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 ...
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Proof that you cannot beat a random walk
There is much speculation to what degree financial series are random (and what kind of randomness prevails).
I want to turn the question on its head and ask:
Is there a mathematical proof that ...
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6answers
2k views
Can social media be applied to algorithmic trading?
Can social media sites, like Twitter, be used to analyze financial markets for algorithmic trading? How much research has been done on this topic?
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5answers
1k views
What are the advantages of switching platforms/languages between strategy development and implementation?
I am interested in coding a medium frequency (trading over minutes to hours, holding for days to weeks) quantitative trading strategy and trading it with Interactive Brokers.
I have seen many people ...
9
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1answer
522 views
How to use macroeconomic indicators for long/short trading strategies?
I am trying to understand how to use macroeconomic data in my trading. I understand that using such data could be used to gauge an overall view of the market and how it's doing as a whole. I have been ...
7
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2answers
532 views
What quantitative strategies were successful through the 2008 crisis?
Obviously, strategies like "short everything" did well during this period, but getting the future right is one thing and having a robust strategy is another.
In particular, many quantitative ...
16
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5answers
1k views
Most successful investors using academic-based framework?
What are the most famous/best performing absolute-return funds employing approaches based on mainstream finance theory (i.e., theory presented in Journal of Finance, AER, Econometrica, using typically ...
5
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1answer
572 views
Can momentum strategies be quantitative in nature?
I have read some papers on quantitative trading strategies and it seems like strategies that focus on mean reversion or statistical arbitrage give signals that are dependent on some quantitative ...
6
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4answers
683 views
How to properly evaluate backtest returns?
Do you evaluate a strategy in a backtest based on the cumulative returns generated by the strategy (i.e. looking at the cumulative returns of the trades that occur) or do you start with a certain ...
8
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1answer
799 views
How to apply the Kelly criterion when expected return may be negative?
My concern is how to handle a negative value for the Kelly formula. Even when you have a system that has positive expectancy, you can (and usually will) sustain a number of losses, sometimes ...
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3answers
901 views
How to compute the alpha decay of a strategy?
How can one compute the alpha decay of a systematic trading strategy?
10
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3answers
2k views
How to combine multiple trading algorithms?
Is it possible to combine different algorithms so as to improve trading performance? In particular, I have read that social media sentiment tracking, digital signal processing and neural networks all ...
12
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4answers
1k views
Evaluating automated trading strategies: accepted practice
Both for private projects, and for clients, I've been working on code a lot this year to evaluate automated trading strategies. This often ends up turning into the task of how to fairly compare apples ...
6
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2answers
2k views
What is a medium to low frequency trading strategy and why is it less hyped?
The term high frequency trading has been used quite often recently to refer to trading using real-time tick data (or data aggregated to few seconds) and having an intra-day holding period.
How are ...
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5answers
1k views
How many explanatory variables is too many?
When researching any sort of predictive model, whether using ordinary linear regression or more sophisticated methods such as neural networks or classification and regression trees, there seems to ...
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2answers
3k views
What types of neural networks are most appropriate for trading?
What types of neural networks are most appropriate for forecasting returns? Can neural networks be the basis for a high-frequency trading strategy?
Types of neural networks include:
Support Vector ...
16
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4answers
1k views
Any research on how natural language processing can be used to forecast stocks?
Is there any published research of decent quality linking news or unstructured information to asset returns? I know that Thomson Reuters offers its Machine Readable news (MRN), so somebody must use ...
9
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3answers
822 views
How to optimally allocate capital among trading strategies?
I'm trying to find an optimal way to allocate capital among trading strategies.
"Quantitative Trading" by Ernie Chan claims on page 97 that the optimal fraction of capital to allocate to a given ...
8
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1answer
821 views
What is the average Sharpe ratio of volatility arbitrage funds?
Where can I get data on performance metrics for volatility arbitrage funds? I am trying to compare the Sharpe ratio of my strategy to those of the major players.
7
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2answers
412 views
What is a reasonable upper bound on the performance of a daily trading strategy?
I am backtesting an equity trading strategy which trades only once per day. Is there a general rule of thumb for the reasonable upper bound on the rate of return of such a strategy? For example, a ...
10
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2answers
733 views
How to build a regime-switching model which knows its own limits?
In recent months I've come to the conclusion that there are not only certain regimes in the markets (like bear or bull) but phases where all models fail because we are in uncharted territory. The ...
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3answers
2k views
Papers about backtesting option trading strategies
I am looking for all kinds of research concerning option trading strategies. With that I mean papers that publish results on different option trading strategies properly backtested with real-world ...
9
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3answers
801 views
What is the ideal ratio of in-sample length to out-of-sample length?
Suppose you are running a portfolio of quantitative strategies and that you develop a new potential strategy to be added to the mix. Assume for simplicity that the new strategy is independent of the ...
6
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1answer
361 views
Are shorter holding period strategies better?
Consider two statistically identical strategies (identical information ratios, sample size, ratio of transaction costs to total profit, etc.) except that one has a much shorter average holding period. ...
17
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2answers
1k views
How much data is needed to validate a short-horizon trading strategy?
Suppose one has an idea for a short-horizon trading strategy, which we will define as having an average holding period of under 1 week and a required latency between signal calculation and execution ...
25
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7answers
6k views
How useful is the genetic algorithm for financial market forecasting?
There is a large body of literature on the "success" of the application of evolutionary algorithms in general, and the genetic algorithm in particular, to the financial markets.
However, I feel ...
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4answers
593 views
What are the risk factors in analysing strategies?
What do you think of strategies displayed on timelyportfolio.blogspot.com?
I really like the fact that there is some code to reproduce the strategies, but they seem very elementary because he does ...
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2answers
1k views
How can I learn about the quantitative aspects of market making in illiquid single stock options?
I would like to learn more about the possible ways of doing quantitative research regarding option market making. In particular, while the mainstream index option market may be very liquid, the ...
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1answer
201 views
What would be the impact of the US Credit Rating downgrade on Crude Oil Prices? [closed]
From a modeling point of view, here are my primary assumptions for Monday:
a) I would expect the US$ to depreciate and crude oil to rise in the long term.
b) Expect crude oil to dip in the short run ...
11
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2answers
478 views
Transparent quant products with real track record
A real track record is better than backtesting! I am looking for
products, funds, certificates, indices etc. that are based on
quantitative trading strategies where the
strategies and performance ...
