Tag Archives: Sharpe ratio

Best Performing Forex Pair Should Hugely Increase Your Expected Return And Sharpe Ratio

Proper metrics under proper conditions

The first little bit talks about the combination. I have tested this on multiple time frames but usually find these 2 best performing currency pairs historically will give you highest expected rate of return and expected Sharpe as well.

Note that there is a gap of blackness in video so just wait to see the detailed analysis.

Do realize that this technique can be applied to any asset class universally.

Here was an interesting conversation of Youtube 

Hey Brian, Dofl here. I’m trying to get real-time stock data that would contain pre-market data/historical data. Basically I want to use my own personal scans, etc. Would you be able to recommend any data sources that I can use and parse with java? I know this is off topic of the video, but I really have been l looking for a while. TD Ameritrade seemed promising but unfortunately they aren’t active/don’t allow posting on their API forums, and as a result doesn’t work for me. The existing sources I’ve found on google seem to never have before/after market hours. I know that all the big companies/charting softwares have to get their data somewhere, would you happen to know? Thank you for your time!

good question. It depends on the type of broker where small ones use wholesale brokers. TD Ameritrade would be big enough to have their own network of clients. Most data may also come from  their own prime broker like Citi or Goldman if they provide liquidity.

I see, very interesting. The problem is, I’m trying to get the data so that I can parse it myself. Now, TD-Ameritrade offers an API, but I couldn’t get it to work. I’m not going to burden you and ask you to do a video on it, but I truly think that for us free-stock traders, who want not only to swing-trade, but to day-trade with an edge in the markets, we need that data. I’m really annoyed, because I know I can make the programs I need with my java skills, I just don’t have the data-sources, nor the 1000’s of dollars to throw away just yet lol

It sounds like you need direct market access which means you would need a large account e.g. 500K maybe. This would give you access to the exchanges but you would the to join the line first.

Thanks for reading

P.S. Don’t forget to ask about the offline course deal I have coming up? Once the courses are announced, I will not keep it at this deal!! 

The first little bit talks about the combination. I have tested this on multiple time frames but usually find these 2 best performing currency pairs historically will give you highest expected rate of return and expected Sharpe as well
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Combining best performing forex pair should hugely increase your expected return and Sharpe Ratio

Combining best performing forex pair should hugely increase your expected return and Sharpe Ratio

Proper metrics under proper conditions

The first little bit talks about the combination. I have tested this on multiple time frames but usually find these 2 best performing currency pairs historically will give you highest expected rate of return and expected Sharpe as well.

Note that there is a gap of blackness in video so just wait to see the detailed analysis.

Do realize that this technique can be applied to any asset class universally.

If you are interested in how the Portfolio Optimization, I have various videos that showcase this 

 

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When to use Sortino over Sharpe ratio

When to use Sortino over Sharpe ratio

You need to love Investopedia when you learn something new everyday

. Sharpe ratios are better at analyzing portfolios that have low volatility because the Sortino ratio won’t have enough data points to calculate downside deviation. This makes the Sortino ratio better when analyzing highly volatile portfolios.

Read more: http://www.investopedia.com/terms/s/sortinoratio.asp#ixzz3Yv5bFZYK

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PDF Red Rock research paper: Is there such thing better than a Sharpe Ratio for measuring your trading activity?

PDF Red Rock research paper: Is there such thing better than a Sharpe Ratio for measuring your trading activity?

This was just sent in by the NYC contact.

http://www.redrockcapital.com/assets/RedRock_Sortino_white_paper.pdf

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How to use performance metric like Sharpe Ratio to reduce your drawdown in your trading?

How to use performance metric like Sharpe Ratio to reduce your drawdown in your trading?

Again, thank to my NYC source for providing this

http://www.stat.cmu.edu/~abrock/algotrading/page9.html

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Here is my opinion of CAPM and Sharpe Ratio while you research your potential profitable quant trading strategy

Here is my opinion of CAPM and Sharpe Ratio while you research your potential profitable quant trading strategy

This came in from some one on my email list:
Question:
do you know much about capm or sharpe ration?
http://www.investinganswers.com/financial-dictionary/stock-valuation/capital-asset-pricing-model-capm-1125
I want to write my own sharpe ratio and was hoping someone can help clarify a few things

My response:

I am no expert but I do believe CAPM is really decent for finding beta. That is about it.

Sharpe ratio is an industry standard to find the performance on your trading strategies.

More info on the function from Matlab from:

http://www.mathworks.com/discovery/capm.html

http://www.mathworks.com/help/finance/sharpe.html

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Volatility weighting and volatility targeting improves Sharpe Ratio

Volatility weighting and volatility targeting improves Sharpe Ratio

There is increasing interest in risk-controlled investment strategies, such as volatility weighting and volatility targeting. However, surprisingly little has been done from a theoretical perspective in studying the relative dominance or optimality of volatility weighted strategies. I recently wrote a paper ( http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2008176 ) in which I provide a proof that volatility weighting over time increases the Sharpe or Information Ratio. The higher the degree of volatility smoothing achieved by volatility weighting, the higher the risk-adjusted performance. Our results apply to risky portfolios managed against a risk free or risky benchmark (so including alpha strategies) and to volatility targeting strategies. We provide an empirical illustration of our results. I welcome any comments or remarks on my paper or on this topic !
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2008176

papers.ssrn.com

 

==

Very interesting formalization of “market timing”. Two comments:

– The normalized return r=R/sig (i.e. the return divided by its standard deviation) can be non-unique because of capacity issues: as we take more and more risk “sig” in a given strategy with return “R”, the distribution of the return R varies in scale, but also in other features. This is a second order effect that kicks in only when the strategy/portfolio that generates R becomes large.

– In practice people look at the sample Sharpe ratio s_SR, defined over a period 1->T as the ratio of the sample mean divided by the sample standard deviation:
s_SR(1->T)=s_mean{R_t}/s_Sd{R_t}
Before the realization of the series of returns R_t from t=1 to t=T, s_SR is a random variable, whose features, such as expectation E{s_SR}, standard deviation Sd{s_SR}, etc., might be related in a non-trivial way to E{R_t}/Sd{R_t}, which is the subject of the above paper.

 

=–

Ad 1. Indeed, I can imagine that the distribution of the vol-targeted return r*_t = [ R_t / sig_t ] * V is different for different values of the vol-target V. The reason I see is that the full excess return is scaled, not only its deviation from its mean. So I guess that in addition to the variance component (which we want to target) there is a bias component which affects the distribution of the rescaled returns r*_t.
Another issue is that I limit myself to volatility as the risk measure. Vol-scaling will undoubtedly also affect downside risk and tail risk. That signifies a nice route for further research.
Ad 2. The population Sharpe Ratio is defined as the risk premium per unit volatility, which implies that numerator and denominator are estimated separately. But indeed the sample SR is a composite stochastic variable (i.e. the ratio of two variates). When evaluating a sample SR, the estimate can be subjected to a statictical test. (A good reference is “Performance Hypothesis Testing with the Sharpe Ratio” by Christoph Memmel in Finance Letters, 2003.)

I hope I have addressed your issues satisfactorily.

 

Last week I updated my volatility weighting paper (SSRN nr 2008176), addressing a.o. the issue above.
In April I also looked at the Fama-French momentum factor (data from French’s website) and found a doubling of the Sharpe Ratio after simple vol weighting. This is fully in line with the results on vol-weighting the momentum factor that are reported by Barrosso & Santa-Clara (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2041429). Over subperiods, I even found that vol weighting did turn negative Sharpe Ratios into positive ones !
It is well-known that momentum returns are negatively related to volatility. That vol weighting works so well for momentum may hence not come as a surprise. The timing effect (increasing positions when vol is low and returns tend to be positive, and vice versa) is substantial.

 

One question on Barrosso & Santa-Clara (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2041429)
The authors standardize the strategy by its recent unconditional sample standard deviation, i.e. calling w_t the weights that determine the strategy at time t and r_t the respective returns, they use the sample s.dev. of the recent series w_t’*r_t.
An alternative would be to use the conditional s.dev., or point-in-time s.dev, i.e. the sample s.dev. of w_T’*r_t, where the current weights w_T are hit by the past returns r_t.
Any reason pro/against either approach?

 

==

Just a small comment regarding the Memmel (2003) test for the Sharpe ratio that was mentioned earlier. The Memmel test is not robust against non-normality and/or GARCH effects. We know both of these are important in financial time-series. This is why it would be generally preferable to use the test I published with Mike Wolf:
Ledoit, O., and Wolf, M. (2008).
Robust performance hypothesis testing with the Sharpe ratio. (PDF, 302 KB)
Journal of Empirical Finance, 15, 850-859.

 

==

Addressing Attilio’s comment above : in their empirical analysis of volatility-weighting the Fama-French momentum factor (UMD), Barroso & Santa-Clara indeed use the past momentum series itself to gauge the volatility. An alternative would be, as Attilio describes, to take the historical point-in-time volatility of the *current* UMD portfolio.
In favor of the B&SC approach is that they measure the risk of momentum.
After all, generally speaking, when you would use the return history of the current momentum stocks (or portfolio), then this would not represent momentum risk since the current momentum stocks were not momentum stocks in the past. But since B&SC look back only 6 months, I doubt whether this would make a difference.
So I guess that when evaluating the use of the realized or the point-in-time volatility it is important to see whether the attribute you want to consider does change over the risk estimation interval or not. If it does change, I would use the realized returns on that attribute; if it does not, there’s not much difference. Would you agree ?
One complicating factor is that in a strategy you can have neutral positions and these neutral positions would lower the realized vol. At some point I would start feeling uncomfortable in using the actual series to estimate vol …..

 

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Learn Maximum number of intraday Sharpe ratio

Learn Maximum number of intraday Sharpe ratio

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Thanks for reading Bryan

 

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How to maxize your number intraday Sharpe ratio for highest potential profit

How to maxize your number intraday Sharpe ratio for highest potential profit

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Videos on algo strategy development course with Sharpe Ratio, Periodic rate of return, benchmarking, and Profits from limit orders

Videos on algo strategy development course with Sharpe Ratio, Periodic rate of return, benchmarking, and Profits from limit orders

 

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