Factors influencing stock prices
There are probably two major influences on stock prices: fundamental aspects of the underlying business, and investor expectations of future company performance. I like to break these down into five factors that are generally agreed upon as the primary factors in stock prices.
- MARKET: The overall valuation and performance of the stock market, including the macroeconomic effect of interest rates, inflation, etc.
- INDUSTRY EXPECTATIONS: The consensus outlook and structure of the industry or industries within which the company does business.
- COMPANY EXPECTATIONS: The consensus expected earnings, cash flow, sales growth of the company.
- FUNDAMENTAL: The company's characteristics, such as book value of assets, recent earnings experience, and recent sales growth.
- PSYCHOLOGY: Investor over-reactions to news events, herding behavior, and stock analyst rating biases, and analyst neglect, all influence stock prices.
Unfortunately, there is very little agreement on how these factors combine to generate prices.
NightScope is a nonlinear, data-driven, FUNDAMENTAL pricing model. The remaining factors, other than the MARKET which acts as the backdrop for the model, are assumed to be captured in the difference between the current market price and the model price.
Value Investing and Fundamentals
The NightScope model works on valuing the company's FUNDAMENTAL factors. The most successful value investors, like Warren Buffet or Peter Lynch, openly advocate ignoring the current state of the MARKET. Instead, they look for healthy companies that are trading at prices below the value of their fundamentals. They also have their own, understandably vague, mental models for figuring out the impact of EXPECTATIONS factors. Although they have both written extensively on the subject of value investing, it seems to be extremely difficult to replicate their decision making process well enough to consistently match their performance.
Value perspective
This is a value based approach to stock picking. I believe that the best strategy for a typical investor is to hold a diversified portfolio and pay a reasonable price for each stock. That's harder than it sounds, because prices fluctuate so much. The model uses advanced Artificial Neural Network (ANN) technology to make good estimates of the correct price to pay for a given set of fundamentals. If a stock is trading above this price, it is up to the investor to determine whether or not the premium is justifiable. What might justify a premium? A premium would be justified if the company will grow a sustainable earnings stream above the average for companies with similar characteristics.
Interpolation rather than extrapolation
The model interpolates over the actual market prices and fundamentals in the market. I am not forecasting or extrapolating the price return a day, or a month, or a year from now. Instead I am modeling the relationship between key fundamentals and price that exists in the market at the time the model is fitted. I then compare the actual market price with the model price and note the premium or discount at which the stock is trading relative to that justified purely by the fundamentals.
In essence, the model prices stocks by taking the average price of all the stocks in the training set (typically 2500-3500) with similar characteristics. I do not address the question of whether the market as a whole is overvalued. Instead, I assess the value of a given company within the context of the market as a whole. Actually, it's a bit like using neighborhood "comp prices" for figuring out the value of a home.
Isolating fundamental value
It is my opinion that the premium or discount of the stock over or below the model price contains the effects of EXPECTATIONS and INVESTOR PSYCHOLOGY. Further, I subscribe to the idea that a company's stock price is a complicated function of the factors listed above. This hypothesis is supported in some of the more radical finance literature (and by the generally low predictive power of linear risk models.) For example, the best linear risk models in use today capture about 40-50% of risk -- that leaves a lot of room for a nonlinear pricing framework.
Stocks are priced differently than bonds or derivatives
At the risk of offending readers with quantitative finance backgrounds, here are some basics about the key pricing differences between stocks and bonds or derivatives. Bonds and derivatives are priced using arbitrage methods. These instruments are priced by building a portfolio of securities that has exactly the same type and timing of cash flows. The original instrument must trade at a price sufficiently close to the replicating portfolio to preclude the taking, after transaction costs, of riskless arbitrage profits. Stocks are different because, in general, it is not possible to construct a replicating portfolio. Stocks are priced through an equilibrium of "Supply and Demand" and, in some ways, their price behavior is more similar to real estate than bonds. Of course, an important difference between stocks and real estate is the use of structured exchanges -- the presence of exchanges creates a far more efficient market.
Copyright ©1996 by Gordon Rios.
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