This is again an extension of the last question. Will the market be counterproductive? Not really!

When you say algorithms it essentially means that you have automated the executions, an algorithm does not always mean high-frequency trading. So if you are a retail customer and you are trading using an API offered by any broker, you are not really trading on a high-frequency basis hence you are not HFT but you are definitely algo, it just brings more efficiency.

If there is too much of algo and you are trying to trade the inefficiencies in the market then it can be a challenge just because finding those efficiencies can be really difficult but otherwise, it won’t be counterproductive. Another thing to add is that even for the inefficiencies, targeting them becomes a game of technology and infrastructure. So these factors give you a certain advantage.

For e.g. the kind of network you can have, the kind of systems, hardware that keeps on becoming more expensive.

So if you are focused on eating on the market inefficiencies more the HFT in the market it will be difficult to spot inefficiencies because the moment it is there, it is gone, and someone will take it away.

Yes, you can quantify technical indicators and it’s very simple because it is a set of mathematical formulae, whether they are quantitative or not it can be seen upon. But you can definitely quantify and automate them.

Yes, you can also quantify patterns and waves. Patterns with relatively much more ease; if you can think of something then the machine is capable of doing it because like our brain machine also works on logic. To elaborate on that some of the algorithms can be more complex when you are coding the logic and some of them can be easy to code.

For e.g. if you are drawing a trend line then it’s fairly simple, you are looking for two points and y=mx+c is what your formula for a trend line is and if you know the intercept you can create a line or if you know the two points you can calculate the intercept and create a line. That part being is not difficult, you can calculate the local maxima and local minima then you can draw the line. In case you are looking at something which has a lot of room for subjectivity that it can be more difficult.

Similarly on the wave side if you are trying to code an Elliott wave and have defined the wave rules very explicitly then it’s not that difficult but if you have kept a lot of room for subjectivity then, in that case, it will become very difficult. In fact, there are some tools available that are used for coding the patterns for these waves and we have also started working on such things which you should be able to see in the near future.

It all depends what works for you. If the ready-made software is already working for you and you are happy with the performance then you just need to keep on evolving and experimenting because the same thing won’t work all the time.

Definitely! In fact, this is one of the benefits of automating your strategy.

Controlling the emotions, giving you the scalability, giving you the bandwidth that you can use to work on the strategies while execution is carried out by the machines are some of the key benefits that you get by automating at any scale.

Unless if you are interfering with your port all the time then nothing can help you but assuming you are not doing that then yes automation can help.

Is algorithmic trading for retail traders? Probably yes, if you have the right skills.

But HFT for retail traders is definitely no because HFT is more of a technology game. Don’t get misled by someone if they say now you are a retail trader, you can go for HFT. This can be if the person doesn’t know what HFT exactly means or he doesn’t know what a retail trader means.

You would need to spend a reasonable amount of capital before you go and start trading HFT strategies. That does not mean you cannot do algo, algo you can.

But if you are planning to do cash future arbitrage or calendar spread or some basic put call arbitrage using a retail platform then probably you would not be seeing much success based on that.

In most of the HFT firms, if you are on the high frequency and low-latency side C++ is the preferred language, since it is the fastest and you are concerned about every microsecond. In case you are not concerned about that then you can have any other language, it doesn’t matter, and it doesn’t add that much latency that you should be concerned about. So yes, C++ language can be used.

Can it be the only one that can be used? If you are doing HFT then most likely yes but not otherwise.

Another important thing to know is that these programming languages are not just here to code algorithms or strategies but it also helps in doing a lot of research and analysis, so that is something which is more popular in R and Python. Even in the HFT test you will see a lot of analysts using R and Python for backtesting and evaluate the trading strategies. When it goes to production, the algorithms are coded in C++ for HFT. But for medium and low frequency any of the languages should be fine.

This is just limited information here but what I would suspect or what I would guess here is that something wrong in the backtesting parameters or the output parameters, there can be some room for optimization there.

In the quant trading strategies, you look at the sortino ratio as well as different ratios including the one basic thing that every trader looks at is the drawdown. So there is one basic but not so popular concept of in-sample and out-of-sample trading which is that you do not optimize your backtesting on the whole dataset that is available to you, you take it down to in-sample and out-of-sample data. In the in-sample data you do all the optimizations you want to do and then you run the strategy on the out-of-sample data on which it has not been optimized and you check how the performance is or in your case how the drawdown is. If the drawdown is too high then you need to curve a bit volatility in your strategy which is too high for a risk and if it is showing results which are giving back to back big losses in the out-of-sample data. So this is something that can help you and you might get some confidence in scaling up your strategy.

As we discussed earlier the HFT ratio just tells you about how much competition you can expect. If your strategies are plain vanilla arbitrage strategy then the HFT ratio would suggest that it might not be a good idea to venture into that market. If your strategies are not plain vanilla arbitrage strategy but are more intelligent, use more data analysis results and use more statistical data with some decent predictions, then, in that case, it might not matter that much.

High HFT definitely means that if you want to venture into the plain vanilla arbitrage strategies or even to certain extend market making strategies, you would need to have a technologically very strong infrastructure base on your end.