The use of technical analysis by financial market professionals is not well understood. This paper thus analyzes survey evidence from 692 fund managers in five countries, the vast majority of whom rely on technical analysis. At a forecasting horizon of weeks, technical analysis is the most important form of analysis and up to this horizon it is thus more important than fundamental analysis. Technicians are as experienced, as educated, as successful in their career and largely just as overconfident in decision-making as others. However, technical analysis is somewhat more popular in smaller asset management firms. What we find most significant is the relation of technical analysis with the view that prices are heavily determined by psychological influences. Consequently, technicians apply trend-following behavior.

Bond excess returns can be predicted by macro factors, however, large parts remain still unexplained. We apply a novel term structure model to decompose bond excess returns into expected excess returns (risk premia) and the innovation part. In order to explore these risk premia and innovations, we complement macro variables by financial condition variables as possible determinants of bond excess returns. We find that the expected part of bond excess returns is driven by macro factors, whereas innovations seem to be mainly influenced by financial conditions, before and after the financial crisis. Thus, financial conditions, such as financial stress, deserve attention when analyzing bond excess returns.

This paper examines the relative information shares of the Bund, i.e. the 10-year Euro bond future contract on German sovereign debt, versus two futures with shorter maturity. We find that the Bund is most important but does not dominate price discovery. The other contracts also have relevant – and at many days even higher – information shares. In examining determinants of information shares, we add order flow measures to market state variables and macroeconomic news. More order flow in a contract consistently increases this contract’s information share.

Evidence on the effectiveness of foreign exchange (FX) interventions is either limited to short horizons or hampered by debatable identification. We address these limitations by identifying a structural vector autoregressive model for the daily frequency with an external instrument. Generally we find, for freely floating currencies, that FX intervention shocks significantly affect exchange rates and that this impact persists for months. The signaling channel dominates the portfolio channel. Moreover, interest rates tend to fall in response to sales of the domestic currency, whereas stock prices of large (exporting) firms increase after devaluation of the domestic currency.

Technical analysis involves the prediction of asset price movements from inductive analysis of past movements. We establish a number of stylized facts, including that technical analysis is widespread in the foreign exchange market and that it may be profitable. We then analyze four arguments that have been put forward to explain this: that the market may not be fully rational; that technical analysis may exploit the influence of official interventions; that it may be an efficient form of information processing; and that it may inform on nonfundamental influences. While each may have some validity, the latter is the most plausible. As for the foreign exchange, it is almost as romantic as young love, and quite as resistant to formulae.

Due to opaque information and weak enforcement in emerging loan markets, the need for collateral is high, whereas borrowers lack adequate assets to pledge as collateral. How is this puzzle solved? We find for a representative sample from Northeast Thailand that indeed most loans do not include any tangible assets as collateral. Instead, lenders enforce collateral-free loans through third-party guarantees and relationship lending, but also through modifying loan terms, such as reducing loan size. Guarantees are the relatively most important substitute, they reduce collateral requirements independently of relationship lending and they are more often used by formal financial institutions.

This paper examines the role and determinants of collateral in emerging markets compared to mature ones. Analyzing a data set of 560 credit files of Thai commercial banks, we find that both the incidence and degree of collateralization are higher there than in developed markets. Thai banks use collateral primarily to reduce the higher credit risks of small and relatively young firms. Long credit relationships do not reduce collateral requirements by lowering information asymmetry. Market imperfections result from housebanks demanding higher collateral than non-housebanks, suggesting a lock-in effect for their borrowers, and from larger banks realizing higher collateral claims.

This paper provides evidence that informed traders dominate the response of limit-order submissions to shocks in a pure limit-order market. In the market we study, informed traders are highly sensitive to spreads, volatility, momentum and depth. By contrast, uninformed traders are relatively insensitive to all these market conditions. The dominance of the informed over limit-order submissions is magnified by contrasts between them and the uninformed in the use of aggressively-priced limit orders.