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on Market Microstructure |
| By: | Nicholas Mulligan; Daan Steenkamp (Reserve Bank of New Zealand) |
| Abstract: | There is a large literature focused on exchange rate forecasting. A common finding is that it is difficult to systematically predict exchange rate movements, consistent with the results of Meese and Rogoff (1983), who showed that it is difficult to beat a random walk forecast. This note heads down the same well-worn path, but assesses the usefulness of the Commitments of Traders (COT) positioning data for understanding and predicting exchange rate movements. COT data has been used extensively in research assessing the impact of speculation in commodity markets, but there has been comparatively little recent research into the usefulness of this data for thinking about foreign exchange market developments. COT data also provides classifications of trading entities that allow the trading behaviour of different groups of traders (such as hedgers and speculators), and their respective market impact, to be examined. This note focuses on the positioning of speculative traders who are thought to express their beliefs of future currency movements through futures positions. The COT data is available at weekly frequency and aggregates holdings of futures in key US markets. The lag between the collection of the COT data and its publication may in fact limit its information content. For example, assuming markets are informationally efficient, new information is expected to be quickly incorporated into spot exchange rates and futures positions at the same time. Therefore, the data cannot provide insight as to whether exchange rates change contemporaneously as futures positions are opened or closed (in real-time). The key question examined in this note is what the information content of COT positioning data is for major currencies, and at what horizon is positioning data best for forecasting exchange rate changes. As has been found by earlier studies, our results suggest that futures positioning data can help with interpretation of historical exchange rate changes, although its use as a predictor of exchange rates is limited. However, higher frequency positioning data, such as hourly or daily data, may in fact have predictive power. |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:nzb:nzbans:2018/03&r=mst |
| By: | David-Jan Jansen |
| Abstract: | This paper studies the intraday spillovers of the 2010 U.S. Flash Crash to international equity markets. We document a substantial and almost immediate echo of the crash in Latin America. Using data for 148 firms trading in Argentina, Brazil, Chile, or Mexico, we estimate price declines of up to 10% within minutes after the U.S. crash. Estimates for two different factor models indicate that this echo followed from normal interdependence rather than financial contagion. There is no evidence of contagion for firms with strong links to the U.S. economy. |
| Keywords: | flash crash; stock returns; Latin America; spillovers; contagion |
| JEL: | G1 N2 |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:dnb:dnbwpp:589&r=mst |
| By: | Carey Caginalp; Gunduz Caginalp |
| Abstract: | Cryptocurrencies are examined through the asset flow equations and experimental asset markets. Since tangible value of a typical cryptocurrency is non-existent, the theory suggests that price will gravitate toward liquidity value, i.e., the total amount of cash available for purchase of the asset divided by the number of units. Thus it is unlikely that cryptocurrencies in their current form will be stable in the absence of a mechanism of a link to value. |
| Date: | 2018–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1802.09959&r=mst |
| By: | Febi Wulandari; Dorothea Schäfer; Andreas Strephan; Chen Sun |
| Abstract: | This study analyses how liquidity risk affects bonds’ yield spreads after controlling for credit risk, bond-specific characteristics and macroeconomic variables. Using two liquidity estimates, LOT liquidity and the bid-ask spread, we find that, in particular, the LOT liquidity measure has explanatory power for the yield spread of green bonds. Overall, however, the impact of LOT decreases over time, implying that, nowadays liquidity risk is negligible for green bonds. |
| Keywords: | Green Bond, Liquidity Risk, Yield Spread, Sustainable Investment, Fixed Income Security, Financial Innovation |
| JEL: | G12 G32 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:diw:diwwpp:dp1728&r=mst |
| By: | Michail Anthropelos; Constantinos Kardaras |
| Abstract: | We consider a market of financial securities with restricted participation, in which traders may not have access to the trade of all securities. The market is assumed thin: traders may influence the market and strategically trade against their price impacts. We prove existence and uniqueness of the equilibrium even when traders are heterogeneous with respect to their beliefs and risk tolerance. An efficient algorithm is provided to numerically obtain the equilibrium prices and allocations given market's inputs. |
| Date: | 2018–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1802.09954&r=mst |