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This study investigates a forecasting power of volatility curvatures and risk neutral densities implicit in KOSPI 200 option prices by analyzing minute by minute historical index option intraday trading data from January of 2007 to January of 2011. We begin by estimating implied volatility functions and risk neutral price densities based on non-parametric method every minute and by calculating volatility curvature and skewness premium. We then compare the daily rate of return of the signal following trading strategy that we buy (sell) a stock index when the volatility curvature or skewness premium increases (decreases) with that of an intraday buy-and-hold strategy that we buy a stock index on 9:05AM and sell it on 2:50PM. We found that the rate of return of the signal following trading strategy was significantly higher than that of the intraday buy-and-hold strategy, which implies that the option prices have a strong forecasting power on the direction of stock market. Another finding is that the information contents of option prices disappear after three or four minutes.

This paper aims to demonstrate a dynamic cointegration-based pairs trading strategy, including an optimal look-back window framework in the cryptocurrency market and evaluate its return and risk by applying three different scenarios.

This study uses the Engle-Granger methodology, the Kapetanios-Snell-Shin test and the Johansen test as cointegration tests in different scenarios. This study calibrates the mean-reversion speed of the Ornstein-Uhlenbeck process to obtain the half-life used for the asset selection phase and look-back window estimation.

By considering the main limitations in the market microstructure, the strategy of this paper exceeds the naive buy-and-hold approach in the Bitmex exchange. Another significant finding is that this study implements a numerous collection of cryptocurrency coins to formulate the model’s spread, which improves the risk-adjusted profitability of the pairs trading strategy. Besides, the strategy’s maximum drawdown level is reasonably low, which makes it useful to be deployed. The results also indicate that a class of coins has better potential arbitrage opportunities than others.

This research has some noticeable advantages, making it stand out from similar studies in the cryptocurrency market. First is the accuracy of data in which minute-binned data create the signals in the formation period. Besides, to backtest the strategy during the trading period, this study simulates the trading signals using best bid/ask quotes and market trades. This study exclusively takes the order execution into account when the asset size is already available at its quoted price (with one or more period gaps after signal generation). This action makes the backtesting much more realistic.

The authors test the weak-form efficiency in cryptocurrency markets using the most recent and comprehensive data as of 2021. The authors apply various technical indicators to take a long or short position on 99 cryptocurrencies and compare the 10-day returns based on the technical trading strategies to the simple buy-and-hold returns. The authors find that the trading strategies based on single indicators or the combination of two indicators do not generate higher returns than buy-and-hold returns among cryptos. These findings suggest that cryptocurrency markets are weak-form efficient in general.

This paper aims to investigate popular technical trading rules (TTRs) applied to the FTSE Turkish all-cap and small-cap indexes from September 23, 2003 to August 9, 2019 to determine rules that produce net excess returns over the Buy-and-Hold strategy (B&H).

Five TTRs, namely, simple moving average, relative strength index, moving average convergence divergence, momentum, and rate of change, are applied, singly (one indicator) and in combination (two indicators) for multiple time periods.

For the small-cap index, some TTRs – including the famous Golden Cross, when the 50-day moving average rises above 200-day moving average – produced net annual excess returns (NAERs) over the B&H strategy, for the entire period and each sub-period, after accounting for risk and transaction costs. Results were mixed for the large-cap index. The results support Cakici and Topyan (2013).

This study investigates several indicators, but future studies should examine others, especially based on volume and price.

Investors in the FTSE Turkish small-cap index may use some trading rules to earn NAERs over the B&H strategy.

This research is important because it addresses a gap in the research by examining numerous TTRs in the Turkish stock market. Studies of TTRs in Turkey are scarce.

The purpose of this paper is to explore trading strategies that exploit investors’ anchoring bias.

This paper forms portfolios based on nearness ratio and other anomaly variables under one- and two-way sorts. The portfolio return series are then regressed on Fama and French three factors to extract abnormal returns.

First is to use anchoring as a technical signal. A strategy that trades against anchoring buys stocks with prices near their 52-week high and sells stocks with prices far below their 52-week high. Based on deciles, the strategy generates a significant value-weighted monthly α of 1.13 percent, after accounting for the market, size, and value factors. Further, the strategy is profitable among both large and small stocks; the trading profit is higher among younger firms and more volatile stocks, but is similar between subsamples formed on number of analysts, level of institutional ownership, and number of institutional owners. The strategy is more profitable following periods of high investor sentiment. Second is to combine anchoring with known anomalies. For a broad set of 26 anomalies, a trading strategy that combines anchoring with the anomalies increases the value-weighted monthly α from an average of 0.61 percent to an average of 1.38 percent. While part of the profits can be attributed to momentum, momentum itself does not explain all the profits.

This paper presents empirical evidence that anchoring bias explains the profitability of a broad set of anomalies and describes practical trading strategies that exploit the anchoring bias.

The purpose of this paper is to examine whether abnormal returns to a fundamental signal (FS) strategy disappear after the publication of Abarbanell and Bushee (1998).

Using data on NYSE/AMEX firms from 1974 to 2012, this research estimates annual Fama and MacBeth (1973) cross-sectional regression of risk-adjusted buy-and-hold returns on the FSs after controlling for contemporaneous earnings changes and a proxy for market risk.

This paper finds that predictable hedge returns to the FSs substantially decrease and become statistically insignificant after the Abarbanell and Bushee’s publication date. This research also finds that the FSs have not lost their importance to equity valuation process; value relevance of the FSs has not diminished, and the FSs have retained their predictive ability over time. The evidence on changing information and trading environments appears to contribute to the disappearing abnormal returns to a FS strategy.

This paper adds to the growing body of literature on the persistence of pricing anomalies.

This paper tests two moving average technical trading rules for four Asian markets. Our results indicate that moving average rules do indeed have predictive power and can discern recurring price patterns for profitable trading. Moreover, our results support the hypothesis that technical trading rules can outperform the buy‐and‐hold strategy. Break‐even one‐way trading costs are estimated to be high for all four markets. To confirm the test outcome, robust tests based on bootstrap and the related t‐tests among the markets are also carried out. We conclude from the statistical results that moving average rules are valid and indeed have predictive power. It is implied that the trading rules may be used to design a trading strategy that will beat the buy‐and‐hold strategy in the Hong Kong, Singapore, South Korea, and Taiwan markets. The contribution of the current study is that this is the first validation test of trading rules using four markets at a similar development stage and culture tradition; and in the tests, we use most current and longer periods than the periods used in previous literature. Our robust tests are unique and considered distribution‐free.

This study aims to investigate Malaysian stock market efficiency from the view of Sharīʿah-compliant and conventional stocks based on the effectiveness of technical trading strategies.

This study uses unconventional trading strategies that mix buy recommendations of Bursa Malaysia analysts with sell signals generated from 10 selected technical trading strategies (simple moving average, moving average envelopes, Bollinger Bands, momentum, commodity channel index, relative strength index, stochastic, Williams percentage range, moving average convergence divergence oscillator and shooting star) that are detected using ChartNexus. The period from 1 January 2013 until 31 December 2015 produces a total sample consisting of 1,265 buy recommendations of 125 Sharīʿah-compliant stocks and 400 buy recommendations of conventional stocks. The study period is extended until 31 March 2016 to provide an ample time for detecting the sell signal especially for buy recommendations that are released towards the end of 2015.

The resulting Jensen’s alpha show 8 out of 10 strategies are effective in generating abnormal returns in Sharīʿah-compliant samples while only 3 out of 10 strategies are effective in conventional samples. Prominent effectiveness of technical trading strategies in Sharīʿah-compliant stocks implies clear inefficiency in that stock market segment as opposed to those of the conventional stocks.

The results based on unconventional trading strategies provide new insights of Malaysian stock market efficiency especially in Sharīʿah-compliant and conventional stocks. The paper provides more robust findings on market efficiency as firms’ equity level data were focussed together with analysts’ buy recommendations from Bursa Malaysia.

The purpose of this paper is to examine the predictability of the US‐based international mutual fund returns by investigating 2,479 daily observations for all categories of international equity, bond and hybrid mutual funds. Further, trading strategies are proposed and tested under different scenario including a proposed regulation by the Security and Exchange Commission (SEC).

The sample is split and the initial sub sample is used to investigate return patterns of international funds and to develop trading rules based on the predictable return patterns. Trading rules are then tested on the holdout sample.

Empirical results demonstrate statistically significant predictabilities. Various trading strategies show that the returns of both load and no‐load funds are economically significant beating a buy‐and‐hold strategy. Empirical findings are consistent across the fund categories irrespective of sizes and styles. The tested strategies are profitable even with various limits on frequency of trading, minimum holding periods and even under a recent SEC's proposed regulation. Further, possible contracting and regulatory changes are proposed to improve the efficiency in the mutual fund industry.

The results confirm previous findings of statistically and economically significant regularities from trading strategies that involve following the US markets. A test of SEC's proposed regulation documents that short‐term investors may benefit from active trading strategy even if the SEC's rule is implemented.

The study considers time-varying risk premium in investigating the capability of technical analysis (TA) to predict and outperform a buy–hold strategy in Bitcoin exchange rate returns.

The study tests the technical trading rule of fixed moving average (FMA) on daily actual and equilibrium returns of Bitcoin exchange rates. The equilibrium returns are computed using dynamic CAPM in conjunction with a VAR-MGARCH (1, 1) system. The empirical evaluation of the study uses a case study of four Bitcoin exchange rates (BTC/AUD, BTC/EUR, BTC/JPY and BTC/ZAR) for the period 19 June 2010 to 30 October 2020.

The findings are consistent with related studies in conventional foreign exchange markets that find TA to be profitable, especially in emerging markets. Nevertheless, the consideration of risk premium has the effect of reducing the abnormal returns. Also, further robust tests reveal that Bitcoin returns possess a momentum effect which prompts further study in efficient market hypothesis research.

The empirical findings of this study should benefit portfolio managers and active investors on the strength of TA to predict returns in a speculative market like the Bitcoin exchange rate market.

The study takes cognisance that cryptocurrency trading is speculative in nature which renders it a good candidate for TA methods. While there are studies that have explored the value of TA in Bitcoin exchange rates, these studies fail to incorporate the effects of time-varying risk premiums, the strength and focus of the current paper.