Market Timing Strategies Research Articles

Trends and Influencing Factors in Film Box Office: A Study on Chinese Domestic and International Films

At present, box office performance has become one of the critical indicators of a film's success. Both domestic and international film markets have shown steady growth; however, the box office performance of different films varies significantly. In light of this, this paper focuses on the box office development of domestic and foreign films, reviewing and analyzing the factors that influence the box office performance of many films. Additionally, a comparative analysis between domestic and foreign films is conducted. According to research findings, the primary factors affecting the box office performance of domestic films include the "mainstream" theme, storyline, realistic social topics, release timing, and multimedia promotion. In contrast, the factors influencing the box office performance of foreign films mainly involve the production company, country of origin, type of film, technological innovation, and online reputation. Based on these findings, this paper further analyzes the shortcomings that have led to the box office failures of both domestic and foreign films. Furthermore, recommendations for enhancing box office performance, applicable to all films, are proposed from four dimensions: film content, filming technology, market timing, and marketing strategies.

Informed Trading and Return Predictability in China: Research Based on Ensemble Neural Network

ABSTRACT We construct a new informed trading index based on the high-frequency trading data of the Chinese A-share market using the ensemble neural network algorithm. We find that the informed trading index is a strong negative predictor of future aggregate stock market returns, with monthly in-sample and out-of-sample R 2 of 5.45% and 3.53%, respectively, which is far greater than the predictive power of other previously studied informed trading indicators and macroeconomic variables. The asset allocation strategy based on our index can generate large economic gains for the mean-variance investors, with annualized CER (certain equivalent return) gains ranging from 10.91% to 7.80% as the investor’s risk appetite varies. The driving force of the predictive power appears to stem from the liquidity provider role that informed traders play, which decreases the market’s illiquidity risk and lowers the risk premium of equity. Our analysis complements the returns predictability study by adding a new predictor on the one hand and informs market timing strategies on the other.

STRATEGIC TIMING: ANALYZING MARKET TIMING STRATEGIES FOR NON-FINANCIAL COMPANIES' LEVERAGE

This study investigates the impact of market timing strategies on the leverage of non-financial companies. Market timing involves making financial decisions based on expectations of future market movements. Using a sample of non-financial firms, we examine how companies strategically time their debt issuance and repayment activities in response to market conditions. Our analysis considers factors such as interest rate fluctuations, market volatility, and economic cycles. We employ quantitative methods to assess the effectiveness of different market timing strategies in influencing firms' leverage levels. The findings shed light on the dynamics between market conditions and corporate leverage decisions, providing valuable insights for financial managers, investors, and policymakers.

Algorithm-Based Low-Frequency Trading Using a Stochastic Oscillator and William%R: A Case Study on the U.S. and Korean Indices

Using stochastics in stock market analysis is widely accepted for index estimation and ultra-high-frequency trading. However, previous studies linking index estimation to actual trading without applying low-frequency trading are limited. This study applied William%R to the existing research and used fixed parameters to remove noise from stochastics. We propose contributing to stock market stakeholders by finding an easy-to-apply algorithmic trading methodology for individual and pension fund investors. The algorithm constructed two oscillators with fixed parameters to identify when to enter and exit the index and achieved good results against the benchmark. We tested two ETFs, SPY (S&P 500) and EWY (MSCI Korea), from 2010 to 2022. Over the 12-year study period, our model showed it can outperform the benchmark index, having a high hit ratio of over 80%, a maximum drawdown in the low single digits, and a trading frequency of 1.5 trades per year. The results of our empirical research show that this methodology simplifies the process for investors to effectively implement market timing strategies in their investment decisions.

Research on the Current Situation of Quantitative Investment in China

Quantitative investment, as one of the many tools in the investment toolkit, plays a significant role in investment practice. Quantitative investment strategies encompass quantitative industry allocation, stock selection, and market timing strategies, among others. In the highly developed capital markets of the United States, quantitative investment has a history spanning several decades. It has garnered praise from numerous corporations and individual investors for its stable investment returns and rational investment style, making it an essential decision-making factor for other investors as well. In China, quantitative investment is still in its nascent stages. This article analyzes several issues existing in the Chinese quantitative investment landscape, such as limited hedging mechanisms for investment strategies, some strategies having a significant impact on the market environment, and the incompatibility of the unique Chinese financial market environment with traditional quantitative investment strategies. The article proposes corresponding solutions to these problems, which hold positive implications for further improving China's financial markets.

Critical Factors Influencing New Product Development Success in Sierra Leone Brewery Limited

This research investigates the crucial factors that affect new product development (NPD) in the beverage industry, concentrating on Sierra Leone Brewery Limited (SLBL). Acknowledging the inherent risks and uncertainties in NPD, the study seeks to recognize and assess both internal and external factors that influence the success of new product initiatives at SLBL. The analysis examines key elements (timing, pricing, packaging, testing, competition, market selection, promotional strategies, and brand development) to enhance our understanding of factors shaping new product introductions within the company. The study uses a case study approach, analyzing primary and secondary data to understand SLBL's new product development. It employs a phenomenological research approach involving stakeholders like managers, product developers, marketing personnel, and consumers. The study utilizes the supply chain and distribution theory as a theoretical framework to understand the factors influencing new product development in the beverage industry. SLBL adopts a meticulous NPD approach, using feasibility studies for decision-making. The concept development phase outlines a trajectory and collaboration, serving as a blueprint. Crafting business cases ensures strategic alignment, and the asset and recipe development phase emphasizes innovation. In material ordering, production, and sampling, SLBL prioritizes strategic procurement and stringent quality control. The success of the product launch depends on factors like market timing and effective promotional strategies. Diverse research methods contribute to a comprehensive analysis, and strategic recommendations include innovation, rebranding, extensive promotion, repositioning, and careful financial allocation. SLBL's NPD approach reflects strategic foresight and commitment to excellence for sustained success in a competitive market.

Practical Applications of Leading Economic Indicator and Global Stock Market Returns

In <ext-link><bold><italic>Leading Economic Indicator and Global Stock Market Returns</italic></bold></ext-link>, from the Summer 2022 issue of <bold><italic>The Journal of Wealth Management</italic></bold>, <bold>Todd Feldman</bold> and <bold>Alan Jung</bold>, both of <bold>San Francisco State University</bold>, present a market-timing strategy based on combining the Conference Board’s Leading Economic Index (LEI) with a 200-day simple moving average (SMA). This LEI/SMA strategy signals when to exit the stock market and move to cash and when to return to the stock market. In a 2015 study (<xref>Feldman, Jung, and Klein 2015</xref>), the authors demonstrated that for the US stock market, the LEI/SMA strategy outperformed other simple market-timing strategies, as well as a buy-and-hold strategy. In this article, Feldman and Jung expand their analysis of the LEI/SMA strategy and include the stock markets of the United States and seven other countries. They find that the LEI/SMA strategy performs better than a buy-and-hold strategy in all but two of those countries. Additionally, the authors show how global economic indicators can be useful in timing US market decisions.

A Market Timing Strategy for the GCC Conventional and Shariah Stock Indices

This paper defines and assesses a market timing strategy for the Gulf Cooperation Council (GCC) stock indices, namely the Tadawul All Share Index, FTSE Abu Dhabi General Index, Qatar All Share Index and Qatar Al Rayan Islamic Index. The strategy intends to deliver a consistent reduction in volatility and better risk-adjusted performance. The present empirical study capitalises on the work by Colepand and Copeland (1999) on the US market, re-proposed recently by Bantwa (2020) on the Indian market, which resorts to implied volatility as the trigger to adjust the asset allocation. The strategy hereby proposed is modified considering the higher volatility of the GCC financial markets as well as its preeminent goal – risk-adjusted performance optimisation. Moreover, the implied volatility is unavailable for the GCC stock indices under assessment; therefore, it has been replaced with the forecasted volatility obtained through asymmetric GARCH models (GJR-GARCH), one for each stock index. The active strategy in question is backtested on both the conventional and Islamic stock indices to check whether it overperforms the passive strategy equally well on both types of indices. The empirical findings encourage the adoption of volatility-based market timing models in additional emerging markets and Islamic indices.

Avoid Equity Bear Markets with a Market Timing Strategy

Avoid Equity Bear Markets with a Market Timing Strategy

Who and what drives informed options trading after the market opens?

AbstractThis study examines what affects the return predictability of option order imbalances immediately after the market opening and who contributes to this predictability. Although intraday momentum is insignificant, option order imbalances in the first 10 min of trading significantly predict the returns of stock index and index futures for the remainder of the day. Simple market timing strategies result in significant profits even after transaction costs are incurred. This predictive power is more prominent when uncertainty exists in the market or options are attractive to informed investors. Such predictability is mainly driven by institutional traders rather than day traders.

THE IMPACT OF INTRADAY MOMENTUM ON STOCK RETURNS: EVIDENCE FROM S&amp;P500 AND CSI300

This paper analyzes the statistical impact of COVID-19 on the S&amp;P500 and the CSI300 intraday momentum. This study employs an empirical method, that is, the intraday momentum method used in this research. Also, the predictability of timing conditional strategies is also used here to predict the intraday momentum of stock returns. In addition, this study aims to estimate and forecast the coefficients in the stock market pandemic crisis through a robust standard error approach. The empirical findings indicate that the intraday market behavior an unusual balanced; the volatility and trading volume imbalance and the return trends are losing overwhelmingly. The consequence is that the first half-hour return will forecast the last half-hour return of the S&amp;P500, but during the pandemic shock, the last half-hour of both stock markets will not have a significant impact on intraday momentum. Additionally, market timing strategy analysis is a significant factor in the stock market because it shows the perfect trading time, decides investment opportunities and which stocks will perform well on this day. Besides, we also found that when the volatility and volume of the S&amp;P500 are both at a high level, the first half-hour has been a positive impact, while at the low level, the CSI300 has a negative impact on the last half-hour. In addition, this shows that the optimistic effect and positive outlook of the stockholders for the S&amp;P500 is in the first half-hours after weekend on Monday morning because market open during the weekend holiday, and the mentality of every stockholder’s indicate the positive impression of the stock market.

THE SEARCH FOR TIME-SERIES PREDICTABILITY-BASED ANOMALIES

This paper introduces a new algorithm for exploiting time-series predictability-based patterns to obtain an abnormal return, or alpha, with respect to a given benchmark asset pricing model. The algorithm proposes a deterministic daily market timing strategy that decides between being fully invested in a risky asset or in a risk-free asset, with the trading rule represented by a parametric perceptron. The optimal parameters are sought in-sample via differential evolution to directly maximize the alpha. Successively using two modern asset pricing models and two different portfolio weighting schemes, the algorithm was able to discover an undocumented anomaly in the United States stock market cross-section, both out-of-sample and using small transaction costs. The new algorithm represents a simple and flexible alternative to technical analysis and forecast-based trading rules, neither of which necessarily maximizes the alpha. This new algorithm was inspired by recent insights into representing reinforcement learning as evolutionary computation.

How Much Information Is Required to Time the Market?

In this article, the authors present an analytical explanation for why it can be difficult to devise a successful market timing strategy. The authors derive formulas to estimate the minimum required information coefficient for a timing strategy to outperform a buy-and-hold market benchmark, both with and without an alpha target. They show that markets with high Sharpe ratios and those that have low volatility are by nature hard to time. They also show that having high market exposure in a market timing strategy is generally beneficial; however, there can be a critical point beyond which additional market exposure makes timing more difficult. The authors extend the model to cover practical considerations such as transaction costs, skewness and fat tails, and market timing with two correlated assets. Finally, they present a case study to illustrate how investors could apply their framework to choose the optimal market exposure in a market timing strategy using the S&amp;P 500. <b>Key Findings</b> ▪ Under a bivariate normal framework, the authors show that the expected return of a timing strategy comes in two additive parts: one part driven by timing information and the other driven by average market exposure. ▪ There is generally a theoretical nonzero information threshold for a timing strategy to beat a buy-and-hold benchmark. This threshold can serve as a useful guide to determine whether a timing strategy is likely to succeed, complementing historical backtests. ▪ Although an investor can increase timing strategy return by increasing average market exposure without having more timing information, the difficulty of beating a buy-and-hold benchmark with an alpha target increases dramatically as average market exposure becomes very high.

Market-timing performance of mutual fund investors in Emerging Markets

This paper empirically investigates the performance of market-timing strategies effectively used by investors in Emerging Markets (EMs). We identify short-term determinants of mutual fund flows into EM equity and fixed income, finding a well-established flow-performance relation. Hence, we verify whether investors make good timing decisions with a statistic hereafter referred to as “performance gap”. We find that the average performance gap is negative and statistically significant for all funds. It is equal to −0.05% per month for equity and −0.06% for fixed income. Although gaps remain negative regardless of the strategy declared by the fund manager, corporate and growth funds exhibit the worst performance.

Predicting equity premium with adjusted dividend-price ratio: the USA and international evidence

Purpose This paper aims to achieve two main objectives. The first is to introduce a suitable adjustment to the conventional dividend-price ratio, which would address econometric concerns and improve the predictability of the equity premium. The second is to compare the predictive performance of the newly introduced adjusted dividend-price ratio with the conventional dividend-price ratio. Design/methodology/approach The authors hypothesize that the adjusted dividend-price ratio will have better predictive power and forecasting quality for equity premium compared to the conventional dividend-price ratio. To test the hypothesis, the authors predict equity premium with both variables on a sample of 11 developed and emerging market indexes over a period spanning June 1995 to March 2017. To accommodate time variation in parameter values or structural breaks in the data, the authors conducted a fixed window rolling regressions using both variables. A variety of forecast techniques including magnitude and sign accuracy measures are applied to compare the performance of forecasts. Findings The adjusted dividend-price ratio is shown to be stationary and has both lower persistence and variability compared with the conventional dividend-price ratio. The authors find that the adjusted dividend-price ratio provides superior out-of-sample (OOS) performance compared to the conventional dividend-price ratio, for both size and sign accuracy, in forecasting equity premium for the majority of the countries in the sample. Research limitations/implications This paper introduces an easy-to-follow modification in the conventional dividend-price ratio that can be replicated by researchers and practitioners alike. However, the study has a limitation in that it does not capture the impact of dividend-paying firms within each index on the predictive ability of the adjusted dividend-price ratio. Practical implications The knowledge of equity premium predictability is important in implementing market-timing strategies and could be beneficial for portfolio and risk management. The newly introduced variable is easy to construct using widely available data without the need for complex econometric estimation. Investors can use this variable to predict equity premiums in international markets, both developed and emerging. The findings of this paper will be relevant to financial analysts, portfolio managers, investors and researchers in international finance. For example, by using the adjusted dividend-price ratio, investors would see up to 0.5% improvement in their OOS monthly forecasts of the equity premium. Originality/value To the best of the authors’ knowledge, this is the first paper that proposes adjustment in the conventional dividend-price ratio based on the past observations of the most recent quarter. In this way, the paper offers fresh insight that dividend-price ratio is still useful to predict equity premium albeit, after some adjustments and modifications. The findings of the paper would result in renewed interest in using the dividend-price ratio as a predictor of the equity premium.

Systematic investment plans vs market-timed investments

ABSTRACT This paper examines the performance of the Systematic Investment Plan (SIP) and different market timing strategies. The components of the NIFTY50 index are considered for the analysis. The empirical results suggest SIP as a suitable investment strategy for long-term investments and for the stocks belonging to least and moderately volatile. During shocks, absolute momentum investment is a superior short-term investment strategy for highly volatile sectors. Fundamental values also play an important role in deciding the suitable investment strategy. Over the long run, stocks with a higher return on capital employed (ROCE), favours the SIP investment strategy.

The Relation Between Trading Volume Concentration and Stock Returns

The Taiwan Stock Exchange discloses data on daily trading volume across brokerage firms for each listed stock. Market practitioners suggest that the concentration of trading volume contains information on the trading behaviors of big players. We use the Gini Coefficient to measure the degree of concentration, upon which a trading strategy is proposed. We conduct an event study to examine whether such a strategy will yield abnormal returns. Our sample contains 375 listed companies with events identified during the sample period from February 2020 to August 2020. The empirical results show that the trading signal based on the Gini coefficient is informative and that most of the average abnormal returns after the event date are significantly positive with the cumulative average abnormal returns increasing almost monotonically up to the end day of the event window. Consistent with prior studies in which different measures of concentration are utilized, our findings provide additional evidence that the Gini Coefficient could help investors to develop profitable stock selection and market timing strategies.

Market Timing and Stock Selection Strategies in Shariah- Compliant Stock Portfolio

This study focuses on market timing and stock selection strategies that could be implemented by individual investors of Shariah-compliant equity using the top ten constituents of the FTSE Bursa Malaysia Hijrah Shariah Index. Investors are assumed to enter and exit the stock market following the buy-and-sell signal from Moving Average Crossover. Meanwhile, for stock selection, this study aims to construct the optimal portfolio using the Sharpe Ratio Maximisation model and Naïve (1/N) portfolio. The level of market timing and selectivity skills of individual investors following the suggested investment strategies will be measured by using the Treynor-Mazuy model. The empirical results showed that the best Moving Average Crossover gave plausible trading frequencies and provided the most return to investors was the (1, 100, 0.01) strategy. Albeit, the stock allocation for the constructed portfolio was less diversified compared to the Naïve (1/N) portfolio, the composition of portfolio weights of the constructed portfolio was able to offer a more than average risk to reward ratio. Furthermore, in the out-of-sample framework, both portfolios outperformed the market benchmark. Unlike previous studies, this study backed tests the strategy and found that it was beneficial for individual investors of Shariah-compliant equities to enhance market timing and selectivity skills in stock investment.

Overnight Return Momentum: Evidence from European Markets

The increased role played by passive equity investors is associated with significant changes in intraday trading patterns. The authors study the dynamics of stock index returns in major European markets during the last 30 minutes before market close and show that they can be predicted by overnight returns. An intraday market-timing strategy the authors formulated to exploit this dynamic delivered sizable economic gains across all markets since 2000. The strategy performance is evident across different subsamples and market conditions, is robust to various implementation assumptions and transaction costs, and cannot be explained by calendar effects or other risk factors. <b>TOPICS:</b>Fundamental equity analysis, exchange-traded funds and applications, developed markets, performance measurement <b>Key Findings</b> ▪ The last half-hour of stock returns in several major European markets can be predicted by overnight returns at the market level. ▪ Intraday market-timing strategies based on overnight returns have delivered sizable economic gains across European countries relative to benchmarks since 2000. ▪ Strategy performance is present after transaction costs and across different subsamples and market conditions, is robust to alternative implementation assumptions, and cannot be explained by calendar effects or other risk factors.

Macroeconomic variables for predicting bear stock markets of Taiwan and China

PurposeThis research examines how macroeconomic variables can precisely predict bull/bear stock markets in China and Taiwan.Design/methodology/approachThis paper adopts a two-state Markov switching model to characterize the bull and bear markets spanning from 1994 to 2019 and then conduct a bear stock market predictability test by running regressions between the filtered probabilities of bear markets and a series of macroeconomic variables in turn at different horizons of 1, 3, 6, 12 and 24 months.FindingsThis paper shows that inflation rates, changes in real exchange rates, and foreign currency reserve growth are key predictors of bear markets in China, while term spreads, unemployment rates and foreign reserve growth are major factors that can predict bear markets in Taiwan. Remarkably, industrial production growth does not have predictive power for bear markets, which may suggest emerging markets are driven by fund flows rather than real economic activities. Besides, the impact directions of foreign currency reserve growth are opposite, which may be due to different proportions of the financial accounts in their balance of payments.Practical implicationsIn practical respect, this paper provides market participants the usefulness, impact direction and implications of bear market predictors when building their market-timing strategies in China and Taiwan stock markets. The government institutions may also thereby make appropriate policies to prevent huge stock market downturns and serious drawbacks.Originality/valueIt highlights the “fund-driven market hypothesis” and “foreign currency reserve effects” that commonly dominate Taiwan and China stock markets since both are highly affected by international funds.