10

Here are some general directions: Alternative Risk Premia The ARP, or "smart beta," space has gained a lot of tractions over the past few years. These are rule-based strategies that provide systematic exposures to risk factors that have historically generated positive excess returns. Some of the best-known factors are, of course, trend, value, carry, etc. ...


9

If your strategy truly has no directional bias, then the benchmark should be cash (ie whatever you would earn using the capital in your trading account and taking no risk).


6

You could compare it, over the historical period of interest, to 1000 randomly generated VIX strategies which are: Flat on 60 Percent of days (randomly chosen days) Long VIX futures on 20% of days Short VIX futures on 20% of days (You would adjust these percentages to the characteristics of your strategy. I guessed these values from your comment). The ...


5

If you are developing this strategy to use personally, I would benchmark it against your next best option. If the strategy has been developed to attempt to manage other peoples money I would benchmark it against the HFRX RV: Volatility Index. This is an index of alternatives that a Vol investor would consider versus investing in your strategy. From HFRX ...


5

I think it's best to learn generic C++. Most of the firms hiring for quant Dev roles usually need good general programming skills and interest in the markets. If you're learning for personal trading I'd say learn Python and for that any Data Science course that includes coding algorithms from the scratch (not through libraries) would suffice.


4

There are not a lot of research papers regarding fixed income quant strategies. Equities, commodities and multi-asset strategies are much more common ... But I can recommend you to read this (from my library of useful links): AQR's Yield Curve premia Chua, Koh, Ramaswamy: Profiting from Mean-Reverting Yield Curve Trading Strategies Quantpedia's screen ...


4

As clarified by you in the comments, I haven't come across duplicate tickers at least not in Bloomberg or the Indian exchange websites. Example of GOOG and GOOGL mentioned in the comment, represent Alphabet Inc Class C and Alphabet Inc Class A respectively. Class A shareholders enjoy voting rights whereas Class C shareholders don't (see here). Hence there ...


3

If you already have a strategy generating potential long and short positions, you may want to check Chapter 10 of Marcos López de Prado's book Advances in Financial Machine Learning. It describes a number of strategies that include a budgeting approach where you only rely on the number of concurrent long and short positions to optimize position sizing. If ...


3

It depends what you are doing: asset allocation, classifier/regression modelling, etc. In any case can shift the weights of the allocation, change the regressors, etc. Nevertheless, it belongs to the family of backtesting sampling bias.


3

The optimal investment strategy depends on the investment goals, or equivalently your utility function (which the investment strategy is supposed to maximize). The forward will trade at $\mathbf{E}^*_0(F_T)$ in the market when you invest at $t=0$. If you buy your maximum volume $M$, then gain/loss at $T$ is given by $M(F_T-\mathbf{E}^*_0(F_T))$ (which is ...


3

Broadly you're asking about directional versus relative value strategies. There are lots of directional approaches, but I've yet to see many discussed publicly in non-generic ways (I mean, if they work, why would anyone talk about them?). As others have noted, trend following is a notable example. I'd consider a lot of equity factor approaches as a ...


3

There are lot of strategies. You can try for example: Active Collar strategy Calendar Option Strategies Dispersion trading Try to google more, or look for strategies on ssrn.com or arxiv.org ...


3

There are some slight inaccuracies in using term basis. You probably meant strategies which profit from carry/futures roll. There are a lot of variations of carry/roll strategies on different markets. I can point you to: 1/ FX carry - can be easily traded using futures 2/ Term structure/carry in commodities 3/ Term structure/carry in bond futures 4/ Term ...


3

There are two main types of orders: limit orders and market orders. Limit Orders: Limit orders are passive orders that are placed on the book at a given price, and remain there until they are executed or cancelled. Market Orders: Market orders are executed immediately at the best available price in the book, against a limit order that is already there. ...


3

Carry is typically only associated with known cashflows - its closely related cousin, roll, is typically associated with unknown cashflows, assuming the state of the world is unchanged. Given this, carry is typically only analyzed for the current period of the swap or bond. If we assume your swaps are fixed Semi vs a 6m Ibor index, then the natural period ...


3

The first observation I make is that the proportion of variance is not very high for the first PCs, with the implication that I would hypothesise that the PCs are not very stable, nor reliable. (You can test this by varying the sample period and analysing the consistency of the PCs) If the PCs are not stable from period to period then information you can ...


3

The justification for that microprice is empirical, not theoretical. In most market I can think of, most of the time, if there are more orders and more size on the bid than the ask, then it's more likely that that BBO will tick up rather than down. And the greater the imbalance, the higher the probability of an uptick (and vice-versa for downticks). For ...


2

I think the given python code snippet is composed according to the following steps: \begin{equation} var(\tau) = \left< |z(t+\tau)-z(t)|^2 \right> \thicksim \tau^{2H} \end{equation} \begin{equation} \Rightarrow var(...)\thicksim \tau^{2H} \end{equation} \begin{equation} \Rightarrow std(...) \thicksim \tau^{H} \end{equation} \begin{equation} \...


2

1) When you buy/sell a currency pair in the spot market, you will be holding the actual currency. For example, if one buys EUR/USD, one will own EUR and have paid with it in USD. If you have USD in the account to cover the purchase, your account will be debited the USD. If not, you will be borrowing USD from your bank and therefore incur financing costs....


2

The Treasury Bond Basis: An in-Depth Analysis for Hedgers, Speculators, and Arbitrageurs by Galen Burghardt and Terry Belton is a good book on Treasury Futures.


2

You have to consider seriously to use portfolio construction, at least for risk management purposes. To start with, you should "backtest" the risk you are taking with your current "proportional strategy". What would have been: the volatility of your portfolio (ie your aggregated positions) in the past? your maximum loss (max draw down) in the past with this ...


2

Alpha Model: First and foremost is an alpha model that forecasts excess return of stocks in Investment process. If return distribution is characterized by the expected return and the standard deviation, it is often the expected return that determines whether we buy or sell, overweight or underweight, and the standard deviation that determines the ...


2

Assume on a date t, your pair trading strategy said trade the pair: A and B, say go long A, and short B. By definition of the pair strategy, it is very likely that the price of A declined whereas that of B increased in the previous period; so from pair trading perspective, A is cheaper, whereas B is expensive. So we buy A and sell expensive B, expecting A to ...


2

@Dhruv Mahajan makes a good point in my opinion. @LuigiBallabio in the comments is speaking from a position of authority here as he is the lead developer of QuantLib. If you want to learn C++ and Pricing at the same time you can try C++ Design Patterns and Derivatives Pricing (Mathematics, Finance and Risk) by Mark Joshi. However, since that books has been ...


2

IIRC, the signs of the PC are meaningless. +/-'ive doesn't itself tell you anything. Rather, the cross-sectional, absolute max of the PCs will tell you which one is most important per item (eg: PC6 looks most important for Beta: M-3). I think 6.6a and 6.6b in Cochrane's asset pricing touch on this (https://www.youtube.com/playlist?list=...


2

If your signals only become available at market close, you obviously can't execute them in that day's trading session. You have a few options - Try to execute your trades out of market hours with a willing broker (probably a bad idea, you almost certainly won't get good prices) Trade in the opening auction the next day. Trade in the next day's continuous ...


1

Yes. We should indeed say that the Garch part of the model does not help to predict the Direction of the movement (this is given by the expected drift of the Arma, which gives the conditional mean of the return process) but helps to predict the size of the deviation of the next period return from the expected Arma drift. It is a measure of the squared size ...


1

where can I start my research from? Searching for asset allocation papers and portfolio construction papers will yield far better results. Here are a few papers you may find interesting to get you started: Optimal Trade Sizing in a Game with Favourable Odds: The Stock Market A Quantitative Approach to Tactical Asset Allocation


1

The two types of backtesters have slightly different purposes. The vectorised backtest is a rather crude way to quickly test a strategy. You do it by multiplying the signal vector with the returns vector and the result is the equity curve. The event-driven backtester is a more well thought out simulation. By making use of an event driven backtester we can ...


1

You don't need an event-driven backtester. To establish some convention, a function or method that takes a vector as an argument (e.g. a MATLAB function, statsmodels API methods) is sometimes interchangeably and confusingly referred to as a vectorized function. This doesn't necessarily mean that it uses SIMD vectorization, although quite often it is ...


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