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Jul
19
comment How to look for fractals/harmonics patterns in time series?
Depending on what you look to use such system for one of my previous answers may be of help: quant.stackexchange.com/questions/8242/multi-fractals-models
Jul
19
comment How to look for fractals/harmonics patterns in time series?
Asking for book recommendations is of course fine, asking others to pretty much guide you through the construction, well, pretty much delivering you the setup on a silver platter is maybe asking for a little too much. Maybe that is not your intention, it just comes across to me as such. Maybe you could rephrase the question?
Jul
19
comment Question on an approximation in pricing formula
I agree with the assumption QuantIbex stated at the very end. Not knowing the text but if the authors did not elaborate why they made such assumption then I find it a pretty weak treatise and without specific reasons (especially without establishing a relationship between sigma, mu, and t) such assumption could potentially even be wrong.
Jul
19
comment How to look for fractals/harmonics patterns in time series?
I find your question way too broad and open ended to answer. It sounds like you want others to deliver you the done deal to plug in. Maybe you can focus on a more specific issue and ask more targeted questions?
Jul
19
comment DCF Zero Coupon Bond
@jessica, does that answer your question?
Jul
19
comment 30360 Daycount Count Convention to find NPV for Bonds
@jessica, does that answer your question?
Jul
19
comment DCF Zero Coupon Bond
It has to do with what compounding frequency you apply. If you compound annually then the 360 term would drop out. Please see my edited answer here: quant.stackexchange.com/questions/8497/…
Jul
19
comment 30360 Daycount Count Convention to find NPV for Bonds
Please see my edit. The day count convention dictates the 'T', the time fraction applied in the discount factor function. It makes the assumption here that months are of 30 day length and years of 360 days.
Jul
19
comment 30360 Daycount Count Convention to find NPV for Bonds
@jessica, then you get 360 days just as 30/360 suggests. Re coupon payment frequencies you made no mention of that in your question and nor does it matter for your actual problem. You look to discount a future cash flow, whether it be a semi-annually paid cash flow or annually paid cash flow. The formula to discount any cash flow, using 30/360 convention, is as stated above in my answer.
Jul
19
comment Total number of currency transactions
Not sure how you derive value from such estimate. But I am unable to give you such figures because I never thought about it as I never expected such numbers add value
Jul
19
comment fetch from yahoo! finance database - varying number of ticks
I think rather than it being a MATLAB issue (all queries are identical) it may have to do with yahoo data storage or possible the fact that Japan is a week off the grid during golden week (may). It should be easy for you to verify which weeks are missing in the shorter time series.
Jul
18
comment How to tune Kalman filter's parameter?
I did but currently not. I work on something similar than particle filters but the algorithms are very expensive computationally. Digging into Cuda GPU programming in order to ease some matrix computations. Why, do you?
Jul
15
comment Am I reading this correctly? probability way too small with BS model
Nice answer, practical, concise and to the point. +1 for this!!!
Jul
15
comment Tools/R code for predicting Dragon-Kings
By the way, I did watch the TED speech and felt it was a waste of time, why: All his reasons of why he can predict extreme events are accurate, however, the exact same variable states occur in countless market observations that do not lead to extreme events (increasing autocorrelation, increasing variance, increases in cross-correlations with external factors...). So, it again comes down to the same guy screaming "extreme event ahead" who screamed 20 times before and was proven incorrect. I did not come across his name forecasting any past extreme events. How come?
Jul
15
comment Tools/R code for predicting Dragon-Kings
@vonjd, what do you mean with "encrypted forecasts" and why you encrypt something, archive it and then decrypt it? I am not falling victim to a catch-the-fool type of post right now, am I? ;-) (I generally highly value your posts and read them with much interest but you have be gotten completely lost here).
Jul
14
comment Tools/R code for predicting Dragon-Kings
I flipped through the paper and found it to be utter "humbug". Nowhere have the authors established nor presented a statistical study that would support that there is any reliable way to forecast extreme events. While I disagree with Taleb in many ways I would say he is spot on in claiming black swans cannot be predicted but only subsequently managed. No earthquake (as of today) can be reliably predicted nor a financial crisis. For each guy who claimed he pinpointed the day the market put in a top there are 20 guys who did so before and got burned. But of course one should never stop dreaming
Jul
12
comment Non-intuitive correlation between S&P sector indexes and economic indicators
Economic indicators are either forward looking, coincident, or reflect historical data, thus correlations between an equity index and such indicators are a huge function of how you lag the indicators. By the way has it occurred to you that the lag itself is dynamic and changes unpredictably, meaning, the lag that produces the highest positive or negative correlation with a major equity index? Otherwise everyone would trade off such indicators. I can show you countless examples where higher NFPs went along with lower subsequent index returns. Call it "reality"...
Jul
10
comment Calculating most profitable arbitrage orders on multiple market with fixed and variable fees
that does not change the kind of algorithm you need to run the markets over. You need to include your all-in execution related costs and may find out that low volume will not push you over the "hurdle-rate", which may rank this particular arbitrage lower or even net-unprofitable.
Jul
10
comment Calculating most profitable arbitrage orders on multiple market with fixed and variable fees
Example: Market1(fixed fee: 1, variable fee: 2%, BBO: 105/107), Market2(fixed fee: 0.5, variable fee 1%, BBO: 98/100). Variable Fees -> Buy asset at M2 for (100 + 1) and sell to M1 for (105-2.1). PnL with fixed fees applied: (105-0.5) - (100+1). -> Apply same logic to all markets and chose the most profitable one.
Jul
10
comment Calculating most profitable arbitrage orders on multiple market with fixed and variable fees
I find your question slightly confusing. Why you need more than 2 markets to present an arbitrage opportunity, 2 or more are already sufficient. And why is it complicated to add in your execution related fees, whether stated as a percentage of notional traded or as fixed fee per trade?