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.     

Return enhancement trading strategies for size based portfolios

Recent theoretical work suggests that definitions of market efficiency that allow for the possibility of time-varying risk-premia will generally lead to return sign predictability. Consistent with this theory, we show that a logit model based on the lagged value of the market risk premium is useful for successfully predicting the return sign for CRSP small decile portfolio returns, but not large ones. We additionally employ this model in market timing simulations of micro-cap mutual funds in which investment can actually be made. The results indicate that a market-timing strategy based on our return-sign forecasting model outperforms a buy-and-hold strategy for 13 of 14 micro-cap funds studied. On average, the buy-and-hold strategy produces an average compound return of 11.98% per annum versus an average of 16.60% for the market-timing strategy. Nevertheless, trading restrictions make the return-sign forecasting model more practical to employ by the micro-cap fund portfolio manager rather than the individual fund investor.

Disagreement and equilibrium option trading volume

Using a complete market equilibrium model, we present results concerning the effect disagreement has on equilibrium option trading volume and positioning. We find that if agents agree on volatility, total option volume is independent of wealth distribution and average optimism. We also find option volume increasing in drift disagreement and decreasing in risk aversion and volatility. Pessimists are shown to write most options. With volatility disagreement, the results are less clear; however, we show agents with high volatility beliefs write deep out of the money options and buy close to the money options. Numerical comparative statics are also performed. This revised version was published online in June 2006 with corrections to the Cover Date.     

Detecting abnormal trading activities in option markets

We develop an econometric method to detect “abnormal trades” in option markets, i.e., trades which are not driven by liquidity motives. Abnormal trades are characterized by unusually large increments in open interest, trading volume, and option returns, and are not used for option hedging purposes. We use a multiple hypothesis testing technique to control for false discoveries in abnormal trades. We apply the method to 9.6 million of daily option prices.     

中国外汇交易中心推出人民币对外汇期权交易

2011年4月1日起,我国银行间外汇市场推出人民币对外汇期权交易。该交易在中国外汇交易中心（以下简称“交易中心”）的外汇交易系统挂牌和交易。开市后,银行报价、询价活跃。     

Tail-risk protection trading strategies

Starting from well-known empirical stylized facts of financial time series, we develop dynamic portfolio protection trading strategies based on econometric methods. As a criterion for riskiness, we consider the evolution of the value-at-risk spread from a GARCH model with normal innovations relative to a GARCH model with generalized innovations. These generalized innovations may for example follow a Student t, a generalized hyperbolic, an alpha-stable or a Generalized Pareto distribution (GPD). Our results indicate that the GPD distribution provides the strongest signals for avoiding tail risks. This is not surprising as the GPD distribution arises as a limit of tail behaviour in extreme value theory and therefore is especially suited to deal with tail risks. Out-of-sample backtests on 11 years of DAX futures data, indicate that the dynamic tail-risk protection strategy effectively reduces the tail risk while outperforming traditional portfolio protection strategies. The results are further validated by calculating the statistical significance of the results obtained using bootstrap methods. A number of robustness tests including application to other assets further underline the effectiveness of the strategy. Finally, by empirically testing for second-order stochastic dominance, we find that risk averse investors would be willing to pay a positive premium to move from a static buy-and-hold investment in the DAX future to the tail-risk protection strategy.     

An anatomy of trading strategies

In this article we use a single unifying framework to analyzethe sources of profits to a wide spectrum of return-based tradingstrategies implemented in the literature. We show that lessthan 50% of the 120 strategies implemented in the article yieldstatistically significant profits and, unconditionally, momentumand contrarian strategies are equally likely to be successful.However, when we condition on the return horizon (short, medium,or long) of the strategy, or the time period during which itis implemented, two patterns emerge. A momentum strategy isusually profitable at the medium (3- to 12-months) horizon,while a contrarian strategy nets statistically significant profitsat long horizons, but only during the 1926-1947 subperiod. Moreimportantly, our results show that the cross-sectional variationin the mean returns of individual securities included in thesestrategies play an important role in their profitability. Thecross-sectional variation can potentially account for the profitabilityof momentum strategies and it is also responsible for attenuatingthe profits from price reversals to long-horizon contrarianstrategies.     

Insider employee stock option trading and stock prices

The question of which factors determine corporate bonds pricing is investigated by analysing the spreads of eurobonds issued by major G-10 companies during the 1991–2001 period. Three main results emerge from the analysis. First, bond ratings appear as the most important determinant of yield spreads, with investors’ reliance on rating agencies judgments increasing over time. Second, the primary market efficiency and the expected secondary market liquidity are not relevant explanatory factors of spreads cross-sectional variability. Finally, rating agencies adopt a different, ‘through the cycle’, evaluation criteria of default risk with respect to the forward looking one adopted by bond investors.     

Optimal bond trading and the tax-timing option in Canada

The goal of this paper is to determine whether the tax-timing option effect documented in the U.S. bond market exists outside the U.S. Examining Canadian tax rules suggests that the tax option effect is simpler and less valuable than in the U.S. This view is supported by simulations in the spirit of Constantinides and Ingersoll (1984) as well as by empirical tests conducted on bond triplets following Jordan and Jordan (1991).     

Complete markets,informed trading and equity option introductions

This paper proposes and tests a new hypothesis concerning the price impact of option introductions on the underlying asset. We argue that the leverage properties of options induce a higher level of informed trading in the aggregate market (underlying plus derivative), resulting in excess listing-day price movements in the newly optioned equity. Using an alternative dataset, our results suggest that this may be an explanation for the observed positive than negative excess listing-day returns of US optioned stocks over the past thirty years.     

Cross-market informed trading in the CDS and option markets

This paper analyzes how informed traders balance leverage and liquidity in making cross-market trading decisions. Our findings are three-fold. Using daily data on the actively traded North American CDX Investment Grade and High Yield indexes from 2010 to 2017, first, we find robust evidence that, when the credit default swap (CDS) market is illiquid, informed traders do not hesitate to exploit their information advantage in the option market, and this manifests mainly for negative credit news. Second, we find that informed trading occurs predominantly in the option market for low-rated firms due to high adverse selection risk in the CDS market. Third, there is strong evidence of informed trading taking place in the CDS market for financial firms and we argue that this is due to the interdealer network through which CDS dealers obtain private information about other financial firms and their privileged position as market makers to be able to disguise their informed trades as ordinary market-making activities. Finally, we propose re-thinking market efficiency and how to advance it in a direction which does not privilege a small circle of financiers or create monopoly while keeping the markets liquid and tranquil at all times.     

The efficacy of regulatory intervention: Evidence from the distribution of informed option trading

A substantive body of equity-market academic research documents an extensive range of costs arising from the SEC’s October 2000 adoption of strictures on selective disclosure and insider trading; suggesting an unusual outcome, specifically, an increase in informed trading. We investigate the efficacy of the SEC’s regulations by examining informed trading in an attractive setting for exploiting private information; the options market. Using data on the S&P 1500 industrial firms, our analysis indicates that about 38% of firms exhibited symptoms of informed option trading prior to regulatory intervention. After regulatory intervention, we observe that only 19% of firms show symptoms of informed trading. In additional testing of ADR firms – explicitly exempt from complying with Reg FD, we find no evidence of a change in informed option trading from pre- to post-regulation; suggesting that the SEC’s strictures on US firms led a to a significant reduction in informed option trading. Notably, our proxies for large shareholder and financial analyst access are associated with the largest decreases in informed option trading. In developing a unique measure of informed trading based on option market data, we provide evidence on the efficacy of security regulation in limiting informed trading.     

Estimating the profits from trading strategies

Price improvement is the difference between the execution priceof an order and the quoted bid or ask when the order was submitted.We show that expected price improvement falls off dramaticallyas the size of the order approaches the quoted depth, and becomesnegative for larger orders. This is particularly important forsmall firms because the quoted depths are low. Using quotedspreads and depths and our estimate of expected price improvement,we show that trading strategies that attempt to exploit theweekly predictability of small-firm returns would be swampedby transaction costs.     

The information content of CDS implied volatility and associated trading strategies

Using the theoretical link between put options and credit default swaps (CDS) in a very general setting, we develop a robust measure of CDS implied volatility (CIV) that captures the information content of CDS markets. Specifically, we use the unit recovery claim to bridge CDS and deep out-of-the-money put options of the same firm and then back out CIV via the binomial tree. Our CIV measure strongly co-moves with the option implied volatility (OIV), with a correlation coefficient of 0.8. Based on the standardized difference between CIV and OIV, we construct CDS and option trading strategies. Without taking transaction costs into account, the long–short CDS trading strategy achieves an annualized return of 58.29% and a Sharpe ratio of 2.97, which cannot be explained by non-parametric skewness and volatility risk.     

No arbitrage conditions for simple trading strategies

Strict local martingales may admit arbitrage opportunities with respect to the class of simple trading strategies. (Since there is no possibility of using doubling strategies in this framework, the losses are not assumed to be bounded from below.) We show that for a class of non-negative strict local martingales, the strong Markov property implies the no arbitrage property with respect to the class of simple trading strategies. This result can be seen as a generalization of a similar result on three dimensional Bessel process in Delbaen and Schachermayer (Math Finance 4:343–348, 1994). We also provide no arbitrage conditions for stochastic processes within the class of simple trading strategies with shortsale restriction.     

Dynamic mode decomposition for financial trading strategies

We demonstrate the application of an algorithmic trading strategy based upon the recently developed dynamic mode decomposition on portfolios of financial data. The method is capable of characterizing complex dynamical systems, in this case financial market dynamics, in an equation-free manner by decomposing the state of the system into low-rank terms whose temporal coefficients in time are known. By extracting key temporal coherent structures (portfolios) in its sampling window, it provides a regression to a best fit linear dynamical system, allowing for a predictive assessment of the market dynamics and informing an investment strategy. The data-driven analytics capitalizes on stock market patterns, either real or perceived, to inform buy/sell/hold investment decisions. Critical to the method is an associated learning algorithm that optimizes the sampling and prediction windows of the algorithm by discovering trading hot-spots. The underlying mathematical structure of the algorithms is rooted in methods from nonlinear dynamical systems and shows that the decomposition is an effective mathematical tool for data-driven discovery of market patterns.     

Asymmetric return dynamics and technical trading strategies

We investigate the profitability of technical trading strategies based on an asymmetric reverting property of stock returns. We identify an asymmetry in return dynamics for daily returns on the S&P 500 index. Return dynamics evolve along a positive (negative) unconditional mean after a prior positive (negative) return. The trading strategies based on this asymmetry generate a positive return for buy signals, a negative return for sell signals, and a positive return for the spread between buy and sell signals. Our results imply that the observed asymmetry in return dynamics is the main source of profitability for the implied strategies, thereby corroborating arguments for the usefulness of technical trading strategies.     

Entry, exit and trading profits: A look at the trading strategies of a proprietary trading team

We examine the behavior of a 15 strong proprietary stock trading team and show how consistent intraday trading profits were generated. The team, who worked for a large US direct access trading firm, executed over 96 thousand trades in 3 months in 2000. Profitable intraday trading occurred in an anonymous dealer capacity, on both long and short positions, especially when volume and price volatility were higher. The traders rapidly entered long (short) positions when the number of dealers and size become greater on the bid (offer) side of the spread. Profits were taken early against the trend.