Hassan LAHLOUHassan LAHLOUNovember 3, 2016
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68min4970

The Kingdom of Saudi Arabia is a key subject when considering the state of the world’s economy. It is the world’s largest petroleum exporter and the heart of the Islamic nations. Multiple political structures and international relations emerge from its blatant economic, geographic, as well as religious status. This has resulted in the Kingdom becoming a bridge between the Islamic nations and the western civilization. Given its strategic position in the OPEC, it dictates to some extent major trends in the world’s economy by having a strong influence over oil prices, its production capacity and its political agreements. For many decades, oil production was the kingdom’s main economic pillar with a selling price of approximately $85 a barrel and a cost of production below $2. Even such a lucrative industry would hardly support a country indefinitely, considering their finite amount of resources. Today, Saudi Arabia is aware of such a mild threat and is now assessing its options in embracing new visions of growth that do not rely exclusively on oil. First, the government applies the legal code of Islam in its banking system, and second, opens its stock market to foreign countries to optimize its financial puissance.

Many factors contribute to the rapid economic expansion of Saudi Arabia. On one end of the spectrum, having 18% of the world’s proven oil reserves puts Saudi Arabia directly on a pedestal. 50% of the Saudi’s Gross Domestic Profit comes from the oil and gas sector, which represent 85% of export earnings. By world standards, the kingdom is intensely influential. According to the Organization of the Petroleum Exporting Countries’ 2013 report, Saudi Arabia would be in possession of approximately 266 Billion Barrels and an extra 2.5 Billion shared in the Saudi-Kuwaiti Zone. The continuous growing demand for oil products and oil-based machinery in the United States and other major oil consumers fosters the already-established strength of being a major player in the OPEC.

On the other end, the Islamic influence has greatly impacted financial structures by prohibiting usurious practices. In the Islamic laws, money is perceived as a mere measure of value and is not considered an asset itself. Therefore, any earnings based on the “value” of money would not be in accordance with the rules of Shariah (Islamic laws). Financial engineering came up with what is now more commonly known as “Islamic Banking”; A form of finance that involves both lender and borrower in a profit-loss-sharing system aiming at suppressing the favoritism towards the lender. Islamic Banking in Saudi Arabia is a $217 Billion industry worth of assets, the world’s largest Islamic finance concentration.

In 2007, when subprime mortgages started to heavily default showing the weak spot of interest based practices such as teaser rates or predatory lending, Islamic banking on the other hand presented aggressive growth. “ Islamic banks, on average, showed stronger resilience during the global financial crisis.” IMF. It is heavily argued that Islamic banking might be the solution to prevent future credit crises. Today, most of the largest multinational-consultancy firms such as Deloitte and Ernst & Young are welcoming Islamic Finance with open arms as it appeals to a growing group of international investors. Financial assets in Islamic banks have grown at a 17.6% rate annually (on average) since 2009 and are expected to attain 19.7% before 2018.

Though Saudi Arabia has long been relying on its natural resources to affirm its economic presence amongst the wealthiest nations, it is now embracing a new vision of growth by opening its doors to foreign investors. The policies regarding investments in Saudi’s stocks have long been restricted to domestic investors. As the practicality of globalization spreads exponentially, the kingdom is now considering alternative ways for expanding its market. Recently it has been discussed that foreign firms would have access to a $580 Billion investment capacity in the first half of 2015. QFFIs (Qualified Foreign Financial Institutions) will have the opportunity to enter one the world’s most restricted exchanges. Tadawul Exchange (Saudi stock market) stresses the importance of keeping the market safe and protecting itself from being exposed to risky investors. Therefore, only QFIs with a minimum of $5 billion worth of assets under management and a minimum of 5-year experience in the investment field would be eligible to participate in the market offering. In addition, multiple market caps have been put in place to lessen the risk of monopoly of stock ownership. Despite the challenges facing the marketability of its stock market due to the recent plummeting of oil prices, Tadawul Exchange is still a robust market that offers a considerable diversification to QFFIs. Amid several propitious economic impacts, it will ultimately boost the credibility of the Middle-Eastern region for both oil and non-oil based industries.

It is not a secret; Saudi Arabia owes its fortune mainly to its oil industry. For many decades, its growth has been sustainable and steady. However, Saudi Arabia’s future is less certain. Today, in other countries, billions of dollars are being spent in Research & Development to explore alternative forms of energy less harmful to the environment. To what extent does alternative energy represent a threat to the Kingdom’s current strategic position as the world’s top oil exporter? How can Islamic banking contribute to the world’s financial stability? These are some questions that need further considerations.

Work Citation

  • Sarmad Khan, Nikolaj Gammelto, and Arif Sahrif. “Saudi Arabia Drafts Foreign Limits for $580 Billion Bourse.” Bloomberg.com. Bloomberg, 21 Aug. 2014. Web. 08 Feb. 2015.

  • IMF Team. “IMF Survey: Islamic Banks: More Resilient to Crisis?” IMF Survey: Islamic Banks: More Resilient to Crisis? 4 Oct. 2010. Web. 08 Feb. 2015.

  • Heritage.org “Saudi Arabia.” Economy: Population, GDP, Inflation, Business, Trade, FDI, Corruption. Web. 08 Feb. 2015.

  • “Big Interest, No Interest.” The Economist. The Economist Newspaper, 13 Sept. 2014. Web. 08 Feb. 2015.

Islamic banking performance benchmarked against conventional banking

 

Hassan LAHLOU


BONDS & SHARESBONDS & SHARESNovember 3, 2016
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4min3490

Nowadays, we can’t hardly have not heard about Crowfunding in the news, a phenomeneon from the USA and which becomes very famous in France. As it is sometimes translated as a «  participative financing » or «  a crowd financing », this alternative to looking for funds to finance a professional project has been largely inspired by the succesful financing campain in the USA.

Crowdfunding is an Anglo Saxon word. This phenomeneon was born in the XVIIIth century. It appeared in France in 2013.

Crowdfunding or « financing thanks to the crowd» is a new means to finance projects by people. This mecanism is used to find funds, usually small sums, among many people to finance a project according to its nature.

It can work thanks to a platform on the internet. Crowdfunding can support local initiatives or projects defending any values. These operations are different from traditional means of financing and often contain an affective aspect.

It may raise funds thanks to people without asking a bank. This participative form of financing can be applied to different projects. It is also a means to develop a project.

This means of financing implies that there is a financing person and people who often have a project to create a company but who haven’t got the money to do it.

Several forms of contribution are suggested to the financing persons like donation, lending and investment plateforms.

Crowdfunding is regulated by the Authority for the Financial Markets and the Prudential Regulation Authority and it was completed by the law n°2014-559 on May 30th 2014.

Many crowdfunding sites were born with the will to finance a project. Other sectors also surf on this new means of financing like the buildings sector.

Crowdfunding is a transparent and new way to create companies or the development of projects with varied aims, thanks to collective intelligence.

Ghislaine TOVIHO


Benoit ANGLADEBenoit ANGLADEOctober 27, 2016
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38min4580

The multiplication of exceptional climatic phenomenon linked to the climate change proceeds for a few decades. Each year 200 million people are affected by climatic modifications and among them 70.000 people die of it. Even if we do not have enough statistics to prove the impacts of climate change we note a boom of the climate system. Extreme phenomenon and climatic anomalies are booming due to the increase of CO2 emissions; between 1970 and 1985 there were 50 climatic disasters while since 1995 there are already 120 disasters.

According to a 2015 United Nations report, 90% of natural disasters that happened for 20 years are linked to climate change. The real cost of those disasters including earth shakes and tsunamis would be approximatively 250 to 300 billion dollars per annum but some economists are even more pessimistic and estimate the cost at 500 billion dollars. The amount of resulting damage caused by natural disasters has strongly increased for a few years as the following graph shows:

Property damage caused by natural disasters (in billions of US dollars)

According to the last GIEC report launched in April 2014, this disruption affects all the economic sectors such as agriculture, public transport or tourism. An alternative to hedge those risks is to use indexed options on weather risks which is called climate derivatives. Using weather data, it is possible to calculate the risk of a natural disaster, to attribute a value et so to insure it.

Nowadays climate derivatives attract emerging countries and developed countries where it is seen as a complement of the traditional insurance program. India was one of the first country to use indexed insurance products aimed to protect farmers from climatic disasters with the help of the World Bank and the Indian State. In developed countries, the use of climate derivatives to hedge the decline of agricultural yields is more and more important. In the US, the sale of agricultural insurance based on weather indices boomed since 2011.

The weather sensitive aspect of the international economic activity is a reality and economic actors must hedge their climatic risks if they do not want to lose money. Thus, the hedge of natural disasters implications is a true problematic of the 21st century because we know that 30% to 70% of the world GDP is influenced by climatic disasters.

A newly emerging market

Nowadays firms need to hedge from the negative impacts of the climate and to include those instruments into their business plan. Still the creation of an index is complex, even when the sensitivity of an economic activity to weather conditions is confirmed, it can be difficult to identify precisely the link between the variability of weather conditions and income volatility. Furthermore, the climate derivative market still suffer from a lack of liquidity linked to the imbalance of the demand. Risk premium stay at a high level for climate contracts which is one of the major obstacle to the development of this type of product.

Climate is often seen as inevitable and impossible to curb. Economic actors regret negative impacts of the weather on their activity but they are not used to hedge this type of risk. The more the weather risks management will be expanded, the more data is available, risk premiums are low and the hedge is interesting for economic actors.

States and international institutions have a key role to play in the development of weather derivatives, including the definition of the regulatory framework that surround those new products through the judicial form or their counting way. Finally, States can also stimulate the development of weather derivatives by enabling the access to data by offering the deployment of weather stations network.

Climate risk as a new financial product

Nowadays this market remains narrow because there are too little actors to be effective. Many economic actors such as energy companies (electricity, gas producers and suppliers…), agribusiness manufacturers, entertainment companies, farmers or transport companies have to face the climatic risks and their impacts. More and more risks interfere with the economic activity accelerated by climate change but the market is now able to provide a solution to hedge it. This is for now a growing market for the next years due to the acceleration of climate change.

Even if prevention and the use of classic insurance policy remain the standard, companies will have to use these financial products in the future and build new hedging strategies to take into account the climatic impact on their activity.

How to lead a hedge strategy of weather risks?

The international financial system is composed of the bank system, the insurance system and the financial market system. Each of them are using the weather derivatives for now in a variety of ways but with the same goal: hedge against weather risks.

Among the users of the weather derivative, those who are the most interested are the end users but the role of the intermediates such as the brokers or the role of the risk takers such as hedge funds is establishing like a predominant role.

The end users are mainly weather sensitive companies which buy protections against negative impacts of climate change such as a decrease of their production or of their demand. Hedging this type of risk can be also a great opportunity to promote the image of the company.

Brokers mainly popularized this type of product offering their help to companies to find out the different vulnerabilities of the companies regarding weather conditions. Data suppliers are also important because they provide figured data to use this type of indexed product.

Banks use weather derivative as a hedge strategy to cover weather risks for their clients by offering them some advice. The measure and the transfer of weather risks is simply an extension of the intermediation activity of banks. This new market allows the banking sector to expand their activity range and so to attract more clients, interested by this new hedge type of product.

Hedge funds play a key role on the weather derivative market. Indeed, those alternative funds seek absolute performance and weather derivative is very interesting for those funds because their yield is not correlated with the market performance. However, hedge fund strategies are mainly based on performance and speculative yield and not on a real hedge. This use is nevertheless important for this market to have a better visibility and liquidity on the financial markets.

Weather derivative is an alternative to the classic hedge

Weather derivative allow the transfer of new risks such as the weather risks of companies. They can also advantageously complement some traditional hedge solutions mainly with natural disasters reinsurance contracts. Even if the basis risk still remains an issue in his application, the application scope of weather derivative remains important.

Human being have to adapt to the inevitable impacts of climate change, he has to get ready to an increase of total temperature on the earth and to a stronger volatility of weather conditions. With this increased risk linked with climate change, it is obvious that each company would have to hedge this type of risk for the future because the impact of climate change on the economic activity is even stronger.

To find out more:

  • Nicolas Martelin, “Comment le climat est coté en Bourse”, Le Figaro, 2008

  • Pierrick Fay, “Le réchauffement climatique dangereux pour les actifs financiers », Les Echos, 2016

Benoit ANGLADE

 


Achraf MEKKIAchraf MEKKIJuly 16, 2014
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5min3660

The stock exchange has become the symbol of the business world, when everything goes well on the markets; the economy is going well too, but in each crisis or escroquies, the stock market is accused of all names.

The movement recorded in the capital markets exceed the real needs of our economy, the stock market has become the realm of speculation, excess and is completely disconnected from the real world, so much so that the police of the stock exchange (Regulators) can not longer control this.

We found toady many formers of the finance as Jordan Belfort, Jerome Kerviel or Geraint Anderson denouncing the excesses of financial world. According to them, traders are abusing the system, and causing unemployment, suicides, violence, depression and destroy lives, they sell their soul to the devil for money. After each crisis, financial instistutions are not the only ones accused we have also the polemic of « bonuses » (premiums paid to traders), proportionals to the gains which encourage them to make the maximum profit and therefore to take the maximum risk.

According to Geraint Anderson (former Analyst at JP Morgan): “The operators in a trade room have many points in common. They are intelligent, selfish, ruthless, greedy, obsessed with money and with the instinct of competition ; « every day you want to do better than your neighbor in your desk, and you would do anything to achieve your goals ».

The best traders on the planet can expect to earn tens of millions of dollars per year, that represents 20 years of wages for an average European. This bonus prompts you to think only in a short-term view(12 months), if you lose, in the worst case you only risk getting fired but you will reimburse nothing, which leads you to the craziest bet.

Since 2009, banks are encouraged to calculate the performance of their traders on three years and spread their payment over time; but to keep their best people, most banks get around the law by doubling or tripling their fixed remuneration.

John Coats (former trader, researcher at the University of Cambridge) maid a study during the bubble of the internet; he said : « at that time the whole world was caught up in the internet bubble, traders manifasted symptoms of excess of confidence, they were delusionals, euphorics, and did not sleep; However, women were not taken into turmoil in the same way, they were much more skeptical and the issue of hormones and more precisely of testosterone (wich affects more men than women) was the main cause » To study the rate of change of this hormone they collect saliva samples twice per day at the beginning and at the end of the trading day; he then noted that testosterone increased in a very hard way when the trader earned more than the market, but also that the level of testosterone in the morning could predict how he would win in the afternoon; So that would mean that the level of testosterone affects the level of profit and loss and not the reverse.

In conclusion, if we had more women and older men, it would probably bring more stability on the markets, moreover, a reorganization of markets today, where there is too much freedom, would be very useful.

Mekki Achraf


Achraf MEKKIAchraf MEKKIJuly 16, 2014
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4min3220

More than a bank, Goldman Sachs is a rich invisible empire of 700 billion euros in assets, twice the budget of France. It’s called “the Firm”, as in spy novels of 80s. Having enriched during the subprime crisis by betting on the collapse of U.S. households, it was one of the instigators of the crisis of the euro making-up the accounts of Greece and leveraging against the single currency. An empire of money on which the sun never sets, which has transformed the planet into a vast casino. Through its unique network of influence in the world, and his army of 30,000 “monks” bankers, Goldman Sachs took the opportunity in the crisis to increase its financial strength, increase its influence on governments, and enjoy impunity of U.S. and European justices.

The first thing you learn when you’re making an article about GoldmanSachs is that we should not talk about GoldmanSachs. Former employees are afraid, interns are hiding.

Since December 2006, the Financial Goldman Sachs knew that a crisis will come and have greatly beneficiate from this valuable information.

The Americans, have suffered theconsequences and are starting just now to wake up. This dipin the heart o fone of the largest Wall Street institutions give us a real view on methods of global finance.

Goldman Sachs seems to remain above the law

There are 2 different possibilities: either justice is corrupted, or the financial sector has become untouchable.

Mekki Achraf


Achraf MEKKIAchraf MEKKIJuly 16, 2014
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4min6110

It was only a few years ago that most of the world top trading place introduced the electronic trading in their trading room, only 2 places in the worls now are still working with the floor trading, the real trading for someone, the London Metal Exchange and The Chicago Mercantile Exchange.

The London Metal Exchange (LME), located at 56 Leadenhall Street in the City of London, is the futures exchange with the world’s largest market in options and futures contracts on base and other metals. As the LME offers contracts with daily expiry dates of up to three months from trade date, along with longer-dated contracts up to 123 months, it also allows for cash trading. It offers hedging, worldwide reference pricing, and the option of physical delivery to settle contracts.

On this picture, we can see the floor of the LME, brokers and trader of differents firms are negociating each others every metals.

In the futures pits of the Chicago Mercantile Exchange (CME), tens of thousands of people crowd into 70,000 sq. ft. and trade in excess of 550,000 contracts a day by using their voices and hands. Even this volume is pale in comparison to the total dollar volume of all futures contracts worldwide, which are over $500 billion a day. In comparison, the electronic automated counterpart to the Exchange, the GLOBEX Trading System, trades only 6,000 contracts daily.

LME trades the equivalent of $7.41 trillion annually and $29bn on an average business day. More than 95pc of its business comes from overseas.

Compared to futures, options have been slow to transition to screen trading because they are inherently more complex. Not only do they come in a range of strike prices and expiration dates, but their prices depend on the volatility of the underlying futures contract, which can fluctuate sharply on a moment’s notice. On top of that, traders have a huge variety of strategies involving different combinations of puts and calls. In energy markets, it is often easier to execute such strategies through humans on the Nymex floor rather than through Globex, which is best used for plain-vanilla options with nearby expiration dates, according to market participants. That could keep the options pit humming for a while.

Does the « Trading on the floor » has a future in this world based on technology ? Still, others still believe there should be a role for both humans and machines. We’re in the 21st century and open outcry is being replaced by more machines ; but of course, If you’re just trying to do volume, if you’re just trying to do speed, the machine will be the preferred venue. Nobody will argue that. But there’s a place for both in some way, because sooner or later people will want to have more personal attention than a machine can provide. I mean, have you seen all the snafus that the machines have created? We’ve never had that kind of stuff in open outcry. That could keep the pit humming for a while.

Mekki Achraf


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4min3670

There’s something wrong with Europe. Is the euro crisis over? To judge from how often the words appear in global media, the answer is yes.

Markets have calmed since July 2012, when the president of the European Central Bank (ECB) Mario Draghi, promised to do “whatever it takes” to save the euro. Ireland and now Portugal are climbing out of their bail-out programs. Even Greece, where the crisis began, has just sold debt.

Yet, as these books all argue, the crisis was always about more than whether financial markets would buy government debt. It raised broad worries over how countries with widely differing levels of prosperity, competitiveness, public spending taxes, and regulation of labor and product markets, could share a currency without economic shocks blowing them apart. And it was about whether euro-zone voters would accept low growth, high unemployment and a permanent loss of sovereignty to the center. None of these concerns has been fully dealt with.

The biggest error was to misunderstand the underlying causes of the crisis. Because the first victim was Greece, it became accepted wisdom in Brussels (and Berlin) that the problem was profligate spending and borrowing. The Germans liked this explanation because it confirmed the suspicions they had before the creation of the euro that they might be lumbered with other countries’ debts. It also looked susceptible to a gratifyingly simple cure: ever more fiscal austerity. And it avoided any suggestion that Germany might have contributed to the crisis by running a large current-account surplus that its banks recycled in cheap loans to Mediterranean property developers.

The financial crisis that began with the collapse of America’s mortgage market was just one of many episodes of recent financial crises and America’s near-default in the summer of 2011.

The biggest worry may stem from the perception that the crisis is over. This is likely to slow or even stop further reforms.

If that happens, the EU and the Euro will get into trouble again-and the outcome next time could be even worse.

Bouzidi FATIMA-AZZAHRA

 


BONDS & SHARESBONDS & SHARESMarch 26, 2014
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36min2720

Transaction Cost Theory to assess High-Frequency Trading systems impact on market’s performance”

The facts

Newly-known Algorithmic Trading or High-Frequency Trading (HFT) systems in capital markets may be objectively seen today as a symbol of a world seeking for each day more engineering in its processes and execution. Effectively, this booming propensity of financial entities to elaborate mathematical algorithms to integrate in automated decision-making machines leads people to imagine a bright future for such technologies, in a context where HFT firms represented 2% of the approximately 20,000 US trading firms operating on the markets in 2007 (Lebreton), but accounted for more than 60% of all US equity trading volume and more than 50% of all European equity trading volume in 2012, partially over performing the predictions of Pflimlin & Checola (2011).

Realizing this on one hand and given that no entrepreneur in the world could decently agree on an Efficient Market Hypothesis theory being the true reflect of what is reality on markets on another, I got interested in thinking of HFT in relation to a (not so much) theoretical material that stands at a very fundamental level of our economy and business administrations: transaction costs.

Thus being a pillar of the competitive dimension of any business, costs appear to me as being an appropriate element assessing performance on markets. Publications around transaction costs led several contributors to be distinguished with a Nobel Prize and conducted to the progressive formalization of the Transaction Cost Theory (TCT) over the last 75 years.

A big deal indeed. And I invite you to have a look on it so you could catch the trend with us.

Transaction costs are costs occurring in an economic exchange. They can be of various forms and can be detailed as the costs a company or entity has to pay at the moment of any financial or commercial exchange since the very beginning of the operation and until its end, including eventual later extra fees. Costs of research, brokers’ commissions or quality controls are considered as transaction costs as they are directly (stock commissions) or indirectly (prospection costs) linked to a transaction.

The idea of costs pricing system was first evocated by the economist Ronald Coase in his article The Nature of the Firm (1937). He wondered about the origins of economic organizations. According to him, the presence of transaction costs will lead every economic actor engaged in a transaction, to seek for the posture leading to bigger reduction of transaction costs each time the loss implied by this posture in the following steps of the transaction process is lower than the saved transaction costs. In this regard, Coase states that companies or firms are a way to limit transaction costs by creating collaboration between employees (Coase, 1937) thus, implicitly identifying the TCT as part of the Organizational Theory.

Various minds contributed to the TCT’s elaboration such as Oliver Williamson, still considered today as the father of the theoretical stream called Transaction Cost Theory. Inspired by Ronald Coase’s work on transaction costs, Herbert Simon’s on bounded rationality and Kenneth Arrow’s definitions, Williamson defines the transaction costs as the functioning costs of the economic system (1985). His main purpose is to assume that in any economic activity of a company, there are automatically associated costs to be minimized through governance, in order to know how to use either the market or the firm to produce its goods. Williamson proposes then two different categories of costs: the Ex ante transaction costs, defined as costs inherent to negotiation, administration, meetings and discussions that lead the different parts to consider different types of contract; and the Ex post transaction costs, inherent to a system implementation and support, commonly related to bargaining costs when bilateral efforts are taken to correct eventual bad ex ante contracts.

Carl Dahlman has been the very last major contributor to the TCT through his analysis of the generation of externalities (1979). He underlines three different interpretations of the transaction consistent to his conclusions stating that transaction costs are the fundamental causes of externalities on a market. Based on Coase’s definition of transaction costs (1960) Dahlman underlines the three identifiable transaction costs interpretations known as firstly, the “search and information costs” being inherent to either a lack of information when collecting all the existent markets’ opportunities at a defined time or various other characteristics of transactions’ items such as their quality. Secondly, the “bargaining and decision costs” defined as resources’ allocations to identify and motivate the agents’ propensity to trade at certain conditions such as defined price and time. And finally, the “policing and enforcement costs” grounding on a lack of knowledge or assurance regarding one or both parts’ probability to break its contractual obligation eventually. As a matter of fact these interpretations are categorizing occurring transaction costs according to the natural path of a transaction process, from preliminary information search and gathering until the eventual policing costs occurring on the post transactional phase. Dahlman called this “the natural classification of transaction costs”.

So deep. But why am I considering this?

Well, in my opinion as suggested above, the existence of costs in general and specifically of transaction costs as briefly exposed here, is de facto consistent with the observation any operator on markets makes of reality in terms of costs first, as well as in terms of markets’ efficiency by extension put in perspective with theory. Indeed, markets’ efficiency is one of the fundamental hypotheses of financial theories. It presumes the absence of transaction costs, the gratuity and homogeneity of the information. It is mainly based on Fama’s works (1965, 1970) who defined an efficient market on an informational sense, as a market where any pertinent information is completely and instantly reflected in the price; a market where arbitrage is structurally simply impossible. But this hypothesis has been frequently tested and contested, including by Fama himself, on the FX and Equities markets (Fama, 1965, 1970, 1991; Fama & French, 1988a; Jensen, 1969; Summers, 1986; Mignon, 1998…etc.). The definition of the market efficiency finally appeared to be incompatible with the real market functioning, mainly because of the extent of the market’s heterogeneities such as the irregularities of actor’s anticipation, the importance of market’s imperfections and, wait for it, the presence of distinct transaction costs.

Ok, but what about the specific applications on capital markets?

In addition, TCT has been put into perspective with financial markets on various dimensions. Firstly on markets’ structure, when Dumas (1992) and Anderson (1997) stated that transaction costs can be variable from not only an agent to another and based on transaction orders, but also that they can define specific threshold for every investor. Anderson (1997) suggested then that the market price deviations in comparison to their fundamental value could create arbitrage opportunities whereas irrational behaviours of the agents make the price tends to its equilibrium. He identified the transaction costs to be responsible for the market price adjustment to be dissymmetrical. A fact supported by Jawadi & Koubbaa as the presence of heterogeneous transaction costs can dissuade investors from financial arbitrage, preventing them from trading financial securities when the predicted potential benefit is inferior to these costs (Jawadi & Koubbaa, 2006). Transaction costs are in this sense considered as market frictions, imperfections eventually leading to speculations inherent to a gap between the fundamental value of a security and its market price in reality, seized by the propensity to opportunism, characterizing most of the actors on the financial markets.

Which leads us to the second application of transaction costs on capital markets: the establishment of markets’ patterns and modelization. As stated in the last paragraph, linear modelling techniques cannot reproduce effects inherent to the presence of costly information sources, variable transaction costs and heterogeneous anticipations of the investors on capital markets (Jawadi & Koubbaa, 2006). On another hand, it has been shown that transaction costs were partly responsible of failures in asset pricing models according to Fama and French 1996’ Three-Factor Model (Chae, Yang, 2007). They proved that in any market, for the US market as well as for emerging markets, transaction costs is negatively correlated with performance of an asset pricing model. They additionally stated that if transaction costs are not minimized, any pricing model will have various cross-sectional differences in its performance.

TCT has been studied in relation with market’s liquidity and volatility as transaction costs and execution costs are analogically changing with markets’ fluctuations: trading costs are fluctuating according to these two parameters, liquidity and volatility (Domowitz, Glen & Madhavan, 2001). They also stated that innovation and investments in new technologies are often conditioned by costs observations. Indeed, traders use to look after reliable costs prediction that definitely impacts on their portfolios’ strategies: they appear more likely to adapt their trading strategies towards different initiatives that give them access to a better prediction and control of costs (Domowitz, Glen, Madhavan, 2001). However, it seems important here to highlight the fact that back in 2001, the HFT systems as used nowadays were not operational on any market yet and I assume, are different from the (older) automated order systems mentioned in their works as relevant examples of costs’ forecasting tools.

The reflection

The bravest of you people, once having reviewed all this, may be interested in using their brain now to assess the implications of the use of HFT systems on markets’ performance through the TCT. As far as I am concerned proceeding in this sense would imply to first, extract from all the statements above the questions that may be relevant to ask and then, think about it.

I would like to insist on the fact that the following statements and hypotheses are pointless, subjective, independent thought and have nothing to do with any published research. However, I like to think that every research work began with this kind of modest curiosity-based reflections, sometimes leading to the elaboration of a research agenda. This is what stimulates me and I would like to make people feel the same by catching the trend through their own intellectual aspirations.

So here are my propositions based on Dahlman et alii:

  1. Are HFT systems lowering research and information costs? – before a transaction ;

  2. Are HFT systems lowering negotiation and decision costs? – during a transaction ;

  3. Are HFT systems lowering control and execution costs? – after a Transaction.

And based on Domowitz et alii:

  1. Are HFT systems significantly predicting transaction costs?

Because we are certainly open minded people and also maybe because formally answering these simple questions would be of tremendous difficulty, we are going to focus on the different dimensions comprised in the questions: research, information, negotiation, decision, control, execution and prediction. In this regard, we will be mainly focused on the two first questions around the dimensions of research, information, negotiation and decision costs. The other ones underlined by Dahlman, Domowitz et alii such as execution, control and costs prediction appearing as redundant or inconsistent with a reflection under a transaction costs perspective to me. Shall we?

(1) HFT systems are machines configured by traders and quants on markets, the action of the machine itself actually being limited to the execution of automated, controlled operations. In this regard the implementation of such technology does not contribute to the reduction of fundamental investigation costs as they will still be supported by human teams. In this regard it seemed important to me to detail the difference between the two terms “research” and “information” comprised in the question. “Research” first consists in exogenous information. It is about global information external to the automated system itself. Quants and traders will identify all the information needed to calibrate their algorithmic machine so it can act with all its characteristics according to inputted humans’ strategy. This type of external (global) investigation for information is not processed by the machine itself but computerized in it as the strategic frame of its actions on the markets. Exogenous information is so collected with the aim of building a concrete action strategy for automated systems on markets. On the other hand, “information” corresponds to endogenous information. They are information collected by the system itself during its action on markets such as spread or price limits from other counterparties and even public news.

In this regard I would make the assumption that the research and collection of exogenous information should at least lasts the same amount of time as for a standard pre-trade data research and collection, given that the human-based process is the same, besides the time used to calibrate the machines based on some of the information collected. And that, on the other hand, the research and collection of endogenous data is significantly faster when ran by an HFT system, execution speed being the central characteristic of HFT. They can be seen as the fundamental interface existing between humans and internal, short-term or immediate financial information on markets such as spreads, counter-parts bid/ask or price limits. Milliseconds or nanoseconds HFT execution timescale corresponds to an execution speed on markets 1,000 to 10,000 times faster than humans. This is actually so reactive that HFT systems give access to usually inaccessible gains for standard traders. Put this way, exogenous research time would be hardly as longer as the endogenous research time is faster than standard pre-trade human-based-only research time. Consequently, I will assume that globally lowering research and execution timescale in fine implies lowering the costs albeit significant initial investments for the HFT system itself: it will break even at some point.

(2) Similarly, when thinking of decision-making through HFT actions on markets, comes again the execution speed factor of such systems, giving HFT agents an instant-edge over non-HFT agents from a pricing perspective. Even if one could argue that HFT systems are not taking any instinctive decision per se as their actions are purely and simply consequences of preliminary decisions taken by humans, the machines do execute their “algo-logic” decisions according to the ongoing contextual market conditions. We are talking here about specific algorithmic decisions humans can imagine, forecast and sometimes determine through statistics but that could not be executed by themselves at these timescales.

Now looking at HFT’s negotiation processes through TCT implies, additionally to the central characteristic of speed execution, to consider the technical characteristics of HFTs. Indeed, when considering “negotiation” under a technical point of view as “the ability of determining the best price”, HFT technologies appear to be very efficient through two different strategies coarsely explained below.

  • When buying on markets, the “order fragmentation” consists in splitting an initial order into various smaller ones with the same target price with the aim of reducing the investment risks but as well as giving a significant advantage of acquiring as many shares as possible at the best market price on a defined moment – Counterparty [A] instead of getting a unique long position of USD 100m with maximum target price at USD 25 will split it in 10 long positions of USD 10m each. These 100 long positions will be diffused on the market seeking for best deal price through a bottom-up approach, some of them hitting USD 23.5 for example and until the maximum acceptable target USD 25. Human traders commonly use this technique but again the difference in timescale allows HFT systems to process this manipulation almost instantly with much more efficiency regarding human capacities ;

  • The “market maker fragmentation” is about arbitraging the first strategy. The machine acting on the market may be able to understand if counterparty is processing a split-order strategy by detecting the several packets with same characteristics of target price and volumes. In this situation counterparty [B] selling on market will send sell offers to buying counterparty [A] with a top-down approach from higher prices to lower ones in order to discover the maximum target price of counterparty [A]. In this case [B] may get a hit at USD 25 before that [A] buys its global USD 100m. If [A] only acquired for USD 30m and is still under processing its bottom-up, split-order strategy, [B] goes to the market, buys as many underlying as possible at USD 24.5 and sell them to [A] at USD 25 entirely, filling [A]’s demand.

That is what these machines do, they identify and act on the best possible prices. And accordingly, negotiation, still considered under this technical point of view, appears to me as more efficiently executed by HFT systems than by humans given the two different dimensions of efficient strategies processed on markets on one hand, through extra low latencies on the other hand.

(3) No need to come back on the dimension of execution by HFT systems as it has been clearly exposed in the present article as better than human traders at arbitraging noise across a multi-asset universe at very short-term scales because of its execution speed.

However, another dimension which, I think, deserves our reflection is the control of costs; but on a slightly different point of view than the control as stated by Dahlman. Indeed, when identifying control of costs he was referring to post transactional costs of control. A dimension on which I do not see HFT systems acting at all in terms of customer service. We will be discussing about control in the next part.

Consequently and as already suggested in the introduction of this reflection, questions around HFT systems impacting execution and control costs appear to me as being already answered on one hand and inconsistent on the other hand.

(4) As well as for control, the costs prediction dimension appears to me as being inconsistent with the study of HFT systems impacting markets performance or not. Predictions of costs around financial operations are essentially made by humans. A good example may be the use of extra low latency processes for arbitrage operations on capital expenditures. HFT systems will execute large volumes of buying/selling operations in the basis of preliminary known and controlled arbitrage spreads. But humans are the ones who computed the exact spreads to be executed on the operations, not the machines.

The discussion

This, folks, is how it is done. Thanks to our brilliant intuitions, we succeeded to imagine capital markets performance to be impacted by HFT systems under a transaction cost perspective for five out of the seven dimensions stated by the TCT contributors: execution, research, information, negotiation and decision. Unfortunately and as always, reality cannot be embraced by a unique theoretical model, even as brilliant as the TCT, besides applied by the limited imagination of a poor lad. Indeed, we can clearly note the limits of our approach here when assessing HFT systems impacting markets performance through the TCT.

First, we could impute it to the fact that even if costs are a relevant way of assessing markets performance, they do not include all its dimensions. In this sense, markets’ liquidity for example is a main argument of the HFT partisans as the robots engage huge volumes on markets each day, favouring the availability of the stocks which directly benefits to the investors (Pflimlin & Checola, 2010). But the fact commonly opposed to this statement is the number of cancelled orders by HFT systems. The reality is that only a fraction of all the orders are actually leading to a real transaction. For example, the NYSE observed that between 2007 and 2011 real transactions represented about 6.5% of all the orders on the market. Showing that the “cancelled to booking orders” ratio was about 11.6 times higher in 2011 than in 2007 (Mattern & Cvetkovic, 2013). In other words, while HFT systems fundamental objective is arbitraging noise on short-time scale, they are actually creating more noise on market by faking close to 93% of their orders.

A second reason limiting our approach may be imputed to the fact that some assessment levers provided by the TCT, are simply not applicable to HFT systems specifications such as post-transactional costs of control. As seen before, control for example, considered under a transaction costs perspective cannot be applied on HFT systems as no customer relation service belongs to these automated machines’ quantitative objectives (yet). However, control may be observed under a different perspective which allows us to assess HFT systems performance not in terms of costs management but of reliability. Indeed, the truth is that the main reason for the recent people awareness of HFT systems is their increasing presence in literature and stories in the news. Various dramatic examples are tarnishing the short existence of new generation HFT systems. On September 08th 2008, a misinterpretation by HFT systems of market information around United Airways bankrupting made the stock fall by more than 75% in one day. On May 06th 2010 the Dow Jones Index felt by 9% in few minutes, corresponding to a global loss in assets’ value of about USD 1,000bn. On August 1st 2012, Knight Capital Group lost control over a trading robot during 45 minutes at the end of which it recorded a global loss of USD 440m – meaning USD 10m a minute. The company’s stock fell by 80% in two days.

What happens here is that, even as brave as you have been for going through all this development and the efforts you developed for understanding it expecting some kind of knowledge incoming, a much higher degree of complexity around its variables is pointed out and prevent anyone to master it. It seems to be uniquely solvable through a rigorous research agenda that may able to help us understand, as future responsible market operators and perhaps managers, the global implications of such practice. Meanwhile, I will keep on feeling that in the environment of this milliseconds or nanoseconds reactivity, the frontier between the three main different steps of information search, decision-making and execution is fading somehow. And I will not be able to help thinking about understanding this sort of (dangerous) “paradigm distortion” lying on the obvious difference observed between HFT and non-HFT agents’ operational timescales, eventually promising a world in which no humans would trade on markets anymore. A terrible caricature I will admit, however consistent with the common observation of automated strategic systems applied on longer time-scales arguably creating a behavioural edge over human traders as they eliminate the emotional factors which are largely responsible for the fact that in their vast majority traders demonstrably underperform a simple buy-and-hold strategy over long periods of time. Disembodied actors with fast execution abilities apparently being the key for surviv… I mean profit.

Lucas LASSUS

 


BONDS & SHARESBONDS & SHARESMarch 5, 2014
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10min2480

We all know that emotions can affect our judgment when we trade. That is why, we are going to describe the most important emotions that we need to control:

The rules are unique for each person. You have to fix your own rules according to your personality. Each time you take a decision, you can try to put your decision into an emotion and check if you respect your own rules. Remember that human is emotional so decision can be. If you think that your emotion wasn’t rational, you were under pressure so you focus and be honest with yourself. These rules permit to fix a philosophical thinking of trading that reach the discipline necessary, so you can change it and adapt it during the time you trade and learn about yourself.

EGO

  • Choose the opportunities
  • Make a break every 5 winings in a row
  • Looking ourself objectively
  • Have a good strategy doesn’t mean being a good trader
  • Do not overestimate yourself (70% of people do)
  • Only the market is right
  • Using logic skill and not instinct
  • Do not lie to yourself, don’t exagerate the facts
  • Focus on the process and not the result

APATHY

  • Continuing review positions and work with discipline
  • Do not play a game
  • Sports to get more mental
  • Always thinking to improve yourself
  • Get out of the routine if necessary
  • Doing other things than trading, find a balance life
  • Be passionated of work
  • Do not give up face to difficulty
  • Mental, Discipline and Rigor (MDR)
  • Be in good health when trading (eat breakfirst)

EAGERNESS

  • Precipitation lead to fail
  • Using confortable money management for feeling relax
  • Eagerness lead to Ego
  • Make regular breaks after every trades
  • Taking time to take a decision is a good strategy
  • Do not be influenced by other people
  • Discipline is more profitable
  • We take decision to win money, even it is boring
  • Better quality than quantity
  • Precipitation can show a big variation of results
  • DO NOT fall to risk all the money, keep mental
  • Take responsabilities

CERTAINTY

  • Do not find certainty in our position
  • Certainty is a wasting of time
  • It feed our ego
  • There is no certainty on uncertin market
  • Theorical results is just forecast
  • Always find to improve our strategy and backtest it
  • Do not think against-productive
  • Learn slowly
  • Stay focus on the process of the strategy before getting conclusion

ETHICS

  • We are not Jesse Livermore
  • We all have weakness
  • What we perceive is limited at what we know
  • 70% of people overestimate themself
  • A man without weakness is a man without emotion
  • Emotion is natural

MISCONCEPTION

  • Do not fall on wishful thinking
  • Do not stuck on one position result
  • Money come and back naturaly
  • Misconception make people blind
  • Succes is disproportionate
  • If there is market, there us money
  • We are not right, only the market is right
  • Study books don’t being more profitable « loosing time »
  • Target break even is not profitable
  • Emotion are natural and needed but have to be canalized

HEURISTIC

  • Focus on processus
  • Don’t be influenced by results
  • Pass results have to be canalized, it leads to greed
  • There is no chance or luck on random market
  • Do not react from revenge of the past

ANXIETY

  • We trade to earn money
  • We are not playing money, we are working
  • Money has always in impact in human mind
  • Take some relax time oustide of trading
  • If needed, take a long break
  • Try to not think about trading
  • Being addict when necessary is a good thing to compete
  • Losing and failing is natural in trading
  • Respect his Money management strictly

FEAR OF FAILURE

  • Try to love working on what we do
  • Fear have to be a pleasure but canalyzed
  • Passion mean sacrifices and taking risks
  • Results should not have influence in our mind, but the process
  • Love to sing instead of becoming rich and famous
  • Don’t do anything is also a decision making

In trading, we need to plan a strategy and follow it with discipline. But it is not enough to success. We must also focus on our emotions. This is the difference between a winner trader and a looser trader. If we are at least aware of our different emotions, so we can easily find our weaknesses. Emotions described above need to be controlled or known by the trader.

 

Vicky TSANG

 



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