UK assets (e.g. property) and London took on a central role in the increasing financialization of the global economy. (As Ashoka Mody, a former IMF deputy director, points out, a strong pound actually made the British economy more fragile. By encouraging the FIRE sectors—finance, insurance and real estate—and discouraging manufacturing it inflated a “finance-property bubble”.)

The share of finance and insurance in gross value added (GVA = GDP - taxes + subsidies) for the UK went up more than 4 percentage points between 2001-09 and at 9.7% in 2009 was significantly more than the other G7 economies (figure 1).

Figure 1: Share of finance and insurance in nominal GVA
This acute dependence on finance was catastrophically exposed during the credit crisis. Further, the post-crisis reversal in global economic financialization was bound to affect the pound negatively. In fact it stayed ~25% lower from its pre-crisis levels, reflecting the new reality of a more constrained financial sector.

By injecting greater uncertainty on the continued role of the UK in the global financial sector and on trade and economy in general, Brexit has caused a short-term decline in demand as foreign investors reassess the situation. The consequent repricing has been exacerbated as speculators lean against the pound, anticipating prolonged low demand and increased supply as some investors rush to exit.
However, the fall in the pound has not only made British exports cheaper, services of British lawyers, consultants and other professionals have also became more competitively priced. For example, the call-centre labour arbitrage just reduced 15-20%. Are firms going to go to India, or set up shop in the Midlands?

Moreover, following through on threats to relocate post Brexit became more expensive for firms. Yes, the flipside is that imports are more expensive but in a deflationary global environment this is likely to be contained. Moreover, the expected inflationary dose is what every developed market central bank is trying its hardest to deliver without much success so far.

By curtailing import demand and spurring exports, the falling pound reduces the current account deficit, which reached 5.4% in 2015, the highest since records began in 1948.
It will further help by redirecting UK domestic tourism within the country and attracting foreign tourists. All of these effects are likely to create jobs in the non-financial sector and will directly benefit the Brexit-voting constituency. In the side game, grandmaster May has checkmated opposition leader Corbyn even as his party flails around screaming at the clock.

Second, spinning the pound’s weakness as a consequence of poor government policy is an error and obfuscates the UK’s true position in Brexit negotiations. Here, May has made all the right moves.
In the age of Twitter, the British government has stuck to its guns on providing only appropriate disclosures rather than a detailed running commentary. This not only prevents the European Union (EU) from being forewarned and devising a counter, it also allows a smoother process without every small detail being blown into a major bone of contention.

Moreover, it gives greater room to negotiate compromises without fear of screaming headlines about backtracking, losing face, etc. Of course, parliamentary disclosure is essential, but parliament is not expected to co-draft legislation, nor is it expected to be party to every government decision.
May’s announcement to trigger Article 50 by end-March 2017 was an inevitable and essential defensive move given pressure for clarity from the EU and within her own party. Triggering the article will give the EU the advantage since negotiations must complete in two years and the EU can wait it out.

However, May and the government’s publicly stated willingness to prioritize border control over access to the single market has neutralized this advantage even before the event. The move has generated huge controversy and has not been helped by some exceedingly idiotic proposals by May’s team. To paraphrase Lord Acton, by tilting towards populist xenophobia, the Tories are giving opponents just grounds for opposition and kindling dispute within the country. This is illustrated by Nicola Sturgeon’s renewed call for Scottish independence, which latched on to the real and imagined stream of xenophobia running across the Tory conference. 

However, rather than being bogged down in an unending argument on immigration or the grandiose dreams of going it alone in trade, we should focus on the move as a great negotiating ploy. Since Brexit, every EU leader (e.g. Francois HollandeAngela MerkelJean-Claude Juncker) has hectored on curtailing single-market access unless the UK does what the EU wants.

By deprioritizing single market access, May has publicly destroyed the union’s single-point strategy. Of course, to be effective, the statement needs to be credible. However, credibility in negotiations is not based on rational economic arguments, but on making the opponent believe that one is prepared to carry out the stated action. Here, credibility is ensured by the Brexiteers’ triumvirate of Liam Fox, David Davis and Boris Johnson standing behind May.

Third, the mainstream narrative around the pound’s weakness may inadvertently help the UK by providing false comfort to the EU. So far, the EU players' plan seems to be clamouring for Article 50 and making sure UK “pays a price” that dissuades other potential exits.

They are playing a defensive waiting game in the hope of a British capitulation. As discussed above, while a plunging pound may look like an implosion, it actually leads to the opposite and strengthens the UK’s position over time. Moreover recent UK economic statistics give no cause for concern yet, with consumer confidence back to pre-Brexit levels in September and retail sales continuing to rise.
Playing a waiting game also assumes that the European elite can quell the anti-EU movements gaining ground across countries which threaten to tear it apart. Without an implosion of the British economy which shows the dangers of life outside EU, they are left with the much harder challenge of delivering growth.

The IMF forecasts euro area growth to be below the pre-crisis rate and only ~1.5% per annum over the next five years. The EU’s own forecast shows unemployment to fall only gradually and likely to be still above pre-crisis levels by the end of 2017.
While the British pieces have moved to take the best advantage of the situation, Europe is withdrawing into a defensive shell, with Juncker passing a “presidential order” to ensure there are no informal discussions with British representatives.

This speaks to the very real fear that Europe is an amalgamation of differing viewpoints and strategies which UK can use to its benefit. The inability of the EU to offer a united and coherent strategy was cruelly exposed during the European debt crisis and is likely to show up again in Brexit negotiations. While UK has substantial challenges ahead, based on the opening game, betting on grandmaster May to win is a smart move. 

Sunday, 17 July 2016

Theresa May’s Brexit gambit

A grandmaster has entered the Brexit game. Theresa May’s first set of moves as PM have confounded opponents and onlookers alike. Her cabinet appointments have raised eyebrows with Boris Johnson as Foreign Secretary also raising many a laugh. She has indicated a decisive break from the failed pro-elite austerity strategy of Cameron-Osborne. And she has swiftly moved to shore up the union by meeting with Nicola Sturgeon and acknowledging that the UK is more than just England. Importantly, triggering Article 50 to leave the EU will only be done once there is a “UK approach”. This also provides a legitimate reason to prolong the triggering, which is UK’s best strategy in Brexit negotiations. May’s strategy is masterful to watch in an era of Camerons and Goves where bland smiles and glib words hide an intellectual deficit of epic proportions and shameless short term opportunism trumps long-term sense.

The choice of appointing Brexiteers, David Davis, Liam Fox and Boris Johnson, achieves three crucial objectives. First, it cements May’s position by assuaging the Eurosceptic right flank of the Tory party and heading off potential future challengers. It allows her time and space to plan Brexit rather than rush headlong into it. Second, it places the Brexit brigade on the spot to deliver on the dream they promised. If they succeed, she wins by being the PM who calmly steered the nation away from the EU whirlpool. If they fail, she wins again by exposing the mendacity of their pre-Brexit claims and changing course (another reason why deferring invocation of Article 50 is sound strategy). Third, it channels their right-wing energies outwards towards achieving the national interest by competing with other nations. Also, given their fierce ambition (all three having coveted the Tory leadership at various points), they are likely to put in an extra effort to succeed in their brief to distinguish themselves. Moreover, having the right-wingers in international portfolios allows May to pursue a softer domestic economic policy and improve social cohesion.

In addition, May has placed the people quite appropriately. The important international trade and Brexit portfolios where a serious approach and detail orientation are critical have been given to David Davis and Liam Fox. The foreign secretary’s brief requires a candidate able to charm, persuade foreign leaders and raise Britain’s profile in the world. It also requires an ability to be flexible with the truth. Grasp of detail is irrelevant (it is the civil service which takes care of detail). Ergo Boris. He has demonstrated all these capabilities as Mayor of London and successful Brexiteer. Moreover, the clownish persona disarms opponents to the steely machinations of a first rate political brain as evidenced by his rise to the top echelons of the party. It also takes the edge off the insults and nonsense he spouts on occasion as it is usually ascribed to buffoonery. Any other “serious” politician would have been sunk had they even said half of these things. He is exactly the foreign secretary needed to put one over the foreigner. While a “serious” candidate might make us feel good, international relations require a mastery of realpolitik which Boris Johnson has demonstrated. Would you rather have a straight shooter who comes back waving a document signed by an autocrat believing in the eternal friendship being proclaimed?

The other well thought Theresa May move which has surprised is to break from the Osbornian cult of austerity and send its architect packing. Given current conventional wisdom, even considering a fiscal expansion and not falling back on opening the monetary spigot to deal with a crisis is quite revolutionary (notably the Bank of England did not reduce interest rates last Thursday as was widely expected). Austerity along with easy monetary policy has contributed to increasing wealth inequality and created a perception of the system not working for the common person. It has given rise to populists across UK and other countries and was probably a decisive factor in the Brexit vote. In addition to breaking from current economic dogma, May has done well to appoint Philip Hammond. Deficit spending, when the nation has cut itself away from the EU, requires market credibility to prevent soaring Gilt yields. The new Chancellor, being an established fiscal hawk provides it.

Alongside positioning her pieces, May has sharpened offense and strengthened defence. She has kept UK on the front foot by ignoring the European voices clamouring for a swift invocation of Article 50. It pushes significant Brexit uncertainty onto a crisis-ridden EU and constricts its ability to formulate an effective response (evidence the considerable gnashing of teeth from various European capitals). It may make it easier to obtain pre-negotiation concessions. The ambiguity also provides hope to markets stopping them from freaking out, thus containing the short-term economic fallout. Delaying Article 50 triggering also buys time to set a clear strategy and implement it while the country continues to benefit from the single market. In addition, May’s meeting with Nicola Sturgeon to reassure that Scots that they would have a say in Brexit reduces the threat to UK disintegration.

It is early days yet and much can change, however Theresa May seems to have set her eyes on winning the Brexit game. She has rapidly reconfigured the board to put UK at an advantage. She has astutely positioned people, forced EU on the back foot on Article 50 and mitigated potential vulnerabilities by acting to shore up the Union. As the game unfolds, Jean-Claude Juncker and team may find themselves in the position of an amateur playing Judith Polgar.

Sunday, 26 June 2016

The Brexit Chessboard

Thursday's momentous vote in the UK has wrongfooted most investors and has switched "risk off" mode. At this point, the only certainty is that it is going to be a roller-coaster ride for the markets and that it is too early to buy the dip (risk-reward is skewed against buyers).

The "chessboard" below is a quick and initial stab at putting down my thoughts.

The current UK and EU stances favour a risk-off environment with the EU in a dominant negotiating position as the UK invokes article 50 (grey squares in the figure below).

For the UK, the optimal strategy is to not invoke Article 50 for as long as possible and launch an outflanking diplomatic manoeuvre to force real change in EU treaties. This can be done through allying with national leaders in Europe who are fighting anti-EU populist sentiments themselves. However, this is hard and requires a greater degree of competence and leadership than displayed by the UK in the recent past. While Boris Johnson's "no need for haste" veers towards this, a clear "leave" strategy is notable by its absence. It is likely that any new PM invokes article 50, as it is the easiest course to take with the lowest personal political risk (there is also a distinct possibility of a snap election, but invocation of article 50 will still remain the easy choice). Disregarding the referendum is possible and can take many forms, e.g. taking refuge in its "advisory" nature or calling a new one which 3 million petitioners are clamouring for. However, such dodges are unlikely given the British.

For the EU, internal compulsions to deter more "exit-eers" are likely to lead to the desire to set an example of the UK. Mr. Jean-Claude Juncker's comment about not being "an amicable divorce" does not augur well. Ultimately, as in every divorce, the desire for vengeance is likely to be self-defeating. How much of this desire is reflected in their bargaining position will determine the level of acrimony, uncertainty and protractedness of the process. There is a glimmer of hope that national leaders such as Angela Merkel may persuade the European negotiators away from scorched earth tactics. However, at the moment it is not the most likely scenario.

(Please note the disclaimer at bottom - all of this is my personal opinion and should be taken as such. It is likely to change as the situation changes. Nothing here should be considered as an investment recommendation.)

Wednesday, 4 May 2016

Mapping the Artificial Intelligence Landscape

“Artificial intelligence”, “machine learning” and “robotics” are rapidly rising up the buzzword charts. In finance, while there is rising interest in the new technology, the usual ‘old wine in new bottle’ approach by purveyors has created confusion around the precise definition of these technologies and their applications. What used to be bog-standard automation of standardised manual processes is now “robotics”; any set of predictive algorithms are “machine learning”; the mere ability to parse through natural languages confers “artificial intelligence”. All sound cooler and sell more.

It is easier to look at the inter-related technologies under the umbrella term of artificial intelligence (AI). We can define artificial intelligence to be the ability of a man-made system to act independently in a reasonable manner by processing information available to it.  However, we still need to cut through the marketing hype to understand the technology and its potential.  

Even though the boundaries are blurred, independence of action allows us to differentiate between Big / Smart Data and AI. The former pertains to systems which process information to help their operator make decisions. AI systems go one step further by making the decision. Whether the decisions are subject to operator supervision and correction is tangential as this is a function of capability and trust in the system. For example, a natural language processing application which parses through email and chat transcripts to shortlist suspicious conversations for the compliance officer to act upon are part of Big Data. One which flags violations and adjusts to new slang through contextual understanding is AI.

In addition, AI systems can be distinguished from each other by the complexity of input data. This has a direct impact on processing power and complexity. For example, a game ‘bot’ has artificial intelligence and so does a robot which can stack and unstack chosen boxes in a warehouse. However, the former has a limited dataset to process which the latter must process complex visual cues such as configuration of boxes, obstacles on the warehouse floor along with other parameters such as weight of box.

Therefore, the twin dimensions, decision making ability and complexity of input data, allow us to classify different AI applications and create a map of the landscape. This reasonably captures most current applications. However, future development is likely to lead towards a system which displays more broad-based intelligence compared to the current narrowly focused application areas. This suggests a third dimension of broad vs. narrow field of application. Artificial General Intelligence (AGI) which can pass the famous Turing test lies at one end while chess playing AI lies at the other. These three dimensions are represented in the figure below.

Figure 1: 3-D AI landscape
Some of the current application areas can be mapped on this landscape (figure 2). As can be seen, almost all of these are narrow AI. Although some natural language processing (NLP) based applications arguably have a broader field of application e.g. IBM Watson has the potential to function across multiple areas (albeit with training and not simultaneously), AGI systems are non-existent.

Given current interest and investment, it will be interesting to see how the landscape fills out.

Figure 2: Map of AI application areas

Tuesday, 26 January 2016

Artificial Intelligence (AI) in trading

Superhuman intelligence devoid of emotion has been the long-time goal of computer scientists working on artificial intelligence (AI) and the winning formula for many a Hollywood blockbuster. Public interest in AI has piqued again after several luminaries (Bill Gates, Stephen Hawking, Elon Musk amongst others1) argued that real life could follow a Hollywood script as AI advanced beyond human comprehension and control. While we are far from such an eventuality2, an enormous amount of money (~5% of total 2015 VC investment of ~$50BN+3) and time (~10% of overall research in computer science4) has been invested in developing AI for use in various areas from fighting cancer to writing cookbooks5.

In finance, R&D on AI is being carried out by banks, fund managers and Fintech companies. Considerable excitement has been generated by the vision of finally realising the alchemical dream in trading. Well known established hedge funds such as Bridgewater Associates and Renaissance Technologies have invested in AI and are competing with new entrants such as Rebellion Research and Aidiyia. Is the future of markets an uber-rational machine trader, untiringly able to process and draw conclusions from vast amounts of data?

Observing the progress in AI and the rapidity which markets are turning electronic, it may seem that the days of the human trader are limited. Starting from 1997, when IBM’s Deep Blue beat chess grandmaster Kasparov, AI has come a long way. In 2011, IBM’s Watson achieved a more remarkable feat of beating ‘Jeopardy’ champions Brad Rutter and Ken Jennings. ‘Jeopardy’ requires the player to frame a question based on a provided answer. This can be across a variety of themes from arts to science and history to current events. Watson was able to understand natural language (including idioms and puns), relate it to processed data across topics and come up with the correct response. In addition, Watson can improve over time based on feedback to its responses. Based on these successes, a machine trader is not hard to envision. Our version of Trader Smith can imbibe all historical market data and existing knowledge on economics, finance, politics, history, psychology. Further, it can plug itself into sources of new information – newswires, twitter feeds, etc. Armed with this knowledge bank, it can scan through asset markets looking for short-term mispricings, arbitrages and long-term investments. It can stress-test the best trade ideas and automatically execute those making the cut. Having no emotion, it can cut losses or take profits based on a rational data-based approach. It can continually improve its trading strategy by learning from its results. For the average human trader with bounded rationality, emotions and limited knowledge, an encounter with Trader Smith is likely to be very one-sided.

Although the vision is beguiling, the dominance of machines in trading is not ineluctable. For all its claims, artificial intelligence is narrowly focused on performing relatively well-defined tasks. For example, Deep Blue was only great at chess. Similarly, Watson’s expertise is focused based on where it is deployed. The original version was great at playing Jeopardy and not much else. New applications are devoted to using it as an expert in other fields such as medicine6 but this requires considerable reprogramming. True human-like intelligence (technically Artificial General Intelligence – AGI) is still far in the future (it is noteworthy that despite claims, no computer has yet passed the Turing test satisfactorily, including Watson7, 8). It might be argued that AGI is not necessary for trading. It is sufficient to program the computer using a finite knowledge base and trading rules and heuristics. For example, trading corporate bond can be done based on evaluating the borrower creditworthiness, relative value, economic outlook, etc. Trader Smith can not only do a better job given its massively greater power to crunch and analyse data but also improve based on trading results.

However, trading is unlike fields with set rules such as games or medicine9 where cause-effect-response relationships are relatively unchanging and can be computed easily (i.e. these fields are linear). In trading, a similar set of factors may produce significantly different results, i.e. trading is dominated by non-linear phenomena. Just as computers are unable to predict the weather a few days out (despite the massive computing power at the disposal of meteorologists), their clarity horizon will be fairly limited in trading. Therefore a pure deductive approach, which is the hallmark of AI currently, is unlikely to work.

Trading also requires creativity and thinking outside the box which machines are notoriously poor at. For example, Trader Smith may have got an inkling of impending doom in the run up to 2007-0810 but would it have been able to construct bespoke CDOs designed to fail in order to profit from the market downturn (a la Michael Burry11 and John Paulson12)?

AI proponents may argue that even if long-term trades are not the forte of computers, they can certainly beat human traders by capturing short-term opportunities. Indeed, a lot of algorithmic machine trading is driven by momentum and exploiting short-term arbitrage and mispricing opportunities. However, these are purely dependent on speed of processing and response times not artificial intelligence.

In addition to the challenges posed by non-linearity of markets and the need for creativity, there is likely an inherent “creator’s limit” to artificial intelligence13. This arises from the need to “train” machines to become expert at a field. The machine follows the basic rules laid down by the human experts and improves the efficiency of the decision-making process rather than “think” for itself. Yes, there are feedback loops and evolutionary algorithms which try to mimic the human thinking process but they are again constrained by the framework provided during inception / training. For example, Watson looks at the known body of medical research to arrive at a suggested course of treatment for a particular cancer. It cannot suggest an entirely novel course. At best it matches a treatment to a patient leading to a higher chance of survival. Finding a cure for cancer still needs the human mind to question basic assumptions and come up with lateral solutions. In markets, an AI system can choose profitable strategies based on a broad but fixed set of factors14. However, profitability of formulaic trading strategies rarely persists. Market participants rush in to exploit the opportunity and compete away the profits15. Therefore, far from learning and becoming better, Trader Smith would fall into obsolescence unless human help is provided.

Despite the shortcomings, there is hope for machines. Artificial intelligence can be used to augment human trading capability. Marrying ‘big data’ processing and rational analysis with creativity and human understanding of market “moods”, if done properly16, can create a winning combination. Just like in chess17.

9 Even though medical practice changes, the evolution is relatively slow, e.g. even if one study upends conventional thinking, it takes time before a new approach is validated and doctors need to change their prescription/practice
10 Apparently Rebellion Research’s “AI program predicted the stock market crash in 2008” (http://robusttechhouse.com/list-of-funds-or-trading-firms-using-artificial-intelligence-or-machine-learning/). However on their site (http://www.rebellionresearch.com/) the ‘A.I. Global Equity Strategy’ performance chart doesn’t support this assertion
13 This goes against what some very intelligent people believe but intelligence of a person is not sufficient for validity of their assertion. History has shown that intelligence is no guarantee of correctness. Before Einstein propounded the theory of relativity a lot of very intelligent men believed that all that was to be known in physics was already known.
14 For example, Rebellion Research’s AI system monitors 30 factors (http://www.wsj.com/articles/SB10001424052748703834604575365310813948080)
15 Momentum trading may be an exception but much of the academic support is based on historical regressions. The difficulty of knowing the turning points in advance means that in practice most traders are unable to make money in sideways markets
16 The challenge is to create a process for human-machine teamwork with the human combining the ability to work with AI-systems with some trading talent