We often hear about the two most common investment methodologies and philosophies, one is fundamental and the other is technical. I am here to introduce, demystify and educate people on the often misunderstood philosophy of quant investing.
Quantitative investing seeks to reduce potentially adverse human biases and bases investment decisions solely on data, only on the facts; he is emotional and disciplined. Quantitative investing is generally a more rigorous use of science and mathematics than fundamental investing. The “quanta” are not trying to understand the nuances of an idea, but are analyzing patterns and scanning thousands of data points for statistical consistency.
Now while this may sound more “out there”, it is in fact MORE common in our everyday lives, or in almost every aspect of our existence. Every time we use our mobile phones, we’re using the results of mathematical rigor, every time we get into our cars, we benefit from solid scientific studies on everything from the crush zones that keep us safe to the angles of the car that maximize your performance. Better yet, we rely on science and numbers to get astronauts into space, to steer man-made machines into the vast emptiness of space, and stay on perfect course! So, in my opinion, it is perfectly logical to use the same methods to invest. Yes, fundamental investors have a place in the investing world and yes, they can extract hidden value by talking to management and learning about the specifics of a product or market segment. But, just as solidly as math can get us to the moon, it can help design a successful investment methodology.
In quantitative analysis, quants like me look at price behavior, which is actually the behavior of people who trade stocks. The up and down movement of a stock over the course of a day is really the battle between buyers and sellers, each with their wide variety of reasons for making buying or selling decisions. With this in mind, what becomes relevant are things like “who is winning the fight”, which looks at where he closed the action in his range, or “who is more aggressive”, which can be seen by looking at how quickly move. in one direction or the other, or “how strong are the buyers”, which can be seen by studying the volume behind the buy orders. In other words, a more granular look at the activity of buyers and sellers is really an analysis of supply/demand dynamics, which in almost any econometric model can tell us more about the situation and, in particular, about the greater chances that a certain event occurs. result. Simply put, if the demand is constantly increasing, you want to own that!
Let me explain further why the statistics used by the quants are, in my opinion, more relevant than the ratios calculated from balance sheets and income statements. All the information on a balance sheet or income statement is exactly what most (fundamental) investors use to make their decisions about whether to buy or sell. From a quantitative perspective, the reasons behind the buy or sell decision are irrelevant; quants just want to see the consensus results of those decisions. If there is something fantastic on the balance sheet, millions of people will start buying a stock and the stock will start to perform better. The quanta will notice this force and jump right on it. So in the end, I think quantitative investing is an integral conduit for knowing what all the balance sheets and income statements are saying. With this in mind, I suppose you could say that quants are inadvertently exposed to balance sheets and income statements by looking at what traders do.
Another argument I often hear against quantitative modeling and investing is that it relies on historical stock and price activity and as a result uses a more limited source of information than, say, fundamentalists. As explained above, historical trading activity is by definition the broadest source of information, as all other information, no matter where it was collected from, is added to people’s trading decisions based on that information. . Whether from conversations with management, trips around the world to each and every store, or in-depth analysis of balance sheets, income statements, or quarterly reports, every investment decision results in a purchase or sale to some price and with a certain size.
Therefore, when studying price/volume activity, quants capture ALL of this information. In a way, it is Darwinian, that is, all the information evaluated by market participants is reflected in their collective buy/sell decisions (trading activity), which ultimately reveals the consensus opinion of the market. If a management conference call was attended by many, some listeners didn’t like it and others liked it, and I’m just one of the listeners, I only have a single source of information (my personal liking or disliking). But if I look at stock performance after the call, I see what the majority decided, which is probably the most accurate interpretation and therefore the most likely predictor of future outcome.