Financial Engineering and Trading

[boredengr]

I just got to know that a field like FE exists. I attempted reading a book and liked the Math behind (Math was my first crush and my first love). I am planning on reading up a lot on this field. It looks very cool to me.
Now, I am not looking for a degree or a career in FE. I want to find out how much this will help me in trading myself. Obviously, I am not expecting FE to be black magic. But, overall, will it increase the returns on your own portfolio? If so, any ballpark figures?

thanks

 

[Suman]

I have been trading full time for four years now. There is so much to learn, and so much to trade :D. I am working twowards quantifying few aspects of market behavior. Like the last leg of a move is more noisy, also caught as oscillator divergence in TA.
Again looking here and there how QA/FE may improve my trading :sos:

 

[bigbadwolf]

But, overall, will it increase the returns on your own portfolio?

The jury's still out on this question. By the way, do you mean speculating or investing?

 

[woody]

I think it will depend on the type of trading you are doing. TA and FE are different in my mind. You don't need to know stochastic calculus to use the word 'stochastics.' If you plan to use charts and backtesting and other technical analysis, you can focus your studies on trading-specific math. If you want to understand volatility modeling to hedge a natural gas swing contract, then you might need some FE.

 

[Suman]

Woody, what all (and exactly) does the trading-specific math encompasses? I have an idea that it helps in understanding market behavior while designing strategies. BTW I prefer tape reading, the stuff that Richard Wyckoff and Jesse Livermore talked about, than charts for my trading. I am in final level for CMT. Thanks.

 

[woody]

Trading-specific math is probably a dumb way to put it. Trading takes lots of forms. If the distinction is between TA and fundamentals, I imagine the TA'ist would use stats, time series analysis, regression, Excel/VBA, SAS, R. This is where I'd start if I were trading. Would I need advanced probability, real analysis, stochastic calculus, finite difference methods, Monte Carlo simulation, PDE? Or would I need to know how to build an algorithm that executes in C++ with the fewest operations? Not sure.

But FE knowledge is helpful no matter what IMO. A deeper understanding of how things work (if we are to believe that this is what we get from studying FE) can only help.

 

[writankar]

Derivatives Trading

hi all,
I am an EEE developing software for the last 3+ years. very recently, i got a chance to shift over to Derivatives Trading on the international market. it would be great if somebody out here could throw some light on what the job is all about. looking forward to hearing from you guys on this.

cheers

 

[Suman]

Maybe describing my day trading methodology (NASDAQ and NYSE) would be relevant.

Tape Reading:
1. The no. and size of new orders v/s the insuing price moves help me calculate the strength of upcoming waves.
2. By amount of orders being cancelled and orders that stay (execute) help me filter noise particularly in first half hr.
3. By the size changes sorted by market makers helps in finding 'vacuum' ponts where price flow stops for a while.. useful in execution.
4. Rate of new Asks v/s new Bids indicates reversal points as price fluctuates.
5. Sometimes there is a large stale order which also holds (or spikes) price for a while as scalpers try to exit on it.
6. By grouping different market participants to the order of their reaction time to price change helps me gauge sentiment of upcoming moves.
Overall it also helps me segregate arbitrague/scalping driven volumes to speculative volumes. I heard about some hedge funds using order book based strategies, but seek real knowledge about that.

Technical Analysis:
1. Attributes of different phase of a trend
2. Crowd panic versus manipulated momentum
3. Congestion zone versus accumulation/distribution zone.
I find statistics particulary useful. All programming that I did was for Metastock for filters/screeners. Few trader friends tell me that they find MCS particularly useful for backtesting.

I am in India and I averaged 15k USD p.m. in 2007. Here living costs are 1/10 compared to U.S. so I make decent living. I want to grow slowly and steadily and shall prefer to start with a small firm in NSE rather than working my way up a job. So currently looking for all professional course that may help me. Thanks.

 

[scmath]

A Variant Trading View

This is a link to a very intriguing article questioning traditional assumptions on math as it relates to trading.

Interested in hearing thoughts on it.

The Write Investment

SC

 

[bigbadwolf]

Interested in hearing thoughts on it.

An excerpt:

So then stats, probabilities, and the like, simply quantify the most ubiquitous element of human nature, emotions. This suggests that equations, assessments, and even math itself is deeply rooted in emotions, for without such they cannot noticeably exist.

The writer should qualify this assertion and state that this is only in areas like finance and economics, where human actions create their own artificial reality. In physics, for example, we like to think that emotions are incidental, and our mathematics helps to explain and predict objective phenomena independent of us. Thus, Maxwell's Laws should hold whether we are or are not around.

In finance and economics, we only have "phenomenological theories": theories which purport to explain various phenomena without claiming to have dug out root causes on the basis of which axiomatic theories can be constructed. In Newtonian physics, a root cause is the notion of "force," which in conjunction with the three laws, gives us the science of mechanics. For electrodynamics, it's the concept of "field." Epistemologically, these theories are at a different level altogether than much of what is being peddled in finance -- though the mathematical garb may be the same; the latter are merely phenemenological, in the same way the Ptolemaic theory was in astronomy. In addition, in finance, the theries have weak predictive power. In physics, the predictive power is usually with decimal point accuracy.

One good point the writer suggests (or seems to) is to mathematise crowd psychology -- if it's possible. Indeed, he contends that any successful theory in the area will be doing precisely this. I think I should reiterate: finance and economics are artificially engineered realities, whee human actions and emotions are key ingredients (besides the formal rules) in determining the character of that reality. Any theory for these artificial worlds that doesn't deal with these human inputs will be a failure.