Buchempfehlung für Riskkennzahlen in Performancereport in TS??

Hi

Kann mir jemand ein Buch empfehlen, in dem Risikokennzahlen der TS erklärt werden (RINA usw)???

Danke

RE: Buchempfehlung für Riskkennzahlen in Performancereport in TS??

hello Howe,

der volle Titel ist "Profit Strategies: Unlocking trading performance with Money Management" von David Stendahl.

Stendahl war früher, zum Zeitpunkt des Schreibens, Mitarbeiter bei RINA. RINA hat Strategy Evaluator für TS2000i geschrieben.

Das Buch ist von RINA oder Tradersworld zu beziehen.

grüße,

Jim

RE: Sharpe Ratio

hallo Howe,

Nicht alle System Reports zeigen ein Sharp Ratio, aber in RINA Portfolio Evaluator schon.
Hier sind einige Auszüge zu diesem Thema aus der Omega List.

Improving the Sharpe Ratio


By Kevin Dowd, Ph.D.

How do we choose between alternative investments that have
differing expected returns but also entail different degrees of risk?
In particular, given that higher expected returns are desirable but
higher risks are not, how should we choose between an
investment with a high expected return and a relatively high risk,
and an alternative investment with a lower expected return and
lower risk? The obvious answer is that we should adjust
expected returns for the risks involved, but how should we make
this adjustment?

The traditional answer is that we should use the Sharpe ratio (see
Sharpe (1966)). Suppose we have a portfolio, p, with an
expected return , and are using a benchmark, b, with an
expected return . Assume too that all returns are normally
distributed. If d is the differential expected return,-, then
our portfolio’s Sharpe ratio is:

(1) =

where is the predicted standard deviation of d. This ratio
takes account of both the expected differential return between
two portfolios and the associated differential risk. Since it gives
risk estimates before decisions are actually taken, the Sharpe
ratio can be useful for decision-making and, in particular, for
choosing between alternative risky investments.

Note that the Sharpe ratio always refers to the differential
between two portfolios. We can think of this differential as
reflecting a self-financing investment portfolio, with the first
component representing the acquired asset and the second
reflecting the short position taken to finance that acquisition. As
Sharpe himself explains,

Central to the usefulness of the Sharpe Ratio is the
fact that a differential return represents the result of
a zero-investment strategy. This can be defined as
any strategy that involves a zero outlay of money in
the present ... . A differential return clearly falls in
this class, because it can be obtained by taking a
long position in one asset (the fund) and a short
position in another (the benchmark), with the funds
from the latter used to finance the purchase of the
former. (Sharpe (1994, p. 52))

The traditional Sharpe ratio enables us to choose reliably
between two or more alternative investments, provided the
returns to the assets in question are normally distributed and
uncorrelated with the returns to our institution’s existing portfolio:
we simply pick the alternative with the higher Sharpe ratio. In
effect, we can take the Sharpe ratio to be a proxy for the
risk-adjusted return and then choose the investment whose
risk-adjusted return is highest.

However, there is the unfortunate qualification that the traditional
Sharpe ratio presupposes that each prospective investment’s
return is uncorrelated with the return to our existing portfolio. As
Sharpe himself acknowledges, the Sharpe ratio may not give a
reliable ranking if one or more of the assets involved is correlated
with the rest of our portfolio (Sharpe (1994, pp. 54-56)). If asset
A has a lower Sharpe ratio than asset B, the Sharpe ratio
criterion would suggest that we prefer B to A. However, if A’s
return is negatively correlated with the rest of our portfolio and
B’s is positively correlated with our portfolio, then the purchase
of asset A would reduce portfolio risk while the purchase of B
would increase it, and it is possible that we would prefer A over
B if we took these correlation effects into account. Correlations
between the assets in question and the rest of our portfolio mean
that the traditional Sharpe ratio cannot be relied upon to give us
the right answer to our investment problem.

Fortunately, this problem with the traditional Sharpe ratio is easily
put right. All we need to do is redefine our alternatives. Instead
of constructing Sharpe ratios for each of our alternative
investments considered on their own, we construct Sharpe
ratios for each of the alternative portfolios we are choosing
between – each such portfolio consisting of our present portfolio
plus the investment being considered – and then choose the
investment whose associated portfolio has the highest Sharpe
ratio. The optimality of this rule follows from the previous
discussion, which told us that we should choose the position with
the highest Sharpe ratio if the positions being considered are
uncorrelated with the rest of our portfolio - and this condition is
now automatically satisfied.1

Unlike the traditional Sharpe ratio, this new Sharpe rule is valid
regardless of the correlations of prospective new assets with our
existing portfolio. These correlations can take any value, not just
zero, and are already implicitly allowed for in the construction of
the portfolio Sharpe ratio.

The difference between the traditional Sharpe ratio and the
improved one can also be illustrated in terms of the required
returns to alternative investments. If two or more alternative
investments have no correlation with our existing portfolio return,
the two different Sharpe ratios will produce identical – and
correct – rankings of these alternatives, assuming that returns are
normal. Both Sharpe ratios will also give correct estimates of the
alternative investments’ required returns. However, if returns are
positively correlated with our existing portfolio, the traditional
Sharpe ratio will understate the true risk – because it ignores the
correlation – and therefore lead to an underestimate of the
required return on each investment. The higher the correlation,
the greater the underestimate of required returns, and the greater
the potential for mistaken decisions to acquire new positions.
Conversely, if returns are negatively correlated with our existing
portfolio, the traditional Sharpe ratio will overstate the true risk –
again because it ignores the correlation – and lead to an
overestimate of the required return on each investment. And,
once again, the further the correlation is from zero, the greater the
error in our estimate of required returns, and the greater the
potential for us to mistakenly reject good investments. Some
numerical illustrations also confirm that the errors in our estimates
of required returns can very high indeed (Dowd (2000)).

The Sharpe rule proposed here is superior to the traditional
Sharpe ratio because it is valid regardless of the correlations of
the investments being considered with the rest of our portfolio. It
is also straightforward to implement and can be easily
programmed into packages for decision makers to use. Of
course, it still depends on the assumption of normality, and we all
know that this is a very dubious assumption because most returns
are not in fact normally distributed. It should therefore go without
saying that even the improved Sharpe ratio should be used
cautiously where departures from normality may be important.



Kevin Dowd is with the Department of Economics,
University of Sheffield. His email is k.dowd@shef.ac.uk.

This article is abridged from "An improved Sharpe ratio",
which is forthcoming in the International Review of
Economics and Finance.



Notes

1. It is satisfied because the traditional Sharpe ratio criterion
requires that the return to each alternative be uncorrelated
with the return to whatever else is in our portfolio, and we
have constructed our alternatives so that there is nothing
else in our portfolio. The required zero-correlation condition
is therefore automatically satisfied.



References

Dowd, Kevin (2000) "An Improved Sharpe Ratio."
Forthcoming, International Review of Economics and
Finance.

Sharpe, William F. (1966) "Mutual Fund Performance."
Journal of Business 39 (January), Supplement on Security
Prices, pp. 119-38.

Sharpe, William F. (1994) "The Sharpe Ratio." Journal of
Portfolio Management, Fall, pp. 49-58.



noch ein Auszug:


The Sharpe Ratio is related to the annualized rate of return and the
annualized standard deviation of returns. That said, the calculations
can be based upon sampling the equity curve at any fixed interval -
days, weeks, months, calendar quarters, years, etc. (Sampling monthly
is not strictly fixed intervals because the number of trading days in
a month varies a bit.)

If you used weekly samples (neglecting compounding) you would
multiply the average weekly return my 52 and multiply the standard
deviation of weekly returns by the square root of 52 to get the
annualized values for each quantity. If you used monthly returns, the
corresponding numbers would be 12 and the square root of 12.

The annualized values should be about the same no matter how
frequently you take the samples. In theory, they will be independent
of how frequently you take samples if the returns have a "normal"
(Gaussian) distribution. In practice, returns tend to not quite be
"normal" but are a little narrower in the middle and have fatter than
normal "tails". The attached GIF picture shows this clearly. This is
a plot of the weekly returns of a futures trading system. The red
curve is the best-fit "normal" distribution.

I try to sample frequently enough to get at least 30 samples. So
weekly samples would work well for 30 to 100 weeks of trades; daily
samples would work well for 30 to 100 days of trades, etc.

I find that the Sharpe Ratio is the best single measure of the worth
of a trading system or the performance of a money manager or of the
performance of a mutual fund. It is also the only valid way of
comparing the results of using a trading system vs. buy/hold. The
Morningstar web site lists the Sharpe Ratio of mutual funds but you
have to search for it.

Continued in Part II to follow:


Continued from part I

--------

The formula for Sharpe Ratio is:

Sharpe Ratio = Excess Annualized Return /
Annualized Standard Deviation of Returns

The Excess Annualized Return is the return you get for assuming risk.
If you trade stocks, the Excess Annualized Return is the Annualized
Return on your beginning account equity less the return you could
have gotten by investing in a risk-free investment (usually taken as
T-Bills). I usually use 5% for the T-Bill rate but it does vary a
little.

If you trade futures the Excess Annualized Return is the rate of
return on the amount of margin you have on deposit with your broker.
It also depends upon whether you are getting interest on the margin
on deposit with your broker. If your broker lets you invest the
margin in T-Bills, the Excess Annualized Return would be the excess
you get over the T-Bill rate. If your broker pays you no interest on
your margin deposit, the Excess Annualized Return is the actual
annualized return you achieve by trading.

If you trade a fixed number of contracts and withdraw the profits,
you get no compounding of returns. If you scale up the size of your
trades as your profits accumulate, you will get compounding and in
that case you would sample the logarithm of your account value
(instead of the actual account value) since you would ideally expect
the account value to grow exponentially.

A Sharpe Ratio of 1.0 is considered "pretty good". So with a return
of 20% per year trading stocks and a T-Bill rate of 5%, if the
Annualized Standard Deviation = 15%, the Sharpe Ratio will be:

(20% - 5%) / 15% = 1.0

Remembering that with a normal distribution, in about two thirds of
the years, your rate of return will be within one standard
deviation of the average. So two thirds of the years, your rate of
return will be between 5% (20% - 15%) and 35% (20% + 15%). That means
one sixth of the years the rate of return will be below 5% and one
sixth of the years it will be above 35%. So, with a Sharpe Ratio of
1.0, one out of every six years we will make a lower return than we
could have made with T-Bills.

This is true regardless of how many contracts you trade. If you trade
more contracts, your average return will be higher and your standard
deviation of returns will be higher but the Sharpe Ratio you measure
will stay the same. So you would still expect to have one year out of
six where you made less than T-Bills. The Sharpe Ratio depends upon
the combination of the trading system and the market but NOT upon the
number of contracts you trade.

Investing in an S&P500 index fund over the past five years
("buy/hold") had a Sharpe Ratio of about one.

Things improve dramatically with higher Sharpe Ratios. With a Sharpe
Ratio of 2, you beat T-Bills about 97.5% of the years. That means
2.5% of the years you make less than T-Bills which is one year out of
every 40. With a Sharpe Ratio of 3, it means you beat T-Bills all
except one year out of every 200 years! (These calculations assume a
"normal" distribution which we know is not quite right but you get
the idea.)

A "decent" trading system will have a Sharpe Ratio of at least 2. I
usually shoot for at least 3. My best ones are over 5 and I have seen
values as high as 10 for really great systems.

The Sharpe Ratio reported by TradeStation and by Future Truth and
several others does not seem to be calculated correctly so be careful.
I have found that many people who quote their Sharpe Ratios do not
really understand it or how to calculate it.

The Sharpe Ratio was named for Prof. William Sharpe who was one of
three people who shared the Nobel Prize in Economics in 1990 for his
contributions to what is now called "Modern Portfolio Theory". He is
now a Professor at Stanford and has a lot of interesting papers on
his web site at .

The Sharpe Ratio has one theoretical flaw - its value does not depend
upon the sequence of returns. As an example, if all the losing trades
occurred first followed by all the winning trades, the measured
Sharpe Ratio would be the same as had all trades occurred randomly.
This flaw is mostly theoretical since it hardly ever is a factor in
real testing but there have been various attempts at fixing it.

The first was in Tushar Chande s "Beyond Technical Analysis" (ISBN
0-471-16188-. Chapter 6 of the book is dedicated to "Equity Curve
Analysis" and describes an approach based upon using the "standard
error" calculation:

> He defines a "risk return ratio" as equal to slope/standard error.
This
measure is similar but is not scaled properly to be independent of
the
time or price scales so it is difficult to compare different
systems.

The second was in an article by Lars Kester "Measuring System
Performance" (Technical Analysis of Stocks and Commodities, March
1996, pages 46-50). His approach, called the K-Ratio, is similar to
Chande s but with some changes:

> He scales the result by the number of observations, which he
assumes are days, but the TradeStation program in the article
uses trades as the proxy for observations which gives a
different result. It still has no absolute measure of goodness
as does the Sharpe Ratio.

For some time, I have used an improved version of the Sharpe Ratio
(which I have modestly called the F-Ratio or Fulks-Ratio) that I
think fixes all of these issues. I will publish it when I get some
time.

But in practice the Sharpe Ratio gives satisfactory results in almost
all cases.

Bob Fulks

RE: Buchempfehlung für Riskkennzahlen in Performancereport in TS??

Danke schon bestellt bei
www.numa.com

RE: Sharpe Ratio

super !!!

Hast noch mehr davon???

Danke das ist der zentralste Punkt für ein gutes HS, und weniger den Wunderwuzzi Indikator zu finden!!!!

RE: Sharpe Ratio

habe ich mehr wovon? Sharp Ratio Sachen??


Bitte zu Ende lesen, da Code vorhanden ist.

viel Spaß damit.

Jim

Bob Fulkes writes of Sharpe ratios of mechanical systems.

Why not disuss the Sharpe ratios of CTA funds such as
John Henry s, David Druz s, and so forth? They are
100% mechanical, they have a proven track record
(audited, to boot), they have actually made money for
clients as well as themselves.

It is reasonable to expect that the very best Sharpe
ratios are produced by the very best CTA funds -- they
have the most experience, the most market-battle-tested
savvy, and (very importantly) the largest research
budgets to investigate the widest possible spectrum
of trading system ideas.

Go ahead and look. You ll find that CTA s, even the
best of the best, the ones who test out EVERYTHING,
have a Sharpe ratio less than 1.0.

There are plenty of CTA s reading this list and
indeed reading this very message. These CTA s are
tracked by a variety of Managed Futures advisory
services, some in traditional ink-and-paper print
media, some on the web, some doing both. I will
guarantee you that none of these CTAs will respond
with a message, "Go look at such-and-such website
containing my audited results, you will see that
I achieved a Sharpe ratio greater than 3 for five
straight years." No way, Jose.

Mark Brown is a CTA, he advises a managed futures
fund. Go look up his Sharpe Ratio to see what is
actually possible in the real world. See if he
routinely achieves 3 or greater. (answer: no).
See if he even hits a Sharpe Ratio of 1 (answer: no).
This doesn t necessarily mean Mark Brown
is a poor trader, it means that (sharpe ratio > 1)
is a poorly chosen threshold-of-acceptability for
the real world we actually live and trade in.

Get used to it: what can actually be realized
using actual trades and actual fills and actual
markets, is a Sharpe ratio slightly less than 1.
Not 3, not 3-to-5, not greater-than-5. Less than 1.
That s the bad news. The good news is, you can
make >100% profits per year, even with a Sharpe
ratio less than 1. Larry Williams proved it.
Richard Dennis and the Turtles proved it. Michelle
Williams proved it. You and $395 worth of Pinnacle
Data, and $3000 worth of Trading Recipes software
can prove it too.

--
Mark Johnson




Weiter.......


Attached is a ELA written by Bob Fulkes, with the function outline
below. It
calculates the Sharpe Ratio as a function to be used in an
indicator...to be
used in conjunction with a system. I find it to be very useful and I
want to
thank Bob for it.

{Function: SharpeRatio}

{ *******************************************************************

Function : SharpeRatio

Last Edit : 11/24/98

Provided By : Bob Fulks

Description : This function calculates and returns the Sharpe Ratio
of a series of account values. It samples the series of values
on a yearly, quarterly, monthly, weekly, or daily basis as
determined by an input. It also calculates average return and
standard deviation. It prints the results in a form suitable for
importing into an Excel spreadsheet for plotting.

Inputs:
Mode - Sampling period (0=yearly, 1=quarterly, 2=monthly,
3=weekly, 4=daily
NetValue - The series of values to be sampled. It should be
equal to the beginning equity plus accumulated net profits.
Periods - The number of yearly, quarterly, etc., periods to
include in the calculation. If this value is zero, the
function will use all periods up to a maximum of 1500.
PrntMode:
zero - Print one line summary only on last bar
> zero - Print values as stored in array plus summary
< zero - Do not print anything
Futures:
TRUE - For futures trading (Sharpe = Ave / SDev)
FALSE - For Stocks (Sharpe = (Ave - 5) / SDev)

Method: The function samples the value of the trading account at
periodic intervals, calculates returns in each period, then
calculates the average and standard deviation of returns and
annualizes them. It then calculates to Sharpe Ratio as noted
above.

Assumptions: The usage for stocks assumes a constant value of 5%
for the risk-free return (T-Bill interest rate). This is a good
assumption for recent times but may be incorrect for the distant
past. The Sharpe Ratio is independent of the sampling interval
if the returns are normally distributed. Returns are typically
not strictly normally distributed so the sampling interval will
affect the results somewhat. There should be more than about 25
samples to get reasonable accuracy so use daily samples for 1
to 6 months of trades, weekly samples for 6 months to 24 months
of trades, etc.


1998 Robert G. Fulks, All rights reserved.

********************************************************************}

Input: Mode(NumericSimple),
{0=yearly, 1=quarterly, 2=monthly, 3=weekly, 4=daily}
NetValue(NumericSimple),
{Net value of account = Beginning Equity + NetProfit}
Periods(NumericSimple),
{Number of periods to use in calculation, zero = all}
PrntMode(NumericSimple),
{0 = print summary, 1 = include detail, -1 = don t print}
Futures(TrueFalse);
{TRUE for Futures, FALSE for Stocks}

Vars: Index(0), {Index used to index Return array}
SIndex(0), {Index used to sum Return array}
LNetVal(0), {NetValue at end of previous period}
LClose(0), {Close at end of previous period}
YClose(0), {Close at end of previous bar}
Size(0), {Sixe of data to be stored in array}
ILast(0), {Number of entries in array}
Ave(0), {Average return}
ASum(0), {Used to calc Average}
SSum(0), {Used to calc Standard Deviation}
SDev(0), {Standard Deviation}
SDMult(0), {Multiplier to annualize Standard Deviation}
Mo(0), {Month for bar}
MP(0), {MarketPosition}
MP0), {MarketPosition flag becomes 1 on first trade}
YMo(0), {Month for previous bar}
Yr(-99), {Year for bar}
YYr(0), {Year for previous bar}
YDate(0), {Date for previous bar}
AvMult(0), {Multiplier to annualize Average}
NetVal(0), {NetValue series}
YNetVal(0), {Netval for previous bar}
Active(FALSE), {False for first calc then true thereafter}
Record(FALSE), {Flag to trigger calculation at end of period}
Summary(FALSE), {Flag set if summary printed}
StDate(0), {Start date}
Sharpe(0); {Sharpe Ratio}

Array: Return[1500](0); {Table of returns as a percent}

Size = iff(Periods > 0, Periods, 1500);
Size = MinList(Size, 1500);
NetVal = Netvalue;
Mo = Month(Date);
Yr = Year(Date);

{This determines marketposition in either systems or indicators}
if MarketPosition <> 0 then
MP = MarketPosition
else
MP = I_MarketPosition;

MPX = iff(MP <> 0, 1, MPX);

Condition1 = Mo = 1 or Mo = 4 or Mo = 7 or Mo = 10;

begin

{Initialize for yearly}

if Mode = 0 and Yr <> YYr then begin
SDMult = 1;
AvMult = 1;
Record = TRUE;
end;

{Initialize for quarterly}

if Mode = 1 and Mo <> YMo and Condition1 then begin
SDMult = 2;
AvMult = 4;
Record = TRUE;
end;

{Initialize for monthly}

if Mode = 2 and Mo <> YMo then begin
SDMult = SquareRoot(12);
AvMult = 12;
Record = TRUE;
end;

{Initialize for weekly}

if Mode = 3 and DayOfWeek(Date) < DayOfWeek(YDate) then begin
SDMult = SquareRoot(52);
AvMult = 52;
Record = TRUE;
end;

{Initialize for daily}

if Mode = 4 and Date <> YDate then begin
SDMult = SquareRoot(253);
AvMult = 253;
Record = TRUE;
end;
end;

{Action if new year, quarter, month, week, or day}

if Record = TRUE then begin
if Active = TRUE then begin
{Each time except first time}
begin
ILast = ILast + 1;
if LNetVal <> 0 then Value1 = YNetVal / LNetVal;
if Value1 > 0 then Return[Index] = 100 * Log(Value1);
if PrntMode > 0 then Print(Index:5:0, Date:7:0, YClose:6:2,
LClose:6:2, YNetVal:7:0, LNetVal:7:0, Return[Index]:4:2);
Index = Mod(Index + 1, Size);
end;
end else
{First time only after initial position}
if MPX > 0 then begin
Active = TRUE;
StDate = Date;
if PrntMode > 0 then Print(Index:5:0, Date:7:0, YClose:6:2,
LClose:6:2, YNetVal:7:0, LNetVal:7:0, Return[Index]:4:2);
end;

LClose = YClose;
LNetVal = YNetVal;
Record = FALSE;
end;

{Calculate and print summary}

if Active = TRUE and Summary = FALSE and
(LastBarOnChart or ILast >= Size) then begin

{Calculate average return in period}
Summary = TRUE;
ASum = 0;
ILast = MinList(Size, ILast);
for SIndex = 0 to ILast - 1 begin
ASum = ASum + Return[SIndex];
end;
Ave = ASum / ILast;

{Calculate annualized standard deviation}
SSum = 0;
for SIndex = 0 to ILast - 1 begin
SSum = SSum + Square(Return[SIndex] - Ave);
end;
SDev = SDMult * SquareRoot(SSum / ILast);

{Annualize average}
Ave = AvMult * Ave;

{Convert back to ratios from logarithms}
SDev = 100 * (ExpValue(SDev / 100) - 1);
Ave = 100 * (ExpValue(Ave / 100) - 1);

{Calculate Sharpe Ratio}
if SDev <> 0 then begin
if Futures then
Sharpe = Ave / SDev
else
Sharpe = (Ave - 5) / SDev;
end;

if PrntMode >= 0 then
Print( ",", StDate:6:0, ",", ILast:6:0, ",", SDev:6:1, "%,", Ave:6:1,
"%,",
Sharpe:3:2, ", ",GetSymbolName, ",");

end;

{Print(Date:6:0, NetVal, Sharpe:4:2, MP:2:0, Active);}

YMo = Mo;
YYr = Yr;
YDate = Date;
YClose = Close;
YNetVal = NetVal;

SharpeRatio = Sharpe;

RE: Sharpe Ratio noch was....

Sharp ist ein Messgerate, aber ein Ergebnis muß mann schon irgendwie erst produzieren.
Ich bin aber einverstanden, daß es nicht unbedingt auf dem Superindikator ankommt.

grüße,

Jim

RE: Buchempfehlung für Riskkennzahlen in Performancereport in TS??

Rina hat ein pdf File veröffentlicht mit dem Titel: "TS2000_PerformanceReport.PDF".

erklärt die Kennzahlen einigermaßen.
Gruß
Robert