Creating short-term stockmarket trading strategies using artificial neural networks:A case study

Abstract — Developing short-term stockmarket trading systems is a complex process, as there is a great deal of random noise present in the time series data of individual securities. The primary difficulty in training neural networks to identify return expectations is to find variables to help identify the signal present in the data. In this paper, the authors follow the previously published Vanstone and Finnie methodology. They develop a successful neural network, and demonstrate its effectiveness as the core element of a financially viable trading system. Index Terms—stockmarket trading, neural networks, trading system

Does It Pay to Be Informed? Expenditure Efficiency in the US Mutual Fund Industry

The mutual fund industry would like us to believe that fund expenses are justifiable by their extensive management expertise, security analysis and the consequent delivery of returns that exceed the market performance. Management know-how is costly and thus it drives up the expenditure of actively managed mutual funds and potentially lowers their net returns. Nevertheless the fund managers argue that their contributions to the returns fully outweigh their costs and in general their trading strategies add value to the investors. On the other hand many academics hold that such claims are fundamentally misleading and actively managed funds cannot continuously outperform a market index. [excerpt

On the dark side of the market: identifying and analyzing hidden order placements

Trading under limited pre-trade transparency becomes increasingly popular on financial markets. We provide first evidence on traders’ use of (completely) hidden orders which might be placed even inside of the (displayed) bid-ask spread. Employing TotalView-ITCH data on order messages at NASDAQ, we propose a simple method to conduct statistical inference on the location of hidden depth and to test economic hypotheses. Analyzing a wide cross-section of stocks, we show that market conditions reflected by the (visible) bid-ask spread, (visible) depth, recent price movements and trading signals significantly affect the aggressiveness of ’dark’ liquidity supply and thus the ’hidden spread’. Our evidence suggests that traders balance hidden order placements to (i) compete for the provision of (hidden) liquidity and (ii) protect themselves against adverse selection, front-running as well as ’hidden order detection strategies’ used by high-frequency traders. Accordingly, our results show that hidden liquidity locations are predictable given the observable state of the market

High frequency trading and end-of-day price dislocation : [Version 28 Oktober 2013]

We show that the presence of high frequency trading (HFT) has significantly mitigated the frequency and severity of end-of-day price dislocation, counter to recent concerns expressed in the media. The effect of HFT is more pronounced on days when end of day price dislocation is more likely to be the result of market manipulation on days of option expiry dates and end of month. Moreover, the effect of HFT is more pronounced than the role of trading rules, surveillance, enforcement and legal conditions in curtailing the frequency and severity of end-of-day price dislocation. We show our findings are robust to different proxies of the start of HFT by trade size, cancellation of orders, and co-location

Does Partnering Pay Off? - Stock Market Reactions to Inter-Firm Collaboration Announcements in Germany

The dramatic increase in interorganizational partnering in the last two decades raises questions for scholars and managers regarding the value impact of inter-firm collaborations. Using event study methodology, this paper tests whether stock market reactions differ when a collaboration formation or termination is announced. In addition, the study provides an in-depth analysis of potential determinants of stock market reactions to collaboration formation announcements. The sample consists of 1037 announcements in German stock markets from 1997 to 2002. The results show that an unexpected termination announcement decreases firm valuation, and a formation announcement increases firm valuation. Further, certain collaborations are more favorable than others, depending on firm industry, age, size, collaboration constellations, and equity versus non-equity investment in partner firm. The results open avenues for further research on partnering strategies

News, liquidity dynamics and intraday jumps: evidence from the HUF/EUR market

We study intraday jumps on a pure limit order FX market by linking them to news announcements and liquidity shocks. First, we show that jumps are frequent and contribute greatly to the return volatility. Nearly half of the jumps can be linked with scheduled and unscheduled news announcements. Furthermore, we show that jumps are information based, whether they are linked with news announcements or not. Prior to jumps, liquidity does not deviate from its normal level, nor do liquidity shocks offer any predictive power for jump occurrence. Jumps emerge not as a result of unusually low liquidity but rather as a result of an unusually high demand for immediacy concentrated on one side of the book. During and after the jump, a dynamic order placement process emerges: some participants endogenously become liquidity providers and absorb the increased demand for immediacy. We detect an interesting asymmetry and find the liquidity providers to be more reluctant to add liquidity when confronted with a news announcement around the jump. Further evidence shows that participants submit more limit orders relative to market orders after a jump. Consequently, the informational role of order flow becomes less pronounced in the thick order book after the jump

Momentum Equity Strategies: Are Certain Firm-Specific Variables Crucial in Achieving Superior Performance in Short Term Holding Periods?

In this study we analyze the performance of variable-oriented momentum strategies, in order to detect alternatives which offer higher returns, compared to the simple price momentum strategies, for no significantly extra risk, in the very short run. Portfolios are constructed using twenty firm specific variables, of U.S. stocks traded in NYSE, NASDAQ and AMEX for a full six year period starting on March of 2002. We calculate a volatility- reward (VR) ratio for each observation, treated as a performance measure, and we apply Principal Component Analysis (PCA) on their series in order to detect the variables which contribute mostly in enhancing the performance of simple momentum strategies. Our findings suggest that short term investors could significantly benefit from momentum strategies if they take into account past firm specific information, which indirectly indicates a market underreaction to various announcements related to firms' EPS. In particular, top analysts' EPS estimate revisions followed by low P/E and high ROE contribute the most in producing momentum portfolios of superior performance, compared to a simple price momentum strategy. © EuroJournals Publishing, Inc. 2009

The optimal use of return predictability : an empirical study

In this paper we study the economic value and statistical significance of asset return predictability, based on a wide range of commonly used predictive variables. We assess the performance of dynamic, unconditionally efficient strategies, first studied by Hansen and Richard (1987) and Ferson and Siegel (2001), using a test that has both an intuitive economic interpretation and known statistical properties. We find that using the lagged term spread, credit spread, and inflation significantly improves the risk-return trade-off. Our strategies consistently outperform efficient buy-and-hold strategies, both in and out of sample, and they also incur lower transactions costs than traditional conditionally efficient strategies