Abstract
According to traders and investors, combined strategy gives better returns than individual strategy for the security analysis in the stock market. But traders and investors have a trend of first using one of oldest strategy; Moving Average Crossover (Crossover) because this strategy gives upcoming trend direction directly and easily. In this paper, we compare the return of hybrid strategy namely Hybrid Strategy of Donchian Channel and RSI (DCRSI), Hybrid Strategy of Parabolic SAR and EMA (PSAREMA) and Moving Fibonacci Strategy (MF) with the oldest strategy Crossover. Also, we check the profitability of these strategies in different market conditions and demonstrate on NSE data through R-Programming.
Highlights
Mathematical Study of the financial markets is an ongoing process, and a lot of economic and financial theories rely on mathematical models of risk to accomplish such studies
To identify the trend of the market, there are many technical trend indicators that are working on the phenomena of mean reversion and help us to understand upcoming trends
Comparative Study of Hybrid Strategies with Moving Average Crossover security means that an analytical approach that focuses on the underlying fact set to forecast the future price of a security Bollinger (2002)
Summary
Mathematical Study of the financial markets is an ongoing process, and a lot of economic and financial theories rely on mathematical models of risk to accomplish such studies. The main and direct application of mean reversion phenomena in the financial market is to identify market trends. The meaning of market trend is a perceived tendency of the financial market to move in a particular direction over time. To identify the trend of the market, there are many technical trend indicators that are working on the phenomena of mean reversion and help us to understand upcoming trends. We wish to study deeply and analyze the concept of technical trend indicators using data from NSE and demonstrate how we can progress towards understanding technical analysis better
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