From experimental evaluation, we reasonably infer that online trading algorithms can beat the market. We consider the scenario of trading in financial market and present an extensive experimental study to answer the question “Can online trading algorithms beat the market?”. We evaluate the selected set of online trading algorithms on DAX30 and measure the performance against buy-and-hold strate...

This paper addresses the existence of competitive equilibrium in the variant of the Assignment Game where budget-constrained agents are endowed with one good, that can be sold to buy another good. We define the Money Scarcity (MS) condition and its Strong (SMS) and Weak (WMS) versions. The WMS condition ensures the existence of an equilibrium in cases where Quinzii’s indispensability of money a...

We use weekly survey data on short-term and medium-term sentiment of German investors in order to study the causal relationship between investors' mood and subsequent stock price changes. In contrast to extant literature for other countries, a tri-variate vector autoregression for short-run sentiment, medium-run sentiment and stock index returns allows to reject exogeneity of returns. Depending...

We propose to train trading systems by optimizing financial objective functions via reinforcement learning. The performance functions that we consider as value functions are profit or wealth, the Sharpe ratio and our recently proposed differential Sharpe ratio for online learning. In Moody & Wu (1997), we presented empirical results in controlled experiments that demonstrated the advantages of ...

This paper investigates the impact of price limits on the Brazilian futures markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the São Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. The r...

This paper examines the predictability of real estate asset returns using a number of time series techniques. A vector autoregressive model, which incorporates financial spreads, is able to improve upon the out of sample forecasting performance of univariate time series models at a short forecasting horizon. However, as the forecasting horizon increases, the explanatory power of such models is ...

In this paper we propose a new analytical charge injection model. This model is completely general (i.e., it can be applied to any load condition) and models all regions of operation. The validity of the model has been verified via measurements from a fabricated design in a 0.5 CMOS process. Measurement results match extremely well with our model. The model is completely analytical and can be a...

Growing evidence is suggesting that postings on online stock forums affect stock prices, and alter investment decisions in capital markets, either because the postings contain new information or they might have predictive power to manipulate stock prices. In this paper, we propose a new intelligent trading support system based on sentiment prediction by combining text-mining techniques, feature...

This project explores the effectiveness of a Small Moving Average (SMA) crossover trading strategy implemented on TradingView website using Pine Script. The study investigates potential profitability by backtesting it historical price data for various financial instruments. also examines impact different parameter values and timeframes performance SMA strategy. findings suggest that can be an e...