Discover and read the best of Twitter Threads about #quants

Most recents (6)

There is a problem in the financial risk management and financial engineering profession, that #quants tend to overwhelm their customers (in-house staff or external parties) with mathematical informatics.
Big Data science and ML Machine learning dashboard analytics & traditional time series econometrics presented via the system screenshots or PDF sheets attached to emails could be more helpful for the telephone operator mindset traders and dealers, only if appropriately described
More information can at times backfire!
It tends to obfuscate the human mind, negatively impacts decisions and actions in real-time, and renders the decision support systems incapacitated with tech-savvy dipped acronyms, notations,& expressions.
Disseminating Communication risks
Read 15 tweets
The LTCM Crisis taught #Quants one thing in common.
Never trust the risk pricing/hedging models blindly.
The Black Scholes option model assumptions and the Value at Risk Metric both failed miserably.
The liquidity assumptions of the #VaR Model provided a false sense of security.
The most worrying thing is that if #LTCM which was a hedge fund managed by two @NobelPrize winners in Economics could not get things right, then what should one expect from humble risk practitioners like myself!?
imagine the amount of risk that is concealed by Black Box Models.
Always backtest and stress test your #risk models.
Not just the mathematical components, but also the semantics, the #hermeneutics, the syntax that is used for coding the automata, and the symbols which are shown on the analytical dashboard.
It is a big #CON industry at work!
Read 9 tweets
I remember starting my career as a junior derivatives dealer.
The first stupid question I asked was why currency dealers use par-curve yield curve rates to compute FX Swap points?
No "#boostrapping"?
The Chief Dealer/ Head of FX Linear and Cross Currency Rates was not pleased.
Actually asking stupid questions early on in our career helps.
Provided you have a tolerable boss who can entertain stupidity.
But, if you ask questions which threaten your reporting line, then you are cooked!
Done.
Find your next job asap.
My CRO - Chief Risk Officer, was a banker who didn't know maths and statistics.
The man was a nightmare proposition for the academically tuned young graduates
Poor chap begged me to not bring my work to him because he could not check it.
Read 6 tweets
I have met many mathematicians, #engineers, and #statisticians, from different countries, but, the ones that are graduates of #French and Belgian Universities are probably the best that I have come across.
What makes these countries so proficient when it comes to teaching #maths?
During the early 1990s, most of the #Quants and Financial Engineers who joined the Financial Services industry in the City of #London came from France.
French Mathematicians changed the way banking & asset mgmt was done.
Actuaries at @CityUniLondon dominated Insurance
Neither @LBS nor @LSEEcon contributed to the development of the #Quantitative Finance or #Actuarial Science Professional Cultures in the City.
The major contributors were @hwugradfutures and @CityUniLondon
To date, LBS does not teach Financial Engineering as a pathway
Read 6 tweets
1/ 🆕 at Quant's Perspective @ScalableCapDACH @ScalableCapital

Rolling Down the Yield Curve (by @ChrisAndData)

uk.scalable.capital/quants-perspec…

#quants #fintech

Thread 👇
2/ Upwards sloping yield curves can be explained by several yield curve theories, which imply different future yield curve trajectories. Rolling down the yield curve will maximize future returns when yield curves remain constant over time.
3/ We start of with an artificial scenario in terms of yield curve and forward rates (shown in the graphic). If we now want to invest money for 1 year, bonds of which maturity should we buy?
Read 10 tweets
The whole point of the ‘market’ -as we #Asutrians have been telling you for over a century- is that the prices formed by the countless interactions of our teeming humanity convey info of the best possible quality to help co-ordinate the most fruitful use of scarce resources 1/x
- the greater the nodes on that market network; the more individual needs and preferences expressed upon it, the better the solutions: the more enriched the ‘spontaneous order’ it throws up.
The scrambling of price signals by state lever-pullers is one evil we often discuss - 2/x
- what we don’t address often enough in financial markets (theoretically possessed of the densest and most widespread, most rapid, most frictionless networks of all) is the deadening effect of overconcentration and the move to oligopoly under which we are now suffering - 3/x
Read 11 tweets

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