The intra-day performance of market timing strategies and trading systems based on Japanese candlesticks

Abstract

We develop market timing strategies and trading systems to test the intra-day predictive power of Japanese candlesticks at the 5-minute interval on the 30 constituents of the DJIA index. Around a third of the candlestick rules outperform the buy-and-hold strategy at the conservative Bonferroni level. After adjusting for trading costs, however, just a few rules remain profitable. When we correct for data snooping by applying the SSPA test on double-or-out market timing strategies, no single candlestick rule beats the buy-and-hold strategy after transaction costs. We also design fully automated trading systems by combining the best-performing candlestick rules. No evidence of out-performance is found after transaction costs. Although Japanese candlesticks can somewhat predict intra-day returns on large US caps, we show that such predictive power is too limited for active portfolio management to outperform the buy-and-hold strategy when luck, risk, and trading costs are correctly measured.     

Information Asymmetries and Security Market Design: An Empirical Study of the Secondary Market for U.S. Government Securities

This paper examines the empirical implications of an information asymmetry between primary and secondary dealers in the U.S. Government Securities market. This asymmetry arises because primary dealers are permitted to trade through all brokers operating in the marketplace while secondary dealers are restricted to trade through only a subset of brokers. Brokers distribute valuable information over video screens to their trading clients including dealers' up-to-date bid-ask spreads and recent transaction prices. As such, all brokers' video screen information is available to primary dealers, while only a subset of brokers' information is available to secondary dealers. Empirical analyses detect the resulting information asymmetry.     

Trading costs and price discovery

The price discovery roles of a set of related markets or securities have been investigated in many different settings where trading costs effect is often commingled with other trading arrangement factors. In Hong Kong, regular futures and mini futures contracts as well as their underlying spot asset are all traded on a same electronic trading platform. The trading arrangements thus provide us with a unique setting where we can isolate the impacts of transaction costs on price discovery. Using Hasbrouck’s (J Finance 50:1175–1199, 1995) information share approach, it is found that in Hong Kong, the regular futures contracts market plays a dominant role in price discovery while the mini futures and cash index markets play minor roles. The results in this paper provide an unequivocal support to the trading costs hypothesis.     

Discount rate changes,stock market returns,volatility, and trading volume: Evidence from intraday data and implications for market efficiency

We examine the effect of discount rate changes on stock market returns, volatility, and trading volume using intraday data. Equity returns generally respond negatively and significantly to the unexpected announcements; however, the effect of expected changes on equity returns is insignificant. Furthermore, our results indicate that equity prices respond to announcements within the trading period/hour after the information release. An indication of a return reversal is too small to cover the full transaction costs. Unexpected discount rate changes also contribute to higher market volatility although the volatility is short-lived. Similarly, unexpected changes in discount rates induce larger trading volume while expected changes do not. Abnormal trading volume occurs only in period t. Our results also support the notion that unexpected changes in the discount rates impact market returns irrespective of the Federal Reserve operating procedures.     

Intraday patterns in London listed Exchange Traded Funds

In this paper we examine the intraday trading patterns of Exchange Traded Funds (ETFs) listed on the London Stock Exchange. ETFs have been shown to be characterised by much lower bid–ask spread costs and by lower levels of information asymmetry than individual securities. One possible explanation for intraday trading patterns is that concentration of trading arises at the start of the trading day because informed traders have private information that quickly diminishes in value as trading progresses. Since ETFs have lower trading costs and lower levels of information asymmetry we would expect these securities to display less pronounced intraday patterns than individual securities. We fail to find that ETFs are characterised by concentrated trading bouts during the day and therefore find support for the argument that information asymmetry is the cause of intraday volume patterns in stock markets. We find that ETF bid–ask spreads and volatility are elevated at the open but not at the close. This lends support to the “accumulation of information” explanation that sees high spreads and volatility at the open as a consequence of information accumulating during a market closure and impacting on the market when it next opens.     

How efficiency shapes market impact

We develop a theory for the market impact of large trading orders, which we call metaorders because they are typically split into small pieces and executed incrementally. Market impact is empirically observed to be a concave function of metaorder size, i.e. the impact per share of large metaorders is smaller than that of small metaorders. We formulate a stylized model of an algorithmic execution service and derive a fair pricing condition, which says that the average transaction price of the metaorder is equal to the price after trading is completed. We show that at equilibrium the distribution of trading volume adjusts to reflect information, and dictates the shape of the impact function. The resulting theory makes empirically testable predictions for the functional form of both the temporary and permanent components of market impact. Based on the commonly observed asymptotic distribution for the volume of large trades, it says that market impact should increase asymptotically roughly as the square root of metaorder size, with average permanent impact relaxing to about two-thirds of peak impact.     

Periodic Information Asymmetry and Intraday Market Behaviour: An Empirical Analysis

The model of Foster-Viswanathan (1990, FV) predicts that information heterogeneity among market participants generates patterns in volume, trading costs and volatility. In the Italian Treasury bond market, periodic information asymmetry is related to the arrival of block orders from international investors, which cluster soon after the opening of the market and, respectively, of the US market. Our evidence is that volume is lower and trading costs are higher after the two openings, consistent with FV. We find only weak evidence that volatility behaves as implied by the model.     

Asymmetric Volume‐Return Relation and Concentrated Trading in LIFFE Futures

This study demonstrates that intraday volume and return on LIFFE interest rate and currency futures exhibit an asymmetric volume‐return relationship characterised by significantly larger volume associated with negative returns than with non‐negative returns. This finding is unlike the stylised asymmetric relation often observed in equity markets, where the volume on price rise is larger than the volume on price decline. The asymmetric relationship in LIFFE futures is also found to be dynamic as the direction of asymmetry can reverse during the day. It has been argued in the past that a costly short sale restriction that requires a higher transaction cost on a short position than on a long position is responsible for the asymmetric effect in equity markets. Since such a restriction is absent in futures markets, they should not exhibit any asymmetric volume behaviour. Based on the results of this research, the costly short sale hypothesis is rejected. An alternative explanation of the asymmetric relation observed in futures is presented based on recent information models that take into consideration asymmetrically‐informed traders, their dispersion of beliefs, quality and quantity of the information signal, and how the traders process it. The paper also confirms a strong U‐shape trading pattern in 15‐minute volume, but no such pattern is identified in intraday returns.     

Multimarket trading and liquidity: a transaction data analysis of Canada–US interlistings

We use transaction data for Toronto Stock Exchange (TSE) listed stocks to examine the impact on trading costs of the decision to interlist on a US exchange. We measure trading costs using both ‘posted’ bid-ask spreads and ‘effective’ bid-ask spreads that measure actual transaction prices relative to standing bid-ask quotes. After controlling for price level, trade size and trading volume effects, we find that overall posted and effective spreads in the domestic (TSE) market decrease subsequent to the interlisting. However, the decrease in trading costs is concentrated in those TSE stocks that experience a significant shift of total trading volume (TSE and US) to the US exchange after listing. We interpret this result in the context of theories of multimarket trading as a competitive response by TSE market makers to the additional presence of US market makers.     

AUDITOR CHANGE ANNOUNCEMENTS AND DISPERSION OF INVESTOR EXPECTATIONS

The effect of auditor change announcements on the dispersion of investor expectations is investigated by using two approaches. First, the consensus effect (Holthausen and Verrecchia, 1990) is measured by examining unanticipated trading volume change. We show that auditor change announcements provide information to the market, and that the consensus effect dominates the informedness effect. Second, the reduction in information asymmetry (Glosten and Milgrom, 1985) due to auditor change announcements is demonstrated by a reduction in proportional bid-ask spread, which is not driven by increased trading volume. Thus, auditor change announcements reduce dispersion of investor beliefs in that they are both information asymmetry-reducing and consensus-increasing. Finally, we show that the type of auditor change (Big-Eight to Non-Big-Eight, Non-Big-Eight to Big-Eight, or Within-Class) has no impact on the dispersion-reducing effect of auditor change announcements.     

Does Anticipated Information Impose a Cost on Risk‐Averse Investors? A Test of the Hirshleifer Effect

This paper theoretically and empirically investigates how the risk of future adverse price changes created by the anticipated arrival of information influences risk‐averse investors’ trading decisions in institutionally imperfect capital markets. Specifically, I examine how the selling activity of individual investors immediately following an earnings announcement is influenced by the tradeoff between risk‐sharing benefits of immediate trade and explicit transaction costs imposed on such trades. Consistent with my theoretically derived predictions, I find that investors’ current trading decisions are less sensitive to the incremental transaction costs created by short‐term capital gains taxes on trading profits, as both the duration and intensity of the risk of future adverse price changes increase. This evidence is consistent with an incremental cost to investors that results from the revelation of precise information, which is commonly referred to as the Hirshleifer Effect.     

On the hidden side of liquidity

This article deals with the informativeness of iceberg orders, also known as hidden limit orders (HLOs). Namely, we analyze how the market reacts when the presence of hidden volume in the limit order book is revealed by the trading process. We use high-frequency book and transaction data from the Spanish Stock Exchange, including a large sample of executed HLOs. We show that just when hidden volume is detected, traders on the opposite side of the market become more aggressive, exploiting the opportunity to consume more than expected at the best quotes. However, neither illiquidity nor volatility increases in the short term. Furthermore, the detection of hidden volume has no relevant price impact. Overall, our results suggest that market participants do not attribute any relevant information content to the hidden side of liquidity.     

Empirical investigation of stock index futures market efficiency: the case of the Athens Derivatives Exchange

Pricing and trading practices in the Athens Derivatives Exchange, a newly established derivatives market, result in significant futures arbitrage profit opportunities for low-cost traders. We find that a large part of the mispricing is due to transaction costs, but additional factors, such as anticipated volatility and time to maturity, also contribute. Ex ante tests reveal significant arbitrage opportunities that could have been exploited up to 30 min after they had been identified. All different tests employed indicate that the derivatives market was inefficient during its early trading history because arbitrage opportunities persisted even after other market impact costs were taken into consideration.     

A comparison of transaction costs on Xetra and on Nasdaq

Abstract

In today's financial world, providing high quality of order execution at low transaction costs is vitally important to the competitiveness of trading platforms; thus the stock market's microstructure has become a subject of fierce debate and models for computing transaction costs have been needed for quite a while. Capital market synergetics is appropriate to investigate the market microstructure's effectiveness and is implemented in the computer program KapSyn.

In this paper we compare transaction costs for small, medium-size and block-size orders on each exchange, examining different market scenarios. By investigating the peculiarities of Xetra and of Nasdaq we point out their comparative advantages: calculation results clearly show the high operating efficiency of Nasdaq's small-order execution system and Xetra's favourable execution of medium-size and block-size orders. Investors' trading decisions may benefit from taking these results into account. For policy makers and academics these findings contribute to the debate about the optimal design of a market microstructure by highlighting the areas of high performance.     

Transaction Volume and Price Dispersion in the Presale and Spot Real Estate Markets

Noise trading has been intensively studied in finance, but rarely in real estate. Theories of price dispersion have also been well established in retailing research, but less so in real estate. This paper is the first attempt to study the effect of noise trading on price dispersion in the real estate spot and presale (forward) markets. Quality-controlled price dispersion data series are estimated using a sample of transaction data in the housing presale and spot markets in Hong Kong. Our results show that transaction volume has a negative and significant effect on price dispersion in the spot market, but a positive and significant effect in the presale market. These support our conjecture that there are more noise traders in the presale market due to lower transaction costs. The volume effects also provide support for the use of a volume weighted least squares model when constructing a repeat sales index.     

Information transmission and causality in the Italian Treasury bond market

We examine causality and efficiency in the Italian T-bond market, where cash trades take place on the domestic Mercato Telematico dei Titoli di Stato, while futures trading is based on the London International Financial Futures Exchange. We find evidence that causality in prices runs in both directions, and that the cash lead is almost comparable in size and extension to the futures lead. We then try to assess whether the cash market is weak-form efficient with respect to LIFFE prices. Using a simple trading rule with a variety of time and price filters, we conclude that the observed lead cannot be exploited to make a profit after transaction costs.     

Trading volume with private valuation: evidence from the ex-dividend day

We test a theory of the interaction between investors' heterogeneity,risk, transaction costs, and trading volume. We take advantageof the specific nature of trading motives around the distributionof cash dividends, namely the costly trading of tax shields.Consistent with the theory, we show that when trades occur becauseof differential valuation of cash flows, an increase in riskor transaction costs reduces volume. We also show that the nonsystematicrisk plays a significant role in determining the volume of trade.Finally, we demonstrate that trading volume is positively relatedto the degree of heterogeneity and the incentives of the variousgroups to engage in trading.     

Deep hedging

We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, liquidity constraints or risk limits using modern deep reinforcement machine learning methods. We discuss how standard reinforcement learning methods can be applied to non-linear reward structures, i.e. in our case convex risk measures. As a general contribution to the use of deep learning for stochastic processes, we also show in Section 4 that the set of constrained trading strategies used by our algorithm is large enough to ε-approximate any optimal solution. Our algorithm can be implemented efficiently even in high-dimensional situations using modern machine learning tools. Its structure does not depend on specific market dynamics, and generalizes across hedging instruments including the use of liquid derivatives. Its computational performance is largely invariant in the size of the portfolio as it depends mainly on the number of hedging instruments available. We illustrate our approach by an experiment on the S&P500 index and by showing the effect on hedging under transaction costs in a synthetic market driven by the Heston model, where we outperform the standard ‘complete-market’ solution.     

Trading Volume, Information Asymmetry, and Timing Information

This paper investigates trading volume before scheduled and unscheduled corporate announcements to explore how traders respond to private information. I show that cumulative trading volume decreases inversely to information asymmetry prior to scheduled announcements, while the opposite relation holds for volume after the announcement. In contrast, trading volume before unscheduled announcements increases dramatically and shows little relation to proxies for information asymmetry. I investigate the behavior of market makers and find that they act appropriately by increasing price sensitivity before all announcements, implying that they extract timing information from their order books.     

A simulation analysis of the microstructure of an order driven financial market with multiple securities and portfolio choices

In this paper we propose an artificial market where multiple risky assets are exchanged. Agents are constrained by the availability of resources and trade to adjust their portfolio according to an exogenously given target portfolio. We model the trading mechanism as a continuous auction order-driven market. Agents are heterogeneous in terms of desired target portfolio allocations, but they are homogeneous in terms of trading strategies. We investigate the role played by the trading mechanism in affecting the dynamics of prices, trading volume and volatility. We show that the institutional setting of a double auction market is sufficient to generate a non-normal distribution of price changes and temporal patterns that resemble those observed in real markets. Moreover, we highlight the role played by the interaction between individual wealth constraints and the market frictions associated with a double auction system to determine the negative asymmetry of the stock returns distribution.