Demand derived analysis: A new form of investing

There are many different schools of investing such as fundamental analysis, quantitative analysis and technical analysis. This essay is an exploratory look into what I’m going to call ‘demand-derived analysis.’

The idea came from an essay I wrote on housing, where because housing lacks an obvious fundamental to tie prices to, I instead used incomes. The basic idea was that as housing (in London at least) has relatively fixed/inelastic supply you could assume that in the long-run house prices in an area should be highly correlated with incomes in that area, in particular, your long-run views on housing should simply be a function of your long-run view on incomes. If you believe there is going to be increasing inequality in incomes across London then you should invest in expensive areas like Chelsea/South Kensington. If you believe there is going to be increasing equality in incomes then you should target poorer areas. What’s interesting about this approach is incomes and the associated maximum buying power (as dictated by lending standards etc.) mean above a certain price threshold demand just disappears (it’s not even price elastic it’s just a complete disappearance).

What is not clear to me is how this highly budget sensitive market operates with speculators. I suppose the key question is what percentage of the market are speculators? If the number is very large then perhaps they can collectively lead to self-reinforcing bubbles with the presumption that the bubble will burst to a level that is aligned with most house buyers budget constraints. The implication, seems to be, that even in markets with a high number of speculators there is a long-term envelope which is demand-derived and a function of buyers budget constraints.

The reason I think this is interesting is because none of the investing approaches seem to look to directly measure investors demand-constraint. Instead as with fundamental, quantitative and technical approaches the focus is more on the thing getting traded rather than the constraints of those doing the trading. The financial crisis however, would seem to suggest that – in recessions at least – the investing appetites of market participants seems to not just a factor but the most important factor in determining prices.


The basic idea then is to try and predict the demand-constraints of market participants. Market participants rather than the safer approach of trying to find the best deals possible and then mapping those out on a spectrum of risk and reward and building portfolios accordingly instead first decide upon their required risk and reward appetites and then try to find assets that match those descriptions. I suspect this, admittedly subtle, distinction leads to lots of self-enforcing bubbles as market participants who need, for example, 10% of their portfolio to be high return, say 20%+ then go find assets that fit that description and collectively make those assets have those returns through their collective buying behaviour. Peter Thiel, the billionaire investor and entrepreneur has in fact argued that one of the reasons for the housing crisis and the technology bubble is that investors are looking for massive returns where there are none. The returns should be found in investing in technologies but Thiel argues that VCs have been too conservative focusing on the world of bytes rather than bits which has led to the weak returns in VCs and the bubbles in other markets.

Thus my demand-derived investing approach starts with the risk-reward appetite of investors. This appetite is not so much a function of the actual risk-reward returns that are possible but rather what risk-rewards are required to be a competitive fund. Therefore if a competitive fund requires:

10% high yield (20%+) 30% mid yield (10-20%) 40% low yield (5-10%) 20% T-bills (0-5%)

Then this will in turn determine the demand for the different asset classes that match these different yields and my main hypothesis is that the investor demand for level of yield is the biggest factor in determining the price of assets that match each yield class.

If that hypothesis is true then

1) the buying power of market participants (including the a priori competitively determined portfolio yield requirements) is the primary factor in determining the prices of assets. Self-reinforcing bubble dynamics can mean that simple excess demand and constrained supply can be sustained for long periods of time – thus even if high yields don’t exist the market’s demand for them can make them appear (in the short-run).

2) each yield band of asset class can be treated as largely independent markets from each other. Within each band assets are direct substitutes because investors chase returns wherever they can find them regardless of which asset class they are found in.

3) In the long-run the appetite for different levels of risk is a function of the perceived level of uncertainty. Thus even if you cannot accurately predict what will happen you can still make money as an investor simply by tracking the increases and decreases in uncertainty around different asset classes and the resulting affect on demand and supply. I.e. demand = f(level of uncertainty) not a f(what will actually happen). Thus in analyzing future events you only need to evaluate whether the outcome is increased or decreased uncertainty rather than the implications of what will actually happen in the different states of the world.