Quantitative Analyst Quotes

Graham was not only the original quantitative analyst, to whom today's whole school of such thinking owes its heritage, but he was also a source of much of the fundamental analysis and lore that Wall Streeters follow today.

The nature of risk may be the single most important argument for the use of quantitative analysis in investment management. Neither Investors nor Analysts can be blamed for this fact. Nor can Harry Markowitz. Nature made risk a quadratic function. Markowitz only discovered it.

Laney had recently noticed that the only people who had titles that clearly described their jobs had jobs he wouldn’t have wanted. If people asked him what he did, he said he was a quantitative analyst. He didn’t try to explain the nodal points, or Kathy Torrance’s theories about celebrity.

Over the years, my brain trust of more than twenty-five people has included a guy who was number one in his class at Caltech, a department chair of economics at a major U.S. university, mathematical savants, computer wizards, PhDs, and quantitative and database handicappers who live and breathe algorithms and theoretical angles not found in your average textbook. Our team members act like hedge fund analysts, assigning a numerical value to every conceivable factor or variable capable of affecting sporting events to within a tenth of a point. In the NFL alone, I have several teams of experts working independently. They have never met each other, even though most have worked with me for more than thirty years, funneling their information to one common denominator: me.

The evaluation of securities and businesses for investment purposes has always involved a mixture of qualitative and quantitative factors. At the one extreme, the analyst exclusively oriented to qualitative factors would say, “Buy the right company (with the right prospects, inherent industry conditions, management, etc.) and the price will take care of itself.” On the other hand, the quantitative spokesman would say, “Buy at the right price and the company (and stock) will take care of itself.” . . . Interestingly enough, although I consider myself to be primarily in the quantitative school (and as I write this no one has come back from recess—I may be the only one left in the class), the really sensational ideas I have had over the years have been heavily weighted toward the qualitative side where I have had a “high-probability insight.” This is what causes the cash register to sing. However, it is an infrequent occurrence, as insights usually are, and, of course, no insight is required on the quantitative side—the figures should hit you over the head with a baseball bat. So the really big money tends to be made by investors who are right on qualitative decisions, but, at least in my opinion, the more sure money tends to be made on the obvious quantitative decisions.

The organizational consequence of this highly quantitative image of defense decision-making is an independent and high-level office of systems analysis (or program analysis) reporting directly to the secretary. This office, separated from the parochialism of the individual services, commands, and functional offices of the Defense Department, is charged with de novo analysis of the services' program proposals (and, indeed, with the generation of alternative programs) to assess the relative merits of different potential uses of the same dollars. Its activities culminate in the secretary's decision on a single coherent set of numerically defined programs. This model imposes a requirement for close interaction between the secretary of defense and the principal program analyst. A suitable person for the job is difficult to obtain without granting him or her direct access to the secretary. This model, therefore, requires that the chief program analyst report directly to the secretary and it inevitably limits the program and budget role of the other chief officials of the OSD, especially the principal policy adviser. The model leaves unresolved how the guidance for the analysis process is to be developed and even how choices are to be made. Analysis is not always made rigorous and objective simply by making it quantitative, and not everything relevant can be quantified. At its extreme, it can degenerate into a system in which objectives become important because they can be quantified, rather than quantification being important because it can illuminate objectives.

The ECB in June became the first of the world’s main central banks to push a key policy rate below zero. But after Thursday’s cuts Mr Draghi said he saw no scope for further reductions. While yields on shorter-dated bond yields typically held by banks have fallen, the impact of the ECB’s latest measures on longer-term debt is less certain. Yields on benchmark 10-year bonds should rise if the ECB succeeds in raising expectations about future growth and inflation rates. However, speculation that the ECB could still launch a full-blown “quantitative easing” programme and buy government bonds would have the opposite effect. Analysts said even the asset purchase programme announced on Thursday could have QE-type effects.

Youssef Zohny began his journey in investment advising and wealth management as a quantitative analyst. From there, he gained expertise, skills, and grit relating to the industry that allows him to be the successful advisor he is today. He currently focuses on helping clients manage accounts and investments ranging from trust funds to family offices.

What Do the Results of a Successful Tour of Duty Look Like for the Company? A successful mission objective delivers results for the company for either quantitative or qualitative goals, such as launching a new product line and generating a certain dollar amount in first-year revenues, or achieving thought leadership in a specific market category, as measured by the writings of industry analysts. At LinkedIn, for example, managers ask, “How will the company be transformed by this employee?” What Do the Results of

The evaluation of securities and businesses for investment purposes has always involved a mixture of qualitative and quantitative factors. At the one extreme, the analyst exclusively oriented to qualitative factors would say, “Buy the right company (with the right prospects, inherent industry conditions, management, etc.) and the price will take care of itself.” On the other hand, the quantitative spokesman would say, “Buy at the right price and the company (and stock) will take care of itself.” As is so often the pleasant result in the securities world, money can be made with either approach. And, of course, any analyst combines the two to some extent—his classification in either school would depend on the relative weight he assigns to the various factors and not to his consideration of one group of factors to the exclusion of the other group. Interestingly enough, although I consider myself to be primarily in the quantitative school (and as I write this no one has come back from recess—I may be the only one left in the class), the really sensational ideas I have had over the years have been heavily weighted toward the qualitative side where I have had a “high-probability insight.” This is what causes the cash register to really sing. However, it is an infrequent occurrence, as insights usually are, and, of course, no insight is required on the quantitative side—the figures should hit you over the head with a baseball bat. So the really big money tends to be made by investors who are right on qualitative decisions but, at least in my opinion, the more sure money tends to be made on the obvious quantitative decisions. As