Trading

Most assets in the world are traded. Where there is trade, there can be speculation.

In finance, speculation is a financial action that does not promise safety of the initial investment along with the return on the principal sum [30]. This is contrary to an investment. Speculation is often called active trading and is usually done with a short time horizon. The type of trading this system does is to be considered speculation as the plan is to generate returns by buying and selling positions in assets relatively often.

The Virtue of Speculation

One concern that might be raised about active trading is of social nature. Some claim that pure speculation is just a form of institutionalized parasitism that brings no value to society. However, this does not take into consideration a wider per-spective. Businesses need risk capital to grow. Few investors are willing to lock their capital down for as many years as the company would need it. With a liquid financial market this can be mitigated by giving investors the ability to get rid of

14 Financial and Investment Theory

their exposure in the company at any given time. Speculation increases the liquid-ity of financial markets, thus attracting investors to growth businesses that need time to mature. In turn, this ushers forward bottom up growth and puts pressure on existing companies to stay profitable and innovative. Furthermore this increase in trading activity will in itself make the markets more efficient as more or less rational investors will correct all arbitrage options they might find.

Categories of Traders

There are many different types of traders active in the various markets. They are often categorized by their trading time-frame. Alternatively it is possible to categorize based on what kind of strategies they apply. The most common will be introduced and presented with the field of algorithmic trading as a backdrop.

In general there are some main distinctions to make. There is difference between technical and fundamental trading. Fundamental trading includes factors outside the price of the security; typically a company’s accounts are used. Technical trading however is only based on the actual price and its qualities. Technical traders base their strategy on the assumption that historical price data can in some way predict future prices. These aspects will be further elaborated on in 2.2.

The degrees of which analysis one employs affect the time-frame, as fundamental analysis are inherently much more static than technical. One can get a price update several times per second, while the company results are only published once a quarter. Fundamental data are also more qualitative and thus harder to analyze quickly, e.g. news. Analysis of technical data is purely quantitative, and can thus be handled by computers. Generally the shorter time-frame, the more automatic are the traders. Additionally the risk is can be seen higher as the market converges toward a zero-sum game when the time-frame considered decreases¹. Position Trading. The longest time-frame is often called position trading. It generally consists of all positions held longer than a few months. This is a very reputable strategy, recommended by Warren Buffet himself[128], but with a limited possibility of return. Since one has plenty of time to do a thorough analysis of the asset, algorithmic methods have less advantage here, but can be used as supplementary guidance. This category also includes more active investors, who are active in a different sense than earlier described. They take an active part in management of the company they’re invested in, like private equity companies.

Swing Trading. Positions held over days or weeks include strategies like swing trading and more short-term fundamental analysis strategies. This is generally

1The long term increase called the equity premium[106] does only apply if one holds a position for some time. Trades where one aims to hold a position as short as possible will thus in principle be a zero-sum game as one trades against a snapshot in time where all values are fixed.

Time Horizon Trader

Years

Months

Weeks

Days

Hours

Minutes

Seconds

Milliseconds Algorithmic

Technical Traders

Human Fundamental

Traders

Position Trading

Swing Trading

Intraday Trading

High-Frequency Trading Automation

Figure 2.1: Trading time horizon and automation.

the shortest time-frame one finds purely fundamental analysis traders. Changes in price on a lower scale than days are often considered noise to these traders.

There is some technical analysis done over several days, but it is limited. This is because the primary goal of pure technical analysts is to speculate on price swings.

A shorter time frame will give more than enough volatility to do this, due to the fractal² nature of the stock market.

Intraday Trading. Intraday trading is trading confined to a single day, most day-traders sell their positions before close. This is mainly speculation and mostly done by technical analysis, though one might supplement with fundamental techniques.

2A fractal is a mathematical concept where roughness exist at whatever resolution one uses.

The graph of price a different time periods will tend to have roughly the same kind of volatility.

16 Financial and Investment Theory

Day trading can be a job for human investors, but require much time and is quite close to a zero sum game due to the lack of the long term equity premium. Intraday trading is becoming the realm of machines as they can search through much more data. Most machines are however trading on more or less instant strategies where the aim is to hold an actual position as short as possible; these are called High-frequency traders.

High-Frequency Trading. High-frequency trading (HFT) is a poorly defined term. In this paper it is used in its semantic meaning of all trading done at a high frequency instead of meddling with all the contradictory definitions in the literature. With this meaning of the term, HFT will be a broad concept that includes all trading where the trading speed is used as a competitive advantage.

In 2010 these systems trade on milli- and microseconds[75]. All HFT is done by algorithms, as the speeds required for this trading type are beyond human capabilities.

Low-Latency Trading. Low-latency trading is a subclass of HFT, and can be thought of as a specific strategy of HFT. These are a naive set of simple algorithms which sole advantage is their ultra-low latency, direct market access. An example of a low-latency strategy is to survey the news. The instance good news hits the market, a low-latency trader will buy from slower sellers which have not had time to increase their bid price, and then sell to a new higher price. Most of these tactics revolve around quickly finding and exploiting arbitrage possibilities. There is tough competition in having the fastest algorithms and the lowest latency. This activity is very capital intensive due to the hardware requirements and it needs a certain initial capital. There are few amateurs in this area and most actors are large banks, funds or even specialized algorithmic trading firms[32].