Our Philosophy

Before the launch of this website, many existing theoretical concepts were scrutinized and thought over. Many practical investment tools were given due consideration. Below is a condensed summary of matters that were examined during the research phase. Many investing approaches that came to attention were computer modeled and tested. The outcomes of historical data tests helped to better understand the effectiveness and efficiency of different investment styles and practices. Trial and error process was at the heart of the research process. Investment principles and philosophy of this website gradually took shape. Finally, a set of proprietary stock picking algorithms was put together and tested. There is no such thing as guarantee of success when it comes to stock market trading techniques. Time will tell how the algorithms will perform in the long run. It will still be, to a large extent, a matter of luck. Stock picking makes sense only to an extent that the risk adjusted return of a portfolio exceeds that of a broad market (alpha). Otherwise, a broad market passive portfolio would be a better option. Just to stay on par with a broad index is a very ambitious and many times unattainable goal for many experienced investors, leave alone seeking to generate alpha.

Although referring a different topic, a great idealist of the past wrote “How anything can be changed at all, how it is possible that one state in a given time is followed by another at another time, of that we have not the slightest conception a priori. We want for that a knowledge of real powers, which can be given empirically only…” (Kant, 1922, p168-169), He further continued “What can be considered a priori, according to the law of causality and the conditions of time, are the form of every change…” (Kant, 1922, p169). Another great philosopher, a materialist stated "All arguments concerning existence are founded on the relation of cause and effect; and our knowledge of that affect is derived entirely from experience; and that all our experimental conclusions proceed upon the supposition that the future will be comfortable to the past.” (Hume, 2007, p26). “In reality, all arguments from experience are founded on the similarity...” (Hume, 2007, p26). “From causes which appear similar we expect similar effects.” (Hume, 2007, p26). "When we transfer the past to the future, in order to determine the effect, which will result from any cause, we transfer all the different events, in the same proportion as they appeared in the past... “ (Hume, 2007, p43). “Being determined by custom to transfer the past to the future, in all our inferences; where the past has been entirely regular and uniform, we expect the event with the greatest assurance, and leave no room for any contrary supposition.” (Hume, 2007, p42). “…the supposition, that the future resembles the past, is not founded on arguments of any kind, but is derived entirely from habit..." (Hume, 1911, p134-135).

An uncertainty is inherent to stock market investments. An uncertainty arises from a requirement of making judgements about future events. We make judgements about the future relying on our inferences from the past. But the causes that led to certain outcomes in the past may only resemble the current causes, but be different in nature. Causes may vary in significance of influence and may be accompanied by other different causes that were not present in an experience observed in the past. There can be new cause-effect relationships, which were not previously observed through experience. As a result “cause fails of producing its usual effect” (Hume, 2007, p42). There is a temptation to think that the mankind has been able to develop a sufficient knowledge to make judgements about any phenomenon or concept. In many cases this is a very correct supposition. Unfortunately, not everything can be learned about. Future is such a concept. There is no way to know future for sure. “The idea that the future is unpredictable is undermined every day by the ease with which the past is explained.” (Kahneman, 2011, p225). When it comes to the stock market predictions we can only speak in terms of probabilities. That does not mean that the forces that cause changes in stock prices should not be scrutinized. Anything that may potentially help improve the quality and reliability of judgements about the future is worth the effort.

Arguably, the major forces that move stock prices include: macroeconomic forces (GDP, employment, inflation, investments, interest rate etc. related data), microeconomic forces (related to the individual public companies’ financial information), industry-specific developments and data, market sentiment, trends, and news (politics etc.). Those professionals whose primary interest rests with micro and macroeconomic data as well as industry data are said to be the proponents of fundamental analysis. Those who concentrate on market sentiment, trends and news are called technical traders. When it comes to fundamental analysis, there is a great deal of very well grounded and systematized body of knowledge. Arguably, proponents of fundamental analysis can be split into two vast groups. There is no strict division. Professionals tend to use different techniques to their benefit. But for the sake of conveniency it would make sense to make such a distinction.

The first group of the proponents of the fundamental analysis relies on the prospective financial figures. Usually, with regards to a particular public company, it is a forecast of the normalized financial statements, which allows to arrive to expected future free cash flows (FCF). This exercise requires a rather deep understanding of company’s business and of the industry it belongs to. An understanding of an overall economic perspectives of a particular country and perhaps of a world economy should also be taken into consideration. Derived future FCFs (including terminal value CF) then get discounted at weighted average cost of capital (WACC) rate. Without going into unnecessary details let us jump straight to the conclusions. After spending many months preparing different computer models, the following subjective opinion was reached. The universe of valuation techniques based on the prospective data can be described as the place where the countless number of variables gets wrapped in endless number of assumptions (For example, WACC can have multiple defensible values and a small change in the WACC rate can translate into very significant change in valuation results. Another example, all figures in a prospective statement of profit and loss (P&L) are simply best estimates. A slightest change in an expected revenue growth rate changes the entire valuation figures significantly). As a result, almost any valuation figure falls within the range of reasonably expected outcomes and is defensible. This happens because brilliant financial theories through the means of beautiful mathematical calculations struggle with a stubborn reality of unpredictability of the future. Various valuation models will only provide its user with a theoretical (intrinsic) value, which may be very different from the actual stock price at the exchange. This does not automatically mean that the company’s stock is over or undervalued on the exchange. Intrinsic value differs from stock price by definition. This happens because of existence of other factors such as, for example, market sentiment. “When the price of a stock can be influenced by a “herd” on Wall Street with prices set at the margin by the most emotional person, or the greediest person, it is hard to argue that the market always prices rationally. In fact, market prices are frequently nonsensical.” (Buffett, 1984, p 13).

The second group of the proponents of the fundamental analysis relies on historic financial data. Financial statements are used to derive different ratios such as price to book ratio, price to earnings ratio, return on equity ratio etc. Ratios alone are not enough to make practical inferences in terms of potential sell or buy decisions. Additional information is necessary. Such information includes: thorough understanding of company’s business model, competitive environment, quality of management etc. Usually, value investors prefer to buy companies that they believe are severely undervalued by the market. Long story short, many attempts to simulate trading decisions based on different ratios revealed promising results. However, it was decided not to pursue this approach. Firstly, it seemed impossible to fully automate the analysis process. Subjective decision making was necessary. Secondly, an approach requires a long-term investor mentality. Historical financial statements are made available only few times a year. Investment horizon spans over years. The longer the investment horizon the more the uncertainty. “…I let our marketable equities tell us by their operating results - not by their daily, or even yearly, price quotations - whether our investments are successful.” (Buffett, 1988).

The long-term focus of fundamental analysis supposes at least basic understandings of the macroeconomic trends. Theoretically, the significance of macroeconomic factors grows as the time horizon expands. The longer term the investment the more serious consideration should be given to the macroeconomic trends. Macroeconomic predictions are way more difficult than predictions about individual public companies. For example, Keynesian economics talks about overall output of goods and services in a perspective of changes in investments and savings (mainly affected by government spending and taxes) and changes in money supply (mainly affected through interest rates and changes in prices). To keep everything very basic - low taxes, large government spending, low interest rates and lower prices lead to real GDP growth, but also lead to large budget deficit, which is usually covered by debt. Thus, large budget deficit theoretically will sooner or later translate into higher taxes and reductions in government spending, that will hamper a GDP growth. Taxes, government spending, interest rates, prices and inflation, debt (remember that each of these terms, for example taxes and fiscal policy, represents a separate vast field of study). Availability and quality of a labor force and availability of production capacities are other major variables. Availability of natural resources surely matters. In open economies international environment has a great significance. To summarize, it is very difficult to form an independent yet correct opinion about the future macroeconomic trends. In addition, all policies can change and therefore make any long-term predictions obsolete. “…macro-economics is a tough game in which few people, Charlie and I included, have demonstrated skill.” (Buffett, 2005).

Fundamental analysis with its focus on micro and macroeconomic data and somewhat longer-term approach proved to be of little help. After years of research, modeling, and testing, it was time to turn to technical analysis with its focus on market sentiment, stock price trends and news. "It is evident that all sciences have a relation, greater or less, to human nature..." (Hume, 1911, p4). “Economics…is a social science and is therefore concerned primarily with those economic problems whose solution involves the cooperation and interaction of different individuals.” (Friedman, 1962, p7).

Market sentiment can be described as a general belief among majority of stock exchange players. It does not matter whether that belief is rational or not. It is a very powerful force that creates an objective reality. “Belief…causes an idea to imitate the effects of the impressions...". (Hume, 1911, p120). Fear, admiration, surprise other passions "...vivify and enliven the idea, that it resembles the inferences we draw from experience." (Hume, 1911, p120). "Accordingly, we may observe, that wherever that influence arises from any other principles beside truth or reality, they supply its place, and give an equal entertainment to the imagination." (Hume, 1911, p122). "When the imagination… acquires such a vivacity…there is no means of distinguishing between truth and falsehood; but every loose fiction or idea, having the same influence as the impressions of the memory, or the conclusions of the judgment." (Hume, 1911, p123). “We thus have an impression of a state in which an individual's separate emotion and personal intellectual act are too weak to come to anything by themselves and are absolutely obliged to wait till they are reinforced through being repeated in a similar way in the other members of the group…” (Freud Sigmund, 1949, p82)."...they [feelings exhibited by a crowd] present the double character of being very simple and very exaggerated...”. (Le Bon, 1920, p56)."We see [in a crowd] ...the turning by means of suggestion and contagion of feelings and ideas in an identical direction …" (Le Bon, 1920, p35). “Trotter derives the mental phenomena that are described as occurring in groups from a herd instinct.” (Freud Sigmund, 1949, p83). “We know that people can maintain an unshakable faith in any proposition, however absurd, when they are sustained by a community of like-minded believers” (Kahneman, 2011, p225). "Still, though the wishes of crowds are frenzied they are not durable. Crowds are as incapable of willing as of thinking for any length of time" (Le Bon, 1920, p44)

Market sentiment defines trends and to a significant extends stems from the information that is available to the market. News may be pure facts. Press releases, publications of financial statements or news related to changes in government policies are examples of such news. However, a large amount of information represents interpretations and expert opinions. Such news may be influenced by widespread beliefs or other considerations. Opinions may be contradictory. “Their [Humans] view of the world is limited by the information that is available at a given moment, and therefore they cannot be as consistent and logical...” (Kahneman, 2011, p276). “…reason is the recent development of the newspaper press, by whose agency the most contrary opinions are being continually brought before the attention of crowds. The suggestions that might result from each individual opinion are soon destroyed by suggestions of an opposite character." (Le Bon, 1920, p169). “Another reason for the inferiority of expert judgment is that humans are incorrigibly inconsistent in making summary judgments of complex information. When asked to evaluate the same information twice, they frequently give different answers. The extent of the inconsistency is often a matter of real concern. Because you have little direct knowledge of what goes on in your mind, you will never know that you might have made a different judgment or reached a different decision under very slightly different circumstances. Formulas do not suffer from such problems. Given the same input, they always return the same answer”. (Kahneman, 2011, p233).

Presumably, investing is an applied science, which uses scientific knowledge of formal sciences such as mathematics and logic and social sciences such as economics and psychology. Investing, thus, has to do with both exact sciences and social sciences. Stock market investing involves rational and irrational elements. Rational and irrational decisions blend and determine the current prices at the stock exchange at any given time. In contrast to fundamental analysis, through statistical methods, technical analysis attempts to capture and describe regularities in stock price changes that are attributable to market sentiment and human psychology. Once described, such regularities are used to predict short- and medium-term stock price movements. “Short-term trends can be forecast, and behavior and achievements can be predicted with fair accuracy from previous behaviors and achievements. The line that separates the possibly predictable future from the unpredictable distant future is yet to be drawn” (Kahneman, 2011, p188). Technical traders focus mainly on the history of changes in share prices and volumes of trading. Information is readily available. Technical traders employ a long list of different strategies. Several dozens of most widely known approaches were computer modelled and tested. The results were inconclusive. Although none of the tested technical analysis strategies proved to outperform the broad market, it became clear that technical analysis can be effective. Because of the ready availability of the most up-to-date information and relative simplicity of the technical analysis concepts technical analysis tools are very efficient. To avoid all the inefficiencies caused by human nature, algorithmic trading approach with no human involvement in decision making process seemed to be the best option for the purposes of this web site. “Why are experts inferior to algorithms?” ”…experts try to be clever, think outside the box, and consider complex combinations of features in making their predictions. Complexity may work in the odd case, but more often than not it reduces validity. Simple combinations of features are better. Several studies have shown that human decision makers are inferior to a prediction formula even when they are given the score suggested by the formula! They feel that they can overrule the formula because they have additional information about the case, but they are wrong more often than not.” (Kahneman, 2011, p190).” Fortunately, the hostility to algorithms will probably soften as their role in everyday life continues to expand.” (Kahneman, 2011, p194).

IN LUE OF CONCLUSION

Future is uncertain. Whether it is fundamental analysis or technical analysis. When it comes to stock market investing there is no, and most probably there will be no magic formula. Fundamental analyses and particularly value investing is an excellent approach for stock market investment decision-making. However, it presupposes lengthy investment horizons and fails to consider all stock market forces. The two biggest disadvantages of fundamental analysis are its imprecision and its requirement for human decision making and, hence, its susceptibility to irrationality and emotional decision making. Speculative trading based on technical analysis is riskier, but can potentially be more profitable. Technical analysis is perfect for algorithmic trading. Algorithmic trading removes human factor and thus eliminates emotions and irrational behavior. Technical analysis presupposes short- and medium-term focus. To achieve an edge, a proprietary technical analysis indicators are necessary. In the process of development of such indicators the following general requirements were set forth and later achieved: 1) The logic that the algorithms employ should have a clear economic or psychological explanation. 2) Algorithms should have a greater tendency to go long rather than short. 3) During historical data tests, algorithms must match or outperform respective broad indexes. 4) During historical data tests, algorithms must demonstrate efficiency on lengthy historical data sets form different markets across the world. 5) During historical data tests, algorithms must demonstrate efficiency on different timeframes including hourly, daily, and weekly stock price timeframes.

REFERENCES

Kant Immanuel. (1922). Critique of pure reason. London: Macmillan & Co, Ltd.

Hume David. (2007). An Enquiry concerning Human Understanding. Oxford: University press

Hume David. (1911). A treatise of human nature. London: J.M. Dent & Sons Ltd

Le Bon Gustave. (1920). The Crowd. A study of the popular mind. London. T. Fisher Unwin Ltd

Freud Sigmund. (1949). Group psychology and the analysis of the ego. London. The Hogarth press

Kahneman Daniel. (2011). Thinking fast and slow. USA. Farrar, Straus and Giroux

Buffett Warren E. (February 29, 1988). Chairman Letter – 1987. https://berkshirehathaway.com/letters/1987.html

Buffett Warren E. (February 28, 2005). Chairman Letter – 2004. https://berkshirehathaway.com/letters/2004ltr.pdf

Buffett Warren E. (1984). The Superinvestors of Graham-and-Doddsville. Columbia Business School Magazine.

Friedman Milton. (1962). Price Theory. Chicago. ALDINE Publishing Company