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Questions tagged [quant-trading-strategies]

Quantitative trading strategies use quantitative signals and a set of predefined systematic rules to make trading decisions. Strategies operate within parameters based on historical analysis (backtesting) and real world market studies (forward testing). Strategies may be executed manually (by a human trader) or automatically (by a computer).

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Given assumptions around transaction costs (e.g., slippage, fees), and potentially downsampled tick or bar data, how can we derive the minimum holding period required for a strategy to be viable — ...
QMath's user avatar
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1 vote
2 answers
590 views

I am currently looking for some comprehensive books on commodities, particularly focusing on the power market. My goal is to better understand the various financial products involved, their pricing ...
Ethantr's user avatar
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1 vote
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Suppose you have $100 But you invest 10% of in in each investment with payoffs (multipliers). that are as follows; 1, 0.9, 2 Investing 10% into 1: ...
M4X_'s user avatar
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1 vote
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I have recently read the paper "Gamma Exposure (GEX), Quantifying hedge rebalancing in SPX options" by SqueezeMetrics (2017) and tried to implement it for NSE Nifty50 weekly options. The ...
Nikhil Arora's user avatar
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I am wondering how it work in big firms like Citadel Securities in market-making and HFT teams. You have a lot of different pods, and the number of markets where you can operate is small. Hence ...
ewfewqfrewdeeeee's user avatar
1 vote
1 answer
261 views

I am wondering how PFOF (Payment For Order Flow) works and why people say that hedge funds make wider spread using PFOF. If a client sends an order A then the broker is going to redirect that order to ...
frewgrewgew's user avatar
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A task I'm working on has the following problem definition: There are 2 provided time-series, an exchange rate (exch_rate) and a tradeable rate (executable_rate). You can assume that the ...
user3739400's user avatar
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0 answers
81 views

I am trying to improve a regular vol-control for a personal project based on t-2 ewma or std vol as it does not really perform any better in sharpe ratio than it's benchmark (S&P500). I am ...
Pira's user avatar
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I have trained a GARCH(1,1) model that does a decent job of forecasting volatility (for real-world stock price time-series). For "known" events such as earnings announcements one can ignore ...
Shreyans's user avatar
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When doing MM people in the industry say that most of the time they have a signal, which give them a faire value of the instrument and they quote around that. For RFQ it makes sense since there's no ...
autoregressive_monoid's user avatar
2 votes
1 answer
570 views

A lot of people working in the finance industry are saying that what makes finance hard is that the signal to noise ratio (SNR) is extremely low. I don't get what is precisely meant by that. How are ...
low_snr's user avatar
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0 votes
1 answer
440 views

I have a strategy that works in the backtests.. but it seems to me that it is not working in the real world.. Here is how i have backtested the strategy: I apply a specific strategy on all the stocks ...
Dhruv Agarwal's user avatar
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0 answers
156 views

When it comes to trading strategies I get the feeling that whenever I read about a strategy in a book or when I have view, all of that is already priced in and does not make a case for a good trading ...
sigma1988's user avatar
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2 votes
0 answers
164 views

I am evaluating the cumulative % return on a trading strategy that requires constant rebalance / scaling, but find it difficult to arrive at an intuitive and sensible method. Daily PnL & % Return ...
JosephDing's user avatar
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0 answers
78 views

When comparing realized swap rate volatility and implied ATM swaption volatilities, should one expect the shape across tenors of the implied volatility to be reflected in the realized and their level? ...
sigma1988's user avatar
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