NIFTY 50 (Monthly outlook)
Francisco Lichucha
Quantitative and Research Analyst| Quantitative trader| Finance Graduate
The Nifty 50, a benchmark market index in India, represents the weighted average of 50 of the largest and most liquid companies listed on the National Stock Exchange (NSE). Known for its high trading volumes and volatility, the Nifty 50 is, in every sense of the term, a playground for day traders looking to capitalize on intraday price movements.
Let's briefly set up the analysis environment, from the perspective of a Quant.
The calculated data shows negative skewness, this means that for day traders (not recommended) would benefit more from taking shorts or buying puts whenever prices are in the overbought region.
(Statistical Descriptors) Dec 13 - Jan 13
Mean- 23681.61904
std- 359.68027
min- 23047.25
25%- 23503.05
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50% - 23637.8
75%- 23800.6
max - 24601.75
With the above statistical descriptors, we can try to identify, through the use of stochastic differentials, the focused entry points for potential trades, rather then waiting for chart patterns and indicators to determine your entries, we can set pending orders at the points recommended by the data and apply hedging strategies for edge cases in which prices break out of the registered levels above, till then, there are substantial intra day shorts with sporadic but regular buys.
After measuring the mean reversion rate using the Ornstein-Uhlenbeck (OU) Process, it has been established that it reverts to the mean (23681.61904) at a rate of 2%. By plugging this data into GBM models followed by Garch Models we can better set our strategies for the remainder of the month of January.
Author's note; This analysis is very short-term in its thinking. It is meant to be used by day traders. The argument behind this research can change as soon as the key levels are broken. In future articles, we can discuss all the different hedging strategies that exist, relevant to day trading, that can allow us to optimize our trading setup for consistent risk-adjusted returns.