**What is Volatility ratio?**

The Term Volatility ratio is coined by Jack D. Schwager to identify trading range and potential trend reversal. The values of the volatility ratio range from 0.01-1.00 and typically traders predicts the reversal points if the value shows above 0.5. However marketcalls recommend to look for reversal above 0.6.

**Volatility ratio formula**

Volatility Ratio (VR) = Today’s True Range/True Range over N number of days

To calculate the volatility ratio, the true range is calculated using the following formula:

Today’s True Range = MAX (today’s high, yesterday’s close) – MIN (today’s low, yesterday’s close)

andTrue Range over N number of days= MAX (Day1 High, Day 2 High, …Day N High, Day 0 Close) minus MIN(Day1 Low, Day 2 Low, …Day N Low, Day 0 Close)

**Volatility ratio – Amibroker AFL code**

_SECTION_BEGIN("Volatility Ratio"); //{Volatility Ratio - Schwager} //Coded By Rajandran R - www.marketcalls.in //Date - 18 Feb 2012 n=Param("Periods",13,1,300,1); VRT=Param("VRthreshold",0.6,0.5,1,0.1); Dday =Param("Decision Day Based on Prev day returns",4,3,5,1); zero=10^-10; r1=H-L; r2=abs(H-Ref(C,-1)); r3=abs(Ref(C,-1)-L); TrueRange=Max(Max(r1,r2),r3); TrueHighPds=Max(HHV(H,n),Ref(C,-n)); TrueLowPds=Min(LLV(L,n),Ref(C,-n)); TrueRangePds=TrueHighPds-TrueLowPds; VolatilityRatio=TrueRange/Max(TrueRangePds,zero); SetPositionSize(1,spsShares); decisionSell=HHV(C,5)-C; decisionBuy=C-LLV(C,5); Buy =decisionBuy>0 AND Cross(VolatilityRatio,VRT); Sell =0; Short=decisionSell>0 AND Cross(VolatilityRatio,VRT); Cover=0; Plot(VolatilityRatio,"Volatility Ratio - Schwager",colorRed); _SECTION_END();

The above code has been derived from the following metastock code as shown below

{Volatility Ratio - Schwager} n:=Input("Periods",1,253,14); zero:=Power(10,-10); r1:=H-L; r2:=Abs(H-Ref(C,-1)); r3:=Abs(Ref(C,-1)-L); TrueRange:=Max(Max(r1,r2),r3); TrueHighPds:=Max(HHV(H,n),Ref(C,-n)); TrueLowPds:=Min(LLV(L,n),Ref(C,-n)); TrueRangePds:=TrueHighPds-TrueLowPds; VolatilityRatio:=TrueRange/Max(TrueRangePds,zero); {plot VR} VolatilityRatio;

**Builing a Trading System using Volatility Ratio**

Now to understand the predictive nature of Volaitity Ratio in idenfitying price reversal we built a simple trading system

The concept is to Buy when Volatility ratio is greater than 0.6 and the past 5 days returns are negative and on the reverse short if the Volatility ratio is greater than 0.6 and the past 5 days returns are positive. And now exit after 10 days of holding the instrument.

We tested the trading system with our benchmark index Nifty on the Daily timeframe. Here is the results about the predictive nature of the indicator followed by snapshots of the signals when volatility ratio crosses 0.6 with period =13

Parameters | Results |
---|---|

Tested Symbol | NSENIFTY |

Total Number of Trades | 52 |

Holding Period | 10 Days |

Winning Trades | 32 |

Winning Ratio | 61.54% |

Points Earned | 2000 Nifty points |

Testing Period | 1991-2012 (23 years) |

Charts below the buy and sell indications for the past 5 years when the volatility ratio shoots above 0.6

**Nifty Daily Chart – 2012**

No signals during the year 2012 and 2013

Hope the above article gives your more understanding about the nature of volatility ratio. Test the indicator and provide your feedback here. Your feedback is much are appreciated

Amazing ..thanks Rajandran R

nice

I found this RSI most interesting but noted no Buy/Sell arrows so added (see below). They should work but don’t so any help will be appreciated.

Dick

Note: send correction to me @ areehoi@yahoo.com

Thanks

SECTION_BEGIN(“Volatility”);

//{Volatility Ratio – Schwager}

//Coded By Rajandran R – http://www.marketcalls.in

//Date – 18 Feb 2012

/*The concept is to Buy when Volatility ratio is greater than 0.6 and the past 5 days returns are negative and on the reverse short if the Volatility

ratio is greater than 0.6 and the past 5 days returns are positive. And now exit after 10 days of holding the instrument.*/

n=Param(“Periods”,13,1,300,1);

VRT=Param(“VRthreshold”,0.6,0.5,1,0.1);

Dday =Param(“Decision Day Based on Prev day returns”,4,3,5,1);

zero=10^-10;

r1=H-L;

r2=abs(H-Ref(C,-1));

r3=abs(Ref(C,-1)-L);

TrueRange=Max(Max(r1,r2),r3);

TrueHighPds=Max(HHV(H,n),Ref(C,-n));

TrueLowPds=Min(LLV(L,n),Ref(C,-n));

TrueRangePds=TrueHighPds-TrueLowPds;

VolatilityRatio=TrueRange/Max(TrueRangePds,zero);

SetPositionSize(1,spsShares);

decisionSell=HHV(C,5)-C;

decisionBuy=C-LLV(C,5);

Buy =decisionBuy>0 AND Cross(VolatilityRatio,VRT);

//Sell =0;

Sell =decisionSell>0 AND Cross(VolatilityRatio,VRT);

Cover=0;

//Plot( Buy, “Buy”, colorBlack, styleLine );

HLine = Param( “Upper Line” ,0.6, 60,95, 5);

LLine = Param( “Lower Line”,0.2, 5, 40, 5);

Plot( Lline, “0.6”, colorBrown,styleLine|styleDashed );

Plot( Hline, “0.2”, colorBrown,styleLine|styleDashed );

Plot(VolatilityRatio,”Volatility Ratio – Schwager”,colorRed,styleThick);

shape = Buy * shapeHollowUpArrow + Sell * shapeHollowDownArrow;

PlotShapes(IIf(Buy,shapeUpArrow,shapeNone),colorBrightGreen,0,L,-15);

PlotShapes(IIf(Buy,shapeHollowUpArrow,shapeNone),colorBrightGreen,0,L,-15);

PlotShapes(IIf(Sell,shapeDownArrow,shapeNone),colorRed,0,H,-15);

PlotShapes(IIf(Sell,shapeHollowDownArrow,shapeNone),colorRed,0,H,-15);

_SECTION_END ();

thanks for ur valuable effort ,plse guide me how to copy into ami charts the above afl code

Raj,

I left response (above) but never received a reply.

Dick

its definitely going to generate a lot of short signals than the long ones.

I tested this strategy using MetaStock. While this strategy performance is good post 2007, the period between 2000 to 2007 it actually lost money (almost all of it). How can the draw down could be reduced. Also wondering how Nifty data in Amibroker is available from 1991 when NSE started it from 1994.

Hello Sir, I want to know if you have a candlestick AFL. I want to scan for candlestick patterns. Is there a possibility to get realtime alerts? For example if a morning star pattern has occurred in SBIN, then it must alert me that SBIN has a morning star pattern.

I want to congratulate you on all the new things that you bring on your website. Thanks for everything.

Karuna