Investment agility in fragile global environment
P.S.-1 (5.2.2020) … The article below is written already more than 4 years ago, yet I still believe that it contains good groundbasis for souls and minds, who want to dig deeper into the matter. After 2014, due to my professionally developed illness … , I personally have stepped aside from the financial world (world with a small letter … substantial, yet incrementally small part of the Universe…. :) ) and 4 years are very long time for the AI networks mentioned below, also some of the legislation may have changed … The mathematics and the prime fundaments though haven’t changed, that’s why as a front picture now I enclose a great book, containing a lot from the core basics of business and financial mathematics … However the analytical mind and lightning precision of the AI networks, use much more advanced maths (not only… I mean philosophy, physics, programming and so … ) … hence you shall search and read more …
Hello, this time I’ve decided to share some thoughts about investment strategies in the really volatile environment we live in. In brief and theoretically we have three prime dimensions of financial analysis — 1) fundamental financial analysis which is based on a variety of financial ratios and coefficients calculated on the basis of the financial statements of an enterprise on both accrual and cash-flow basis. I want also to mention that the latter slightly defers for publicly listed companies and not listed companies and that is firstly because the financial statements of the publicly listed companies are done under different accounting standards and principles (ex. IFRS, US GAAP and so, normally regards the consolidated financial statements) and secondly because for the public companies the coefficients and the majority of calculated ratios are based on market values and number of issued stocks. Nevertheless the prime dimensions of the fundamental financial analysis are solvency, profitability and liquidity for the state of the business, plus of course dividend and market value returns for the owners/investors. — 2) Technical analysis of the movements of the key stock-exchange indexes, which normally is done by following technical levels of the trends, often expressed by moving averages or any other well describing the movements function and its inflection points. — 3) Psychological analysis of the markets/investors, which in brief explores the market sentiments and psychologically based reactions of the human investors J, a little bit later you’ll see why I say so. Well starting backwards, with the fast digitalization of the World including the financial one, the psychological analysis starts having diminishing weight in the weighted average in the investment decisions, if I can say so and that is because it concerns mainly the small investors or at least that part of them not using sophisticated financial software for investing or trading. Yes, nowdays substantial part of the investments and especially the trading (buying and selling within short periods of time) are done via robots, neuron financial systems or other kind of sophisticated high-end software. In brief the neuron financial systems (robots) are based on sophisticated programmes and trading-algorithms which in some cases resemble self-learning artificial intellect that optimizes its behaviour given its past experience and the momentous changes of the environment around it. On top of that its prime function is to optimize the profit, regardless of the direction of movement of the market. In my modest experience often the red (negative markets) are more profitable, because their movements are sharper and deeper and this is what a good trading algorithm needs, movement within which it’s capable of doing thousands of orders per second and that is good for the owners of such well optimized algorithms. But then despite the fact that the small investor is left out of the woods, the powerful algorithms have some really bad sides, such as the flash crashes capable of crashing even the New York Stock exchange . That usually happens when you have several or many powerful algorithms targeting the same market or big enough peace of it, then in given robot-sensitive circumstances (could be on either micro or macroeconomic level or even rumors, speculations or so J) the algorithms start simultaneously crashing technical levels of the mentioned above technical analysis (or other trading logic they may use) and the market is smashed. Just to mention that technically the direction of such robust cumulative movements could be either up and down, but usually when speaking about flash-crash, we mean down movement and nowdays the regulations of many markets include suspension of trading of the financial instruments of a firm or even whole market when quick and unusually big movements are detected.
Then quite often the pricing of an asset, let’s assume stock happens “occasionally” within the “scissors” of opened by the robots (or their owners) hedge/trading positions, simply by trading the news of the day — once again do not forget that a good algorithm could win in either direction … Since the things I try to describe might be difficult to comprehend by a normal person I’ll try to give a kind of short example of opened trading/short positions. For instance as of today 13.9.2015 on the Helsinki Stock-Exchange there are 8 opened major short positions against Outokumpu Oyj (if you want to see more about the “short-sell” Regulation see here (EU) No 236/2012 of the European Parliament ).
All of the above are well established financial institutions trading with really state-of-the-art algorithms and you have to be really good to opt against them … I personally would not recommend that, yet I know people that profit following the movements of the big guys, if I can say so. Just to mention that the above opened short positions have different spots and to some extent algorithm behaviour and in real trading they play against each other. I have tried to ask about the spot prices and the maturity of the opened short positions from the Finnish Financial Supervisory Authority but got no answer. I asked as a private person and do not know if that knowledge is available for the institutional investors, but in my view the lack of the parameters of trading does not support the market transparency equally.
And at the end if you are a normal person or a small not institutional investor and ask me what to do I might answer be wise and careful. In the above described circumstances solely luck would not be enough neither with trading (very dangerous game) nor in a long run (exceptions are possible but if you rely on them better play lottery). Then more concretely try to choose solvent firms with good profit prospective. The solvency might be chosen either as equity ratio or P/B quotient, gearing or so depending on the branch of the business and it shall give you some general security about longer run financial stability. Then try to find businesses with good profitability prospects — in theory the intrinsic value of a firm is roughly the discounted present value of its future cash-flows. Again in theory, comparing the latter against current market value of the stock or other important measurement you could see if the firm is under or over estimated, BUT do not forget the algorithm pricing I tried to describe above in it perceiving win the robots could do whatever they need to. Just for example during the last year the above mentioned Outokumpu Oyj, which business has accumulated tremendous losses during a longer period, has jumped between roughly 4 and 8 euro/stock pretty much because of the algorithm pricing. Then try to diversify your portfolio in different firms and branches, for a small investor 3 to 5 firms might be enough. Well also try to explore the behaviour of the main investors of the chosen business as well as the trading with it algorithms if you wish — all of that is valuable knowledge and I hope you could profit from it.
Kind regards ,,, Rosti …
