IFI recognizes that the ultimate test of any investment forecasting system is its ability to correctly and repeatably forecast future asset prices – throughout the cycle.
To deliver maximum forecasting accuracy, our models and forecasts incorporate the best elements of markets and free market economics as well as fundamental and technical analysis. To uncover the most reliable signals of price changes and portfolio returns amid asset classes, regions, sectors and investment styles, we rigorously measure and test the signalling power of a wide range of inputs and relationships against the objective standard of actual, long-history, never-revised market prices. Every year we recalculate all of our model inputs’ correlation coefficients to check whether they still matter and if so, how much. As one result, we’ve proven that for the five main asset classes and subclasses in the six- and twelve-month forecasting horizons, prices – and only prices – always forecast best. By contrast, despite the widespread use of economic-accounting data by others in our industry, it simply isn’t so that investment returns are predicted by prior moves in such data; more often, the data lag. Indeed, most investment returns are registered prior to movements in the economic and accounting-based data.
We capitalize on the reliable signaling power of price changes in one asset class to forecast another. We have learned that the only way to determine and measure the effect of a price change in one asset class upon another is by a multi-year, multi-factor regression analysis that controls for each of the factors that tend to influence shifts in the second asset’s prices – both contemporaneously and lagged. For example, we’ve learned that bond prices affect and are affected by money market rates that affect currencies and stocks. Precious metals prices affect commodity prices that affect bond prices.
Globalization and politicization of markets have made the reliability of the inter-market approach preeminent. No longer can a money manager afford to remain isolated in single asset class or sector – say, using oil to forecast itself. Indeed, traditional technical analysis which looks at one industry functioning in isolation ignores the interconnected nature of markets and the major asset classes’ market prices. Such analysis is less reliable because it’s provincial – it foregoes the manifold anticipatory, strategic and risk-reduction benefits available only from allegiance to the connected nature of markets. IFI uses inter-market technicals – to identify causal, predictive relationships like equities to inflation, different sectors relative to interest rates, P/Es, dividends, growth, and yield curves. IFI leverages the signaling power of one market to forecast another.
Arbitrage-Pricing Theory (APT)
IFI finds that market prices are the most efficient means of incorporating the rational, forward-looking expectations of market participants – those with their own (or their clients’) money on the line. As such, prices contain implicit forecasts of financial returns and risks – forecasts whose basis is the up-to-date, combined intelligence of all buyers and sellers in a particular market at a specific time. Further, markets are both global and interconnected: exploitable relationships exist among currencies, commodities, bills, bonds, equities, regions and their dependent contexts like developed/emerging, value/growth and others. Finally, prices are never revised after-the-fact. Price levels for the Dow Jones Industrial Average since 1896 or the S&P500 since 1958 are enduring constants. Prices are objective – hence, reliable.
IFI integrates these price-based inputs using APT, a quantitative method that uncovers causal connections between asset classes (including signals from futures and options markets) and points investors toward profitable strategies. IFI’s models do not rely on unrealistic theories (such as the Capital Asset Pricing Model), on backward-looking, flawed and often revised statistics issued by government or on the presumption of “market failure” (such as the “bubble” myth).
Markets are Efficient and Forecastable
Advocates of efficient markets insist that financial asset returns are a cause-less, “random walk” and that investment managers cannot, therefore, consistently outperform benchmarks through superior forecasts. They advise a passive strategy of buying, holding and re-balancing. Those who believe, in contrast, that managers can actively out-perform, tend to do so by claiming markets are irrational and perpetually mis-priced.
IFI believes this is a false alternative. Markets are both efficient and forecastable. Precisely because market prices are efficient integrators and anticipators of information relevant to security valuation, they also serve as high-quality inputs for reliable forecasting models.
New information requires revised valuations. Shifts in the government “policy mix” (changes in the monetary, tax, regulatory and foreign policies of the major industrialized nations’ governments) are an important source of new information – for good or ill. Moreover, unavoidable time lags exist between movements in asset prices, not because markets are inefficient but because no productive process – be it the construction of a factory or the construction of an investment portfolio – can be finalized or adjusted instantaneously.
Modern Portfolio Theory (MPT)
IFI recognizes and exploits the vast historical evidence demonstrating that over 80% of managers’ performance is determined by initial asset allocations, whether among stocks, bonds and cash or within sub-sets of major asset classes. Stock-picking and “market-timing” techniques, while not irrelevant to performance, are usually overwhelmed by longer-term and broader shifts in the returns from major asset classes. Reliable forecasts of the returns and risks likely to be generated by broad asset classes necessarily benefit performance-oriented investors. Accordingly, IFI does not endorse portfolio diversification for its own sake, or as a default position reflecting agnosticism about the future. In some cases, “big bets” are fully – and conservatively – justified by a given juxtaposition of market prices.
IFI uses objective, statistically-based market analysis to identify the causal and exploitable patterns that exist among market prices and asset classes. Our quantitative models are developed and tested by rigorous regression techniques. We advise investors against “single-market myopia” or the use of subjective “hunches,” “data mining,” emotionalism or naïve, technical trend extrapolation devoid of causal significance.
We’ve demonstrated how markets are governed by the incentives faced by self-interested producers, savers and investors. A “policy mix” of sound money, low marginal tax rates, minimal regulation and free trade is most optimal for wealth creation. But powerful disincentives also exist and harm markets. A punitive policy mix repels capital and warrants a focus on its protection. Accordingly, IFI warns clients against relying on today’s failed variants of “demand-side” economics (whether Keynesian or Monetarist).