Identification of short-term and long-term time scales in stock markets and effect of structural break

Abstract

The paper presents the comparative study of the nature of stock markets in shortterm and long-term time scales with and without structural break in the stock data. Structural break point has been identified by applying Zivot and Andrews structural trend break model to break the original time series (TSO) into time series before structural break (TSB) and time series after structural break (TSA). The empirical mode decomposition based Hurst exponent and variance techniques have been applied to the TSO, TSB and TSA to identify the time scales in shortterm and long-term from the decomposed intrinsic mode functions. We found that for TSO, TSB and TSA the short-term time scales and long-term time scales are within the range of few days to 3 months and greater than 5 months respectively, which indicates that the short-term and long-term time scales are present in the stock market. The Hurst exponent is ∼ 0.5 and ≥ 0.75 for TSO, TSB and TSA in short-term and long-term respectively, which indicates that the market is random in short-term and strongly correlated in long-term. The identification of time scales at short-term and long-term investment horizon will be useful for investors to design investment and trading strategies.Investors adopt different strategies in short-term and long-term depending on the investment time horizon as stock markets show different dynamics in different time scales. Hence identification of time scales in short-term and long-term is very important. The time scales have been identified using the empirical mode decomposition based Hurst exponent and normalised variance technique. The robustness of the analysis is further confirmed with Zivot and Andrews structural trend break model. Stock markets show random nature in short-term with time scales ranging from few days to nearly 3 months, and in long-term it shows long-range correlation with time scales greater than 5 months. We hope that these results may help the investors to take better decision on devising short-term and long-term trading strategies.

Can Crude Oil Serve as a Hedging Asset for Underlying Securities?—Research on the Heterogenous Correlation between Crude Oil and Stock Index

“…In the long run, the correlation between returns on different financial assets will not remain constant. Mahata et al [45] separated the stock market into the long term and the short term. They considered the structural change relationship between the financial market and extreme events under different time scales and helped market participants to determine investment strategies.…”

Time Scales and Characteristics of Stock Markets in Different Investment Horizons

“…In the stock markets, there are mainly two types of investors: short-term investors who invest for short-term gain and long-term investors who invest for long-term gain [6,7]. Studies show that the ITH for short-term investors ranges from a single day to a few months, and for long-term investors, it usually ranges from a few months to several years [8,9]. The fund managers and foreign exchange dealers of various countries use technical analysis for the short-term ITH and fundamental analysis for the long-term ITH [8,10].…”

“…As the market is mean reversing in short-term ITH [9], traders fail to generate significant returns using technical analysis [11]. On the other hand, in the long-term ITH, an investor can generate significant return or help in making decision whether to exit from that particular stock to avoid loss by determining the financial health of a company by using fundamental variables [12][13][14].…”

“…However, the fundamental variables are the main determining crucial factors in the long-term ITH. Usually, investors choose the τ of short-term and long-term investment horizon in an arbitrary manner [8,9]. Recently, we used structural break study to show that the τ for the short-term is usually less than a few months [9].…”

“…Usually, investors choose the τ of short-term and long-term investment horizon in an arbitrary manner [8,9]. Recently, we used structural break study to show that the τ for the short-term is usually less than a few months [9]. The separation of the short-and long-term dynamics in terms of τ plays a vital role in the prediction of future price movement.…”