Questions tagged [best-practices]
A "best practice" is a method or process that practitioners recognize (usually through experience and research) as being more effective at getting the job done than other methods (or processes).
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Calculating TWAP for Transaction Cost Analysis
I am looking to perform TCA of several orders.
I would normally look to calculate an order's VWAP/ TWAP only relative to the executions of that order.
So for instance, calculating an order's TWAP (...
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Potential problems with trying to apply reinforcement learning to algorithmic trading
I have been attempting to develop an algorithmic trading agent for a single asset pair and upon researching, it seems as if, in theory, reinforcement learning would be a natural way to approach this ...
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Is there a common way that level 2 and time & sales data are analyzed together?
Let's say that for a single asset, we have a data stream from which we receive both level 2 order book updates (price level/quantity updates) as well as time & sales updates (grouped recent trades)...
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Effect of back-transforming forecasted mean of log returns to get forecasted mean of price
When trying to forecast time series, say forecasting the level of a stock index so we can forecast the future values of an option, it tends to be helpful to analyze the log returns versus the original ...
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Benchmark Model for Path-Dependant Monte Carlo Simulations?
As part of my research for my masters thesis, I'm testing out the effectiveness of some different models in Monte Carlo simulations for path dependant options.
I will be attempting a model-free ...
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How do you hedge volatility risk?
Suppose I model an asset $S_1(t)$ under a stochastic volatility model. To price an option on $S_1$, I must assume the existence of an asset $S_2$ that is used to hedge against changes in the ...
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Is there an Ops Risk in being short a bond on the redemption date?
I am trying to understand whether everyone needs to be long or flat when a bond is redeemed, or being short a bond at that time is also not an issue
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How do traders hedge against “tail side risk” in practice?
In a recent CNBC interview, Black Swan author Nassim Nicholas Taleb gave a categorical advice about investing in the Corona period. “It is very unwise to do any form of investment without some form of ...
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Practical precision for Options Pricing
When pricing options, especially in the theoretical literature getting high precision, say up to 8 decimal places is always a competitive goal. Though realistically in a practical setting is such ...
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Passage from dates ranges to real numbers in modelling : which market practice?
Let's say I model a 6M forward Libor rate as a process $(L^1_t)_t$ that's a diffusion, with in view a Monte-Carlo (MC) pricing of some product. At some point I will have real life dates $T_i$'s that I ...
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What models / methods are used in practice in derivative pricing?
I wrote my bachelor thesis about European Option Pricing under Stochastic Volatility and Jump Diffusion and am now near the end of my MSc in Quant Finance. As i want to write a "potential job"-...
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FX Modeling references
I would like to have some sugestions of reference books on FX modeling with strong mathematical approach, preferably combined with market pratictioner quant perspective.
All sugesting are welcome! ...
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Extrapolating SVI
In his paper Gatheral presents the following parametrization of the implied total variance $w(k,T) = \sigma_{BS}(k,T)^2T$
$$ w(k) = a + b\{\rho (k-m) + \sqrt{(k-m)^2 + \sigma^2} \}.$$
Assuming that ...
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Volatility Surface Constituents, do's and dont's
Recently I have been working a lot with implied volatility and volatility surfaces.
The basic idea is easy to follow:
1) Gather market prices of options at different (Strike,Expiry)
2) Calculate ...
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What's the practical difference between the Johansen vs Engle-Granger tests for cointegration?
For the two-variable case, what are the practical differences between using the Engle-Granger procedure versus the Johansen test for cointegration? Is one universally more powerful than the other? ...
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Divergent or Convergent Strategies? Which is the way to go?
Consider first the simple convergent strategy to invest some amount $X$ in a game, if you win you simply take the winnings and keep playing a subsequent game. In the case of a loss, you believe in ...
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Approaches to check/validate the output of an optimization algorithm
Let's say we want to optimize the a function $f(x_1,\dots, x_n)$ with $(x_1, \dots , x_n) \in \mathbb{D}^n$. For the sake of simplicity let $\mathbb{D}^n$ be the unit sphere.
We chose an optimization ...
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Practical implementation of Least Squares Monte Carlo (tweaks and pittfalls)
The Longstaff-Schwartz LSM approach is nowadays ubiquitous(at least in the academic literature) in pricing path dependant derivatives. Up to now I have mostly worked with lattice methods. My ...
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Interpretation of cross-correlation matrix when one sample distribution is not normal
I am looking at the variance of (log) price changes in securities vs. the amount of social media discussion about them. I'm not interested in building a model. I'm just looking to see if there is a ...
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Industry convention to track trading performance against market indices?
I come from a programming background and not am no quant by career so this is probably a newbie question for you guys. I have written some code to pull daily closing values for market indices (DOW/...
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What is the denominator in calculating daily range as a percentage?
Assume a stock had an open of \$100 and a close of \$102. If the high of the day was \$103 and the low was \$99, the daily range is obviously \$4. What is the best way to express the daily range in ...
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How should you manage lot sizes in this situation?
Imagine that prior to entering the market you know beforehand the profit factor of similar situations.
For example:
...
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Why are GARCH models used to forecast volatility if residuals are often correlated?
The answers to this question on forecast assessment suggest that if the sequence of residuals from the forecast are not properly independent, then the model is missing something and further changes ...
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How are risk management practices applied to ML/AI-based automated trading systems
A potential issue with automated trading systems, that are based on Machine Learning (ML) and/or Artificial Intelligence (AI), is the difficulty of assessing the risk of a trade. An ML/AI algorithm ...
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