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Fundamental value seems like a straightforward investment approach. One simply looks for assets that are “cheap” or “expensive” relative to their rationally expected risk-adjusted discounted cash flows. In reality, conscientious estimation of fundamental value gaps is one of the most challenging strategies in asset management. Value opportunities arise when market prices deviate from contracts’ present values of all associated entitlements or obligations. This requires a lot of information and estimation. Instead, analysts prefer simple valuation ratios, such as real interest rates or equity earnings yields with varying enhancements. Moreover, value strategies can take a long time to pay off and positive returns may be concentrated on episodes of “critical transitions”.
However, there are ways to make value trading more practical. Historically, it has been easier to predict relative value between similar contracts rather than absolute value. Also, simple valuation ratios become more meaningful when combined with related economic indicators. Thus, long-term bond yields are plausibly related to inflation expectations and the correlation of bond prices with economic cycles and market trends. Equity earnings yields can be enhanced by economic trends and market information. And effective exchange rates become a more meaningful metric when combined with inflation differentials and measures of competitiveness of a currency area.
In finance, the fundamental value of a security or derivative contract refers to the expected risk-adjusted present value of all cash flows or, more generally, all associated entitlements or obligations. Estimating such value conscientiously would require three essential ingredients:
This conscientious approach could reveal value gaps, differences between the present value and the market price. A contract would be “cheap” if the market price was below the present value and “dear” if it was above. However, this theoretical approach also makes high demands on research, requiring [1] flexible financial modeling skills, [2] advanced statistical inference, and [3] good judgment on what the relevant uncertainties look like (called “priors” in Bayesian analysis). In practice, few institutional investors have the budget, capacity, and know-how for such research, leave alone the patience.
The most popular references for “cheapness” or “dearness” of financial assets or contracts are simple price-based valuation ratios, such as trade-weighted real exchange rates for currencies, real interest rates for fixed income instruments, or earnings yields for equity. These simple ratios are easy to understand and monitor in real-time. They also have considerable intuitive appeal. For example, a real trade-weighted exchange rate informs on the effective inflation-adjusted appreciation or depreciation of a currency, which should be in accordance with economic performance and competitiveness. Real interest rates help to assess the plausibility of a particular path of monetary policy rates. And in the equity space, forward earnings yields in relation to real bond yields are a basic sanity check for stock prices.
However, these simple valuation ratios are not valid approximations for fundamental value gaps. There is typically a good reason why these valuation ratios are high or low relative to historic averages. The real challenge is to sort the right from the wrong reasons. In other words, judgment on whether valuation ratios are too high or too low depends completely on context. Moreover, because standard valuation ratios are so popular and easy to use, they cannot, by themselves, offer much information advantage. Hence, without further analysis valuation ratios cannot plausibly be a great source of investor value.
In the absence of easy and objective valuation metrics, price-value gaps can be wide and persistent. This inertia may be frustrating for “value traders” but can also offer huge profit opportunities when markets undergo critical transitions. Critical transitions are structural changes in economic backdrop, market regime, and institutions that precipitate a re-evaluation of prices and establish “new trading ranges”. It is in those times that conscientious estimation of fundamental value pays off. Quantitative signals can help detect when such a transition is underway. The signs include a slowdown in corrections to small perturbations in prices, increased autocorrelation of prices, increased variance and skewness of prices, and a “flickering” of markets between different states. (view post here). The basis of such analysis is complexity theory, which describes critical transitions in complex systems and assumes that systems evolve as dis-equilibrium processes
More abstractly value strategies often produce their highest returns when previous market trends have run their course and reverse (view post here). Value and momentum strategies often end up with opposite market views. One strategy succeeds when the other fails. There are two plausible reasons for this.
On the whole, rather than being a stand-alone trading factor or even a rival to trends, value factors are a complement to trend following or momentum strategies.
Absolute value means that a contract is cheap relative to its fundamental price estimate. Relative value means that a contract is cheap relative to another contract. It is usually easier to estimate relative fundamental value across similar contracts rather than absolute fundamental value. That is because similar types of contracts have most price factors in common and one can concentrate on pricing those that are different. For example, all equity prices in one market have the same stochastic discount factor and all FX forward contracts that are traded against the USD have the same reference currency risks. Indeed, empirical analyses support the intuition that it is easier to predict relative returns within an asset class than to predict absolute returns (view post here). Moreover, directional and relative predictability have been complementary sources of investment returns.
Value-based investment strategies in the macro space typically focus on a comparison of valuation ratios, such as yields or price ratios, with related economic conditions.
A necessary condition for estimating fundamental value is a full understanding of the contract and the underlying asset. This is should not be taken for granted. Investment managers engage in some contracts only sporadically and for narrow purposes. They may not have time and patience to consider the implications of all detail. In the past areas of negligence included:
Even simple standard exchange-traded contracts may not deliver the underlying at the time and place it would be needed. In instructive example have been commodity futures in the base metal space, where at expiry holders looking for delivery would have had to accept long delays in the load-out from designated warehouses. This actually led market rationing and high premiums for physical metals over exchange traded spot prices (view post here).
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Macrosynergy is a London based macroeconomic research and technology company whose founders have developed and employed macro quantamental investment strategies in liquid, tradable asset classes, across many markets and for a variety of different factors to generate competitive, uncorrelated investment returns for institutional investors for two decades. Our quantitative-fundamental (quantamental) computing system tracks a broad range of real-time macroeconomic trends in developed and emerging countries, transforming them into macro systematic quantamental investment strategies. In June 2020 Macrosynergy and J.P. Morgan started a collaboration to scale the quantamental system and to popularize tradable economics across financial markets.