Gross capital flows: Dynamics and crises

This paper analyzes the behavior of international capital flows by foreign and domestic agents, dubbed gross capital flows, over the business cycle and during financial crises. We show that gross capital flows are very large and volatile, especially relative to net capital flows. When foreigners invest in a country, domestic agents invest abroad, and vice versa. Gross capital flows are also pro-cyclical. During expansions, foreigners invest more domestically and domestic agents invest more abroad. During crises, total gross flows collapse and there is a retrenchment in both inflows by foreigners and outflows by domestic agents. These patterns hold for different types of capital flows and crises. This evidence sheds light on the sources of fluctuations driving capital flows and helps discriminate among existing theories. Our findings seem consistent with crises affecting domestic and foreign agents asymmetrically, as would be the case under the presence of sovereign risk or asymmetric information.     

Tying the politicians’ hands: The optimal limits to representative democracy

The citizen candidate models of democracy assume that politicians have their own preferences that are not fully revealed at the time of elections. We study the optimal delegation problem which arises between the median voter (the writer of the constitution) and the (future) incumbent politician under the assumption that not only the state of the world but also the politician's type (preferred policy) are the policy‐maker's private information. We show that it is optimal to tie the hands of the politician by imposing both a policy floor and a policy cap and delegating him/her the policy choice only in between the cap and the floor. The delegation interval is shown to be the smaller the greater is the uncertainty about the politician's type. These results are also applicable to settings outside the specific problem that our model addresses.     

Has China replaced colonial trade?

Review of World Economics - China is often suspected of taking over the extraordinary trade relationships that former colonies had within colonial empires. Besides preferential bilateral...     

Anticipating critical transitions of the housing market: new evidence from China

We introduce a novel quantitative methodology to detect real estate bubbles and forecast their critical end time, which we apply to the housing markets of China's metropolises. Building on the Log-Periodic Power Law Singularity (LPPLS) model of self-reinforcing feedback loops, we use the quantile regression calibration approach recently introduced by two of us to build confidence intervals and explore possible distinct scenarios. We propose to consolidate the quantile regressions into the arithmetic average of the quantile-based LPPLS Confidence indicator, which accounts for the robustness of the calibration with respect to bootstrapped residuals. We make three main contributions to the literature of real estate bubbles. First, we verify the validity of the arithmetic average of the quantile-based LPPLS Confidence indicator by studying the critical times of historical housing price bubbles in the U.S., Hong Kong, U.K. and Canada. Second, the LPPLS detection methods are applied to provide early warning signals of the housing markets in some metropolises in China. Third, we determine the possible turning points of the markets in Beijing, Shanghai, Shenzhen, Guangzhou, Tianjin and Chengdu and anticipate critical transitions of China's housing markets via our multi-scales and multi-quantiles analyses. Finally, given these projections performed in February 2017, the price trajectories from March 2017 to January 2018 that became available from the time of submission to the time of revision of the present article offer quite unique genuine out-of-sample tests of the performances of our indicators.     

Non-parametric determination of real-time lag structure between two time series: the ‘optimal thermal causal path’ method

We introduce a novel non-parametric methodology to test for the dynamical time evolution of the lag–lead structure between two arbitrary time series. The method consists of constructing a distance matrix based on the matching of all sample data pairs between the two time series. Then, the lag–lead structure is searched for as the optimal path in the distance matrix landscape that minimizes the total mismatch between the two time series, and that obeys a one-to-one causal matching condition. To make the solution robust to the presence of a large amount of noise that may lead to spurious structures in the distance matrix landscape, we generalize this optimal search by introducing a fuzzy search by sampling over all possible paths, each path being weighted according to a multinomial logit or equivalently Boltzmann factor proportional to the exponential of the global mismatch of this path. We present the efficient transfer matrix method that solves the problem and test it on simple synthetic examples to demonstrate its properties and usefulness compared with the standard running-time cross-correlation method. We then apply our ‘optimal thermal causal path’ method to the question of the lag-dependence between the US stock market and the treasury bond yields and confirm our earlier results on an arrow of the stock markets preceding the Federal Reserve Funds’ adjustments, as well as the yield rates at short maturities in the period 2000–2003. Our application of this technique to inflation, inflation change, GDP growth rate and unemployment rate unearths non-trivial lag relationships: the GDP changes lead inflation especially since the 1980s, inflation changes leads GDP only in the 1980 decade, and inflation leads unemployment rates since the 1970s. In addition, our approach seems to detect multiple competing lag structures in which one can have inflation leading GDP with a certain lag time and GDP feeding back/leading inflation with another lag time.     

Intelligent finance—an emerging direction

Intelligent finance represents a new direction recently emerging from the confluence of several distinct disciplines in financial market analysis, investing and trading, removing any historical or artificial barrier between them. It is conceived as the science, technology and art of the comprehensive, predictive, dynamic and strategic analysis of global financial markets, towards a unification and integration of academic finance and professional finance. As a comprehensive approach, it is a quest for absolute positive and non-trivial returns in investing and trading by exploiting complete information about financial markets from all general perspectives, drawing ideas, theories, models and techniques from many related academic disciplines, such as macroeconomics, microeconomics, academic finance, financial mathematics, econophysics, behavioural finance and computational finance, and from professional schools of thought, such as macrowave investing, trend following, fundamental analysis, technical analysis, mind analysis, active speculation, etc. In terms of risk management, intelligent finance is expected to minimize the very last risk—the incompleteness of an investing or trading method or system. The theoretical framework of intelligent finance consists of four major components: financial information fusion, multilevel stochastic dynamic process models, active portfolio and total risk management, and financial strategic analysis. We first provide the background from which intelligent finance has recently emerged as a new direction in finance research and industry, and then provide a brief theoretical review of the predictability of financial markets since Bachelier. After these background discussions, we clarify the major research directions of intelligent finance.     

The Exchange Rate Macroeconomic Balance Approach: New Methodology and Results for the Euro,the Dollar,the Yen and the Pound Sterling

This paper presents an extension of the macroeconomic exchange rate balance approach. This extension comprises two new aspects. Firstly, it is based on a multinational framework which allows for macroeconomic linkages between countries. Secondly, it uses a procedure that does not require a full modeling of the world economy to derive a consistent set of equilibrium exchange rates. The findings reveal that, in 2001, the dollar was overvalued against the euro and the yen. The paper also shows that this result depends heavily on the chosen notion of current account sustainability.     

Programming and Advertising Competition in the Broadcasting Industry

We analyze competition between two private television channels that derive their profits from advertising receipts. These profits are shown to be proportional to total population advertising attendance. The channels play a sequential game in which they first select their profiles (program mixes) and then their advertising ratios . We show that these ratios play the same role as prices in usual horizontal differentiation models. We prove that whenever ads' interruptions are costly for viewers the program mixes of the channels never converge but that the niche strategies are less effective and that the channel "profiles" are closer as advertising aversion becomes stronger.     

Increasing returns,entrepreneurship and imperfect competition

We study a simple bilateral oligopoly model in which individual agents, who are initially endowed with capital, decide sequentially (1) whether they want to act as producers (entrepreneurs) or as capital lenders (rentiers) and, then (2) which quantity of capital they would like to borrow or lend, though exchange of capital units against units of the produced good. Production takes place under increasing returns to scale. We show the existence of “natural equilibria”, at which wealthier capital owners become entrepreneurs while the remaining ones decide to be rentiers. We also study the efficiency of equilibria which is shown to increase by replication of the economy, but sometimes to decrease as a consequence of wealth redistribution.We thank an anonymous referee for his insightful comments