The Myths about Forecasting, Business Cycles and Time Series, Which Prevent Economists to Forecast: With an Application to Shipping Industry

Abstract

People did not forgive economists for not forecasting the two great depressions. Especially the second one in end-2008 — which followed the 1929-1933 “ Great Depression ” (starting on 29/10/1929: the “ Black Tuesday ” ). Keynes in 1936, wrote a book on “ economics of depression ” , and showed the way how full employment—through marginal efficiency of capital—can be achieved. He was bypassed by: his death (1946) and his disciples’ efforts to “ model economic growth ” (Harrod, 1939 and Domar, 1946). Progress in capitalistic economies cannot be achieved…without Keynes’ animal spirits. The “ wrong beliefs ” of my fellow economists, which we called them “ myths ” for sensation, were showed: “ myths ” about business cycles, time series and forecasting. Though in the long run we are all dead, economic history…remembers. The “ trade cycle ” theory, which eventually became “ business cycle ” , was in scientific focus from 1907 to 1941, and then disappeared. Cycles made the life of shipowners difficult since 1741: one cycle every 10 years ! Ships, however, are assets of long life, living 3.2 times the typical shipping cycle—and we said—for the first time—that the “duration of a shipping slump is related to the durability of ships”...Moreover: cycles are influenced by the state of technology; this stated also for the first time; cycles do not go up x years and exactly x years down. Maritime economists by this made shipowners and ship pers happy: but, as shown, most freight rate’s peaks lased 1 - 2 years and troughs lasted up to 12 years (1947-2016)…Cycles, early in history, attracted the attention 1 of many writers (we counted 449 writers, including Keynes with 12 papers). Most believe that “ trade cycle theory ” started with Jevons (in 1909), but as Mandelbrot and Hudson (2004; 2008 preface [1] ) wrote, Bible described a cycle of 7 years up and down; cycles cannot be predicted and their trends and turning points cannot be found. We have showed that these are not true. Myths concerned also time series like: time series have no memory; they move at the square root of time (H = 1/2)—as proved by Einstein (1905)—and they are best represented by “bell” curve. Hurst (1951) showed that Einstein’s case is a special one, and time series can move faster or slower than that. More important was that if H > 0.50 ≤ 1, time series have to produce cycles : this is an important finding. The general formula shown here includes coefficients: alpha (fat tails; risk), beta (skewness), gam m a (scale) and delta (location). Alpha indicates the height of a distribution and the longevity of its tails— indicating what the real risk is , when a variable falls beyond 3 σ — “ Dow ” fell 22s away on Black Monday 1987, and the freight rates index ~10 σ in end-2008 meltdown…. The myths about forecasting are connected with the fact that econometricians prefer to predict nonlinear time series using linear tools (e.g. GARCH 2 ). We did the opposite: we forecast the nonlinear (shipping) time series index of dry cargoes 1741-2015 (7 years inside the sample and 5 years outside it) testing 5 nonlinear methods and eventually selecting the best one ( i.e. the “ Kernel density estimation ” ). The deviations obtained were from 2% to 10% (yearly) from actual—we also indicated a falling trend. In fact there is no turning point up in shipping dry cargo market…by 2020…