We explore online inductive transfer learning, with a feature representation from radial basis function network formed of Gaussian mixture model hidden processing units to direct, recurrent reinforcement learning agent. This agent is put work in an experiment, trading the major spot market currency pairs, where we accurately account for transaction and funding costs. These sources profit loss, ...

We document that cross-sectional FX correlation dispersion is countercyclical, as FX pairs with high average correlation become more correlated in bad times whereas pairs with low average correlation become less correlated. We show that currencies that perform badly (well) during periods of high crosssectional disparity in conditional FX correlation yield high (low) average excess returns, sugg...

This research investigates the ability of genetic programming (GP) to build profitable trading strategies for the Foreign Exchange Market (FX) of three major currency pairs (EURUSD, USDCHF and EURCHF) using one hour prices from 2008 to 2011. We recognize that such environments are likely to be non-stationary. Thus, we do not require a single training partition to capture all likely future behav...

Abstract Using monthly headline inflation data covering 184 countries for the period between January 1971 and December 2020, this paper investigates role of standard gravity variables on convergence across country pairs. The analysis by unit root tests is based ten-year rolling windows to control potential structural changes over time, whereas corresponding results are connected in preceding ye...

specialist microfinance institutions (MFIs). The Central Bank of Sri Lanka (CBSL) has traditionally pursued an active "developmental" role in the microfinance sector, although this has been changing. It should further reduce its developmental activities by diluting its ownership of regional development banks and taking a less hands-on role in project implementation. Conversely, it would be appr...

This work studies the information content of trades in world’s largest over-the-counter (OTC) market, foreign exchange (FX) market. It analyzes a novel, comprehensive order flow data set, distinguishing among different groups market participants and covering large cross-section currency pairs. We find compelling evidence heterogeneous superior across agents, time, pairs, consistent with asymmet...

We develop the optimal trading strategy for our broker who has non-zero inventory in three currency pairs with different level of liquidity and would like to o ff-load all inventories with a given time schedule while accepting exogenous clients orders. The mid-exchange rate satisfies constraint to exclude the triangle arbitrage. Our broker is risk-neutral, inventory averse and would like to max...

Abstract This study examines the portfolio diversification benefits of alternative currency trading in Bitcoin and foreign exchange markets. The following methods are applied for analysis: spillover index method Diebold Yilmaz (Int J Forecast 28(1): 57–66, 2012. 10.1016/j.ijforecast.2011.02.006 ), asymmetry measures Barunik et al. (J Int Money Finance 77: 39–56, 2017. 10.1016/j.jimonfin.2017.06...

The increasing volatility in pricing and growing potential for profit in digital currency have made predicting the price of cryptocurrency a very attractive research topic. Several studies have already been conducted using various machine-learning models to predict crypto currency prices. This study presented in this paper applied a classic Autoregressive Integrated Moving Average(ARIMA) model ...