▷ Today’s Trading Ecosystem 【2023】

Today’s Trading Ecosystem

The markets have undergone a paradigm shift and, thanks to technological advances, in just a few years we have seen how trading has gone from being carried out entirely by people on the floor to fully electronic operations. This has contributed to the emergence of new players, new ways of trading and even new markets in the world of investment..

Unquestionably, all of this has led to the democratization of investment, allowing access to retail traders, who would not have participated just a few years ago. In this regard, it is no coincidence that most retail traders lose. The entire industry is set up to ensure this is the case, so that their participation simply serves as yet another (very small) source of liquidity for the market.

It is important to keep your feet on the ground. The world of trading and investing is too complex for a home-based retail trader with an internet connection and a computer to make any significant return on their capital. The odds are stacked against them, starting with the fact that the situation is dominated by large institutions which dedicate huge amounts of money both to the development of powerful tools and to the hiring of the most skilled people.

We will now take a very basic look at some of the lesser-known aspects of the current trading ecosystem They are of some relevance, since they could influence our trading approach.

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Types of participants in Financial Markets

Familiarizing ourselves with those who have the ability to influence price movements puts us in a better position to make trading and investment decisions. The financial markets are made up of a whole host of agents. Their trading methods will differ, based on their needs at any specific time.

One of the biggest mistakes we can make is to think that all market movements are orchestrated by a single entity; or to classify traders as either professionals or non-professionals. When these terms are used, along with “strong hands” and “weak hands” it is in order to understand who has greater control of the market, not as a battle between institutions and retail traders. As we know, the latter can do little or nothing when it comes to the most traded assets.

Keep in mind that everything also depends on the volume traded in each particular asset. As that volume increases, more intervention will come from the big players.

For example, one of the largest assets traded worldwide, the American S&P 500 index, is almost entirely controlled by large institutions, with at least 90% of volume traded by these sources. This is a battle they wage among themselves. No trade can be executed unless one institution is willing to take one side of the position and another institution is willing to take the opposite side. The market wouldn’t be able to move a single tick if there wasn’t an institution behind each movement.

By contrast, assets that trade at very low volumes can be influenced by traders with less capacity. That is why I wouldn’t recommended trading assets with low liquidity, to avoid possible manipulations.

Our objective, then, is to analyze the behavior of the chart, to try to determine on which side most of the institutional money lies.

Let’s categorize the different market participants according to their intent:

Hedging

This involves executing financial trades aimed at canceling or reducing risk. These trades consist of the acquisition or sell of a product that is correlated with the asset on which the hedge is to be established.

While it is true that the main objective of hedging is to limit risk, it can also be used to secure a latent profit or preserve the value of a fixed asset. These traders don’t care in which direction the price moves, since this is not part of their core business. They do not trade with any directional intention, but with a more long-term vision.

Although there are different ways of hedging, the most traditional one focuses on the producer.

An example of this would be an airline company that buys oil futures as a way of balancing its fuel costs.
Another example would be a large international import and export company that buying foreign exchange to hedge against possible price changes.

Market makers would also be included in this category, since they might go to the market in order to ensure the neutral risk of all their positions as a whole, depending on their needs.

Speculation

Unlike hedgers, who basically trade to reduce their exposure to risk, speculative traders actively take on risk when they open their positions.

If, given the current market conditions, they believe that the price of the asset in question is cheap, they will buy. And vice versa if they consider it to be expensive.

The sole aim is to obtain a profit from the price movement. This category includes hedge funds, investment funds, trading firms and, in general, any institution that trades directionally in the market to seek profitability. They trade under all sorts of different time frames and also execute trades using high-frequency algorithms.

They are the most active players in the financial market. They basically focus on finding liquidity zones as, due to the large volumes they move, they need to find a counterparty to match their orders.

There is a very common misconception that all institutions are profitable. Many of these institutions are the preferred prey of agents in financial markets, because they move significant amounts of money and may have a weak trading model.

Although they are not purely speculative, some options traders could be included in this category as, if they have a large open position in the options market, it is very likely that they will also go to the futures market to try to defend them, if necessary.

Arbitrage

This consists of taking advantage of the imperfections of the financial market. These traders see an inefficiency in prices and execute trades with the aim of correcting this and adjusting prices.

There are different forms of arbitrage: trading a single product, trading different correlated products, trading between different markets and even trading between contracts with the same and different expiration dates.

An example would be trading a decorrelation between two markets for the same asset, such as the spot market and the futures market. For example, the euro against the dollar (EURUSD) currency pair and the derivative in the futures market (6E). An arbitrage strategy will take advantage of the minuscule price difference that may exist between these two markets to obtain a profit.

Aside from this we also have the Central Banks. They have the greatest capacity since they determine the monetary policies of countries mainly through the establishment of interest rates.

Of the types we have looked at, the only one that would enter the market with the directional objective of adding pressure to one side or the other would be the speculative trader. The other forms of transaction would have a different intention but would also ultimately be represented on the price. The fact that not all trades are speculative is a very important factor to take into account. Many make the mistake of thinking that every trade has a directional interest behind it, and in most cases this is not true. There are many types of participants that interact in the market and the needs of each one are different.

In addition to the intention behind the trade, it is worth highlighting the different time frames used by one or other trader. While some take into account the short term, others apply medium or long-term strategies. The key point is that each and every one of the movements in the market is being supported by a large institution and that at any moment another may enter that has a longer-term perspective with a greater capacity to influence the price.

Electronic markets

Since 2007 the exchanges have gone from being controlled by humans to fully automated, electronic environments. Really it is only computers which now handle the processing for matching orders.

With the emergence of new technologies, IT advances and regulatory changes to the financial world, speed when transmitting and receiving data has become increasingly important. So much so that, today, electronic trading accounts for most of the traded volume.

The most traded products such as futures, stocks and CDS indices are the most electronified; at 90%, 80% and 80% respectively. By contrast, corporate bonds are at the lower end of the spectrum, since they represent more tailor-made products, with investment grade and high yield bonds at levels of 40% and 25% respectively.

All these advances have made it possible to improve the efficiency of the market by adding liquidity, reducing costs, increasing the speed of execution, improving risk management and allowing access to specific markets.

Algorithmic Trading

This is a process of executing orders based on well-defined and programmed rules, carried out automatically by a computer, with no human intervention.

It uses complex statistical and econometric models, on advanced platforms, to make decisions electronically and independently.

It mainly uses price, time and volume as variables and was developed to take advantage of the better speed and data processing offered by computers in comparison to human traders.

These strategies interpret market signals and automatically implement trading strategies based on these factors, with trades of different duration.

The increase in market share in the recent years of algorithmic trading across all types of assets is simply spectacular. Forecasts for the coming years are along the same lines.

One of the reasons for this growth is the emergence of artificial intelligence in the financial sector.

High Frequency Trading

High-Frequency Trading is a type of algorithmic trading applied at the microsecond level, which aims to take advantage of very small changes in asset prices.

It is based on the use of mathematical algorithms, which are used to analyze the market and execute orders based on current conditions. They carry out thousands of trades in a short space of time, earning money systematically and with a high probability of success.

The main advantage is the speed of processing and execution, achieved thanks to the deployment of powerful computers. This means that amateur home-based traders simply do not have the means to access this type of trade. Therefore, it is a style reserved almost exclusively for institutional traders with large amounts of capital.

The share in the American stock market consistently represents over 50% of the total volume traded. In Europe it is slightly lower. It is worth noting how the 2009 crisis led to a decrease in the implementation of HFT, mainly due to increased competitiveness, high costs and low volatility.

Don’t confuse High-Frequency Trading with the automatic systems that a retail trader might create (which do fall into the category of algorithmic trading). Generally these types of tools (known as EAs, robots or bots) are not usually very effective; unlike High-Frequency Trading tools, which cost millions of dollars and have been developed by large financial firms for daily trading with large amounts of money.

How do high-frequency algorithms affect us?

The fact that in today’s markets most of the volume traded comes from highfrequency algorithms does not greatly influence the structure-based analysis that we can carry out. This is mainly because we are not competing to exploit the same anomalies.

While our analyses seek to take advantage of a deterministic aseptic of the market, where we try to elucidate who has more control (buyers or sellers), high-frequency algorithms are more geared towards the random aspect of the market, mainly due to their categorization: arbitrage, directional strategies (momentum and event-based) and market making (liquidity ratio). Although it is true that some algorithms can execute directional strategies (with the aim of benefiting from price movements), these only cover the very short term.

Although they could distort our analyses, the advantage of the Wyckoff Method is that it provides a structural framework, allowing us to minimize some of the noise found in the shorter time frames and to gain a more objective feel for current market conditions, by taking into account a larger context than these algorithms encompass.

Over The Counter (OTC) Markets

This is a type of electronic market where financial assets are traded between two parties without the control and supervision of a regulator, unlike in stock exchanges and futures markets.

The main difference between centralized markets (On-Exchange) and non-centralized markets (Off-Exchange) is that in centralized markets there is a single order book which is responsible for connecting all the participants of that market; while in non-centralized markets there are multiple order books (as many as there are market makers) where the lack of transparency regarding the depth of the market is made evident by the BID and the ASK price.

In recent years, the American market has undergone a process of fragmentation, in which more and more decentralized markets have been created. Currently, US stock liquidity is distributed between 88 different sources, with almost 40% of trades taking place in non-centralized markets.

Non-centralized markets contain different types of broker, depending on the way they handle their clients’ orders. On the one hand, there are those who have a dealing desk that act as the client’s counterparty (known as Market Makers); and on the other those that do not have a dealing desk (Non Dealing Desk) that act as intermediaries between the client and the rest of the market.

This second type, non-dealing desk brokers, are the ones I recommend working with. The reason is that the Market Makers are in charge of offering the final price of the asset, making the process less transparent.

Since they can be the counterparty to their clients’ trades, this opens up the possibility of a conflict of interest, because if the client wins, the broker loses and vice versa. And obviously the broker will do everything possible to ensure the profitability of their business.

When you combine the fact that the owner of the market is in charge of offering the final price and that they can be the counterparty at the same time, one of the main dangers for the retail trader is that they may suffer as a result of price movements being manipulated.

It is also important to know that, due to the very nature of this type of non-centralized market, there may be different prices for the same asset. In other words, if we want to trade the EUR/USD currency pair, each market maker will offer us a different price and volume.

How do OTC markets affect us?

The problem with these types of market is that our analyses will be based on data that might be a valid and significant representation of the market, but could just as easily not be representative of all price and volume data.

To guarantee the reliability of our data, we need to analyze the asset in question in a centralized market. Continuing with the example of the EUR/ USD, we would need to analyze the futures market (centralized market) which corresponds to the ticker $6E.

Therefore, I recommend that if you do not have the economic capacity (sufficient capital) to trade in said futures market, you analyze the asset in this futures market and execute the trade through another more affordable financial derivative such as the CFD (Contract For Difference) with a good broker (not a market maker). An intermediate option would be to trade the small version of the future, the micro future, which, in the case of EURUSD, corresponds to the ticker $M6E.

If you open a chart for the future (6E) and the CFD (EURUSD) you will see that the price movements are practically the same, even though they are different markets. This is possible thanks to an arbitrage process carried out by high-frequency algorithms, which occurs systematically between both markets.

Dark Pools

A Dark Pool is a private market (Off-Exchange) that puts institutional investors in contact with each other and facilitates the exchange of financial assets. What is particular about this sort of market is that the transactions are not reported immediately, and the amount traded (volume) is not disclosed for 24 hours.

In the US, non-centralized markets represent approximately 35% of equity trading, with about 16 to 18% traded in Dark Pools. And according to a study by Bloomberg transactions in Dark Pools already represent over 30% of the total volume traded as a whole.

The market share of Dark Pools in European equity trading has expanded rapidly in recent years, growing from 1% in 2009 to 8% in 2016.

When a large institution wants to buy or sell a huge amount of an asset, it goes to this type of market. This is mainly because it knows that if it accesses the public market it will be difficult to find a counterparty and it will possibly obtain a worse price, while exposing itself to predatory techniques, executed by high frequency algorithms, such as Front Running. In this type of market traders avoid these negative effects and at the same time obtain better commissions since they save on the fees required by the public markets.

Contrary to what many people may think, Dark Pools are highly regulated, since their owners are registered with the SEC (Securities and Exchange Commission) and FINRA (The Financial Industry Regulatory Authority) and therefore are subject to audits and regular examinations, similar to those of a public market.

In addition to private financial institutions, there are public exchanges that have their own Dark Pools, such as the New York Stock Exchange (NYSE), the most traded and liquid stock exchange in the world.

The CME (Chicago Mercantile Exchange), which is the market with the largest number of futures and options contracts in the world, also has its own Dark Pool and offers this opaque trading service through what they call “Block Trades”. Its own website offers information on this matter, including the following:

“Block trades are privately negotiated futures, options or combination transactions that are permitted to be executed apart from the central limit order book. Only “Eligible Contract Participants” or ECPs are permitted to transact blocks. The qualifications are formally defined in the Commodity Exchange Act Rule 526 (“Block Trades”) governs block trading in CME, CBOT, NYMEX and COMEX products. Block trades are permitted in specified products and are subject to minimum transaction size requirements. These vary according to the product, the type of transaction and the time of execution. Block trades must be transacted at prices that are “fair and reasonable” in light of the size of the transactions, prevailing market prices in the futures and other related markets, and other relevant circumstances”.

How do Dark Pools affect us?

The activity carried out in Dark Pools has important microstructural implications as it plays an important role in determining intraday returns and the uncertainty that may be related to them.

So we might be analyzing an asset in which very significant transactions have been carried out in a hidden manner and obviously we cannot even assess the intentions of the buyer.

Since they are not determined by the supply and demand of the public market, these transactions do not have an immediate impact on price formation. However, there are studies that claim that public market traders react to the report of orders executed in the Dark Pool once it is released, which can significantly alter the analysis of the interaction up to that moment.

Randomness vs. Determinism

This is another of the major debates that generates huge controversy among the trading community. The vast majority of those who position themselves in favor of the randomness of the market do so with the aim of discrediting technical analysis as a useful tool. On the other hand, we have those who look at each and every price movement and believe there is intent behind them all; a big mistake. Not everything is black or white.

Randomness is based on the premise of market efficiency. Determinism (non-randomness) is based on its inefficiency.

The random market approach implies that the current price already reflects all the information of the events that occurred in the past and even of the events that the market expects to take place in the future. That is, all the information about the asset is entirely discounted and therefore it is not possible to predict the future price action. The logic is that, when participants try to take advantage of new information, they mutually neutralize said advantage. This leads to the conclusion that there is no advantage to trying to interpret the market per se, unless the trader has access to insider information.

The deterministic market approach suggests that price movements are influenced by external factors, so by knowing what these factors are, the future price action can be predicted. Therefore profits can be obtained by correctly interpreting the market.

When we talk about randomness, we refer to the fact that there is no logical intent behind the movement of the market; it is simply a price fluctuation. Randomness is born of the innumerable variables that exist in the market. No one can possibly know how the rest of the market participants are going to act. If someone knew, they would implement a deterministic system to predict the right outcome every single time.

On the one hand, if the Efficient Market Hypothesis (EMH) and the randomness of the market were valid, no one would be able to obtain profits on a recurring basis. And history has shown that this is not the case. We all know big players in the financial markets who have managed to win with different approaches (technical, fundamental and quantitative). Moreover, the efficient markets hypothesis is heavily criticized because it assumes agents act rationally in all their decision making.

On the other hand, financial markets cannot be modeled as a totally deterministic process in which there is no randomness. This would result in strategies with 100% probability of success and this (as far as we know) is not the case.

The Adaptive Market Hypothesis

We are, therefore, led to the conclusion that financial markets are made up of a percentage of randomness and a percentage of determinism, though we cannot attribute a proportion to each.

This theory is supported by the Adaptive Market Hypothesis (AMH) which shows the efficiency of financial markets, not as a characteristic that either exists or doesn’t exist, but as a quality that varies according to market conditions (the environment, context), which are determined by the interactions between agents.

This hypothesis was presented by the American financial economist Andrew W. Lo in his book Adaptive Markets published in 2017 and is mainly based on the following points:

The efficiency of the market depends on its condition. This changing characteristic is the result of the interactions of the participants, which in turn depend on market conditions.
The agent is not fully rational and is subject to cognitive biases. Participants form expectations based on different factors. For this reason a purely rational model cannot be applied. Moreover, different expectations may be created based on the same information, not to mention the fact that each agent is risk averse to a different extent.

Although the author refers to agents as individual people, this is equally applicable to the current trading ecosystem in which, as we have already mentioned, practically all actions are carried out electronically, by algorithms. This doesn’t alter the principle of the adaptive hypothesis. Regardless of who the market participant is and the way in which it interacts with the rest of the market, it will make its decisions based on the valuations, motives or needs that it has at a given moment. That given moment will be conditioned by different factors, factors that will change over time and therefore change the evaluations, motives or needs of the participants.

AMH doesn’t focus on discrediting the Efficient Markets Hypothesis, it simply treats it as incomplete. It places more value on changing market conditions (due to the emergence of new information) and how participants can react to these. It focuses on the fact that rationality and irrationality (efficiency and inefficiency) can coexist in the market at the same time, depending on the conditions.

How does the Wyckoff methodology fit in?

Moving on to what really concerns us, interpreting the market under the principles of the Wyckoff Method is based on a deterministic market event: The law of Cause and Effect. Because for the market to develop an effect (trend) a cause (accumulation/distribution) must first have occurred. There are other deterministic events that can offer an advantage, such as seasonality.

An example of random behavior could be seen in High Frequency Algorithms. We have already discussed some of their uses and they are the perfect example of forces that have the ability to move the market without necessarily having any directional logic behind them.

Finally, it is worth noting that most studies defending the randomness of the market use traditional chartist patterns such as triangles, head and shoulders, flags, etc. or some price pattern with no underlying logic behind it, to confirm the lack of predictability of technical analysis in general. Our approach to trading the markets is far removed from all of this.

There are studies that have shown how, using a tool as simple as trend lines, you can observe non-random behavior in financial markets, and even exploit anomalies to obtain some return.

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