How to handle Market correction/crash???

[skgarg]

Most of the trading systems work fine in bullish markets.But they fail miserably during market crash.

What if someone relies upon a trading system which has been giving good performance during backtesting and when she invests her capital according to its signals and the next day its boommmm.....market crash!!!!

so basically,through this thread i want to discuss upon matters of market crash and that how to identify them early through technical indicators.

I went through that system implementation excercise thread and it was found that the system performance was greatly hampered by volaitile action of the market.

So I request all the senior members to come up and share their knowledge.

 

[skgarg]

As per my understanding,I think that a technical indicator based on Traded Volume can serve the purpose.I read somewhere reading that "Volume is the fuel" which drives the trend.If there is not enough volume,the trend is sure to fail.A strong movement in stock price is generally preceded with high traded volume.

So may be the MABIUTS system can incorporate a volume indicator also in it and a shot can be given to it.

 

[sudoku1]

as a lay man.....one should look for signs of froth around us....like
>more crowd &chaos in broker's office
>rise in numner of tipsters
>neighbours & newcomers entering for quick gains
>no of stocks rising in ban period in f&o
>rise in risk appetite .....etc ,etc

 

[skgarg]

Hello Sudoku

Thanks for replying

However i am looking from a TA perspective as to how to develop a trading system which keeps sudden market falls also in mind.I wud be happy if some more members give in their views.

I just downloaded the free unregistered version of Amibroker.Is it possible to carry out all this scanning of stocks and backtesting stuff in it or does one has to register it??

 

[oxusmorouz]

Most of the trading systems work fine in bullish markets.But they fail miserably during market crash.

So I request all the senior members to come up and share their knowledge.

Maybe using a monte carlo simulation engine to produce hypothetical stock prices incorporating different scenarios will be of help. You can do this in excel itself, but there are a few softwares which can read ascii or metastock data directly, like this one (Can't guarantee you on performance of any software)

 

[CreditViolet]

Maybe using a monte carlo simulation engine to produce hypothetical stock prices incorporating different scenarios will be of help. You can do this in excel itself, but there are a few softwares which can read ascii or metastock data directly, like this one (Can't guarantee you on performance of any software)

What about things like stationarity, fat tails etc?

 

[omkarmango]

Most of the trading systems work fine in bullish markets.But they fail miserably during market crash.

What if someone relies upon a trading system which has been giving good performance during backtesting and when she invests her capital according to its signals and the next day its boommmm.....market crash!!!!

so basically,through this thread i want to discuss upon matters of market crash and that how to identify them early through technical indicators.

This is not true.... what u are talking is about junk.. pro bull systems.

Not the crashes... but sluggish markets are graveyards of the so called good systems.

 

[oxusmorouz]

What about things like stationarity, fat tails etc?

Great to see you posting again CV. From what I can see, the distribution problem can also be handled in excel itself by multiplying the standard deviation by a constant value, for a given mean (in a log distribution). If the mean daily return is found out to be .0% a day with a SD of 1 (say), a constant of 1.2 (say) is multiplied to get a value of 1.2% ( instead of 1, as assumed in lognormal distribution).
The function, NormalRandom(0,1.2) [where 0 is the mean and 1.2 is the new standard deviation] has the usual 99% of the items within 3.6 of the original standard deviation and not 3.
Once the returns for n days are calculated and the 1st price is known, we can find the stock price for each of the n days by Previous price*(1 + current returns).

Of course, while this deals with kurtosis, it doesn't take into consideration the skewness. Any other way to handle this problem CV?

 

[raosrinivas]

monte carlo similation, lagrangian interpolation, standard deviation, lognormal distribution, i am so scared, do i have a chance to make any money in stock market when i don't really understand anything here. luckily some one said 'when you see a phd running a company , run away from it', so i have some remote chance. all of this reminds me of my statistics and operations research classes.

 

[franktrader]

monte carlo similation, lagrangian interpolation, standard deviation, lognormal distribution, i am so scared, do i have a chance to make any money in stock market when i don't really understand anything here. luckily some one said 'when you see a phd running a company , run away from it', so i have some remote chance. all of this reminds me of my statistics and operations research classes.

one of my friend told me the full form of phd - Permanent Head Damaged !!!!

although it does not applies to all Phd's ,
exceptions are always there