This is sort of like asking how physics and chemistry are used in manufacturing widgets... an impossibly broad question unless you provide some guidance about what exactly you're trying to do. If you already have a profitable discretionary trading system, the math of it all is minimally relevant. You need to have a basic, broad-brush, practical (as opposed to theoretical) understanding of concepts like variance, probability and kurtosis/skewness. You need to understand how the various properties of your trading results, such as win rate and risk:reward ratio, interact to produce an equity curve over time. You need to have an awareness of 'tail risks' (unlikely but catastrophic events) and long-term theoretical vs. short-term realized outcomes. Beyond that, unless you are already well-versed in the relevant mathematics and skilled at statistical analysis in other applications, I wouldn't bother with it. Successful discretionary traders are as a rule incorporating far more information at a far more nuanced level, as a function of training and experience, than any simple statistical study will reveal. You're far more likely to enhance your edge by working to further improve your existing strengths and skill set.
In addition to each of the ways described by various contributors above, statistics also comes into trading as follows. A traded market differs from a mechanical system. Describing the latterâs current behavior, or projecting this behavior into the future, is the realm of natural science (e.g. Physics). If the system is in a known physical state at a given point in space-time, natural science can be used deterministically and with certainty (apart from Heisenberg uncertainty!) to calculate/predict its state (or possible range of states) at another point. A traded market is different; in addition to whatever âphysicalâ parameters describe its state at any point in time (e.g. liquidity, price, change in price, SMA(30), MACD, etc â¦), the bias/sentiment of each participant trading that market is arguably the most important factor to determine how that market will trade. And the bias/sentiment of all participants is unknown (or at best is known imperfectly), and is evolving. (n.b. the current price just reflects a time-lagged measure of the aggregate bias/sentiment, but does not provide any deterministic means to ascertain how the bias/sentiment will evolve). Because the determinism of natural science does not arise easily in traded markets (two markets in exactly the same âphysicalâ state could evolve in totally different directions because the prevailing bias/sentiment is different in the two cases), the determinism needs to be replaced by a probabilistic approach. And the use of probabilities leads naturally into the use of statistical methods.
Advanced stats is needed for derivative valuations, lots of risk management techniques, and return volatility estimates.
That's the thing, I'm not really strong in math. I can calculate percentages, quotients and factors almost instantaneously but it doesn't really go any further than that. I do want to strengthen my math skills though.
What you are describing is just numeracy; Try taking one of those open courses things to get some real math work?
Just found the Kahn Academy after I type my last post. They teach those things free. Gonna check that out.
That's quite a compliment... From someone who actually named a trading firm Random Capital Management. Have you ever hot tubbed with Nassim Taleb?
That's not me & nah, no hot tubbing with Taleb. A bit icky for this punter - but don't let that stop you
all the money is made when the move comes along and totally wipes out all the past statistics then the statistics are reset, and everybody just starts over only, some at an increased account value, and others at a reduced account value