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Ankit Garg Profile picture
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Jun 18 • 8 tweets • 3 min read
#BookRecommendations for beginners in the world of systematic/quantitative trading and investing. Will add more with time.

Retweet/Share with anyone who might benefit.

In no particular order -

1. Systematic Trading by Rob Carver @investingidiocy Image
2. Expected Returns by Antti Ilmanen Image
3. Inside the Black Box - Rishi Narang Image
4. Quantitative Trading by Ernest Chan @chanep Image
5. Algorithmic Trading by Ernest Chan @chanep Image
6. Quantitative Momentum (Investing) by Wesley Gray & Jack Vogel @alphaarchitect Image
7. Active Portfolio Management by Grinold and Kahn

8. ML for Trading (Advanced)

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More from @Ankit_Quant

Ankit Garg Profile picture
Jul 5
Macro Analysis of FX. Putting my erstwhile FX trader hat on to analyze what is happening with global markets.

I see the #CrudeOil move, #EURUSD move as a flight to safety move into USD.

I'm trying to explain the causation of flow in below thread 🧵

1/n
What all is losing ground against #USD?
#CrudeOil 🔻8.32%
#EURUSD 🔻1.77%
#GBPUSD 🔻1.49%
#Gold 🔻2.1%
#BTC 🔻2.7%

All these are being sold against USD. The money doesn't leave the system. So where does it go?

In risk-off environment it goes to safe havens such as:
2/n
#USD, #CHF, #JPY, Long-Dated US bonds (30Y) & #GOLD.

While some G10 FX pairs have lost upwards of 1.5%, both safe-haven currencies of JPY(🔻0.11%) and CHF (🔻0.89%) are seen relatively stable when compared to other G10.

US30Y Yields are down (bonds are up) by🔻4%.
3/n
Read 7 tweets
Ankit Garg Profile picture
Jun 1
I am going to take liberty and expand with book names on some very fine recos by Roy. All books available on Amazon.

1. Sheldon Natenberg
2. Euan Sinclair
3. Colin Bernett
Read 8 tweets
Ankit Garg Profile picture
Sep 1, 2021
No Matter how many algos I hv created in past, evry time I bring a new algo to LIVE trading-I'm jittery. That is the human side of Quant Trading. We build robots/systems – but ourselves are humans with same apprehensions and self-doubt as anyone else. A 🧵of my learnings 👇: 1/n
from bringing #QUICKSINGLES to research stage to LIVE Investor Deployment. It has hit a new ATH today and now has had 60 trades to it on LIVE Trading. Some background of research and approach first: 2/n
I had bt this strategy and associated robustness testing was completed in Mar-21. For the first time I was experimenting with a pure Data Driven strategy research (it had no hypothesis when I started my research). I was skeptical of my BT and kept on finding ways to break it. 3/n
Read 15 tweets
Ankit Garg Profile picture
Jul 8, 2021
Efficient Capital Allocation - A🧵
A lot of traders are looking to deploy multiple systems with opposing styles (trend following + vol selling) on same capital to enhance returns. The assumption is that with sufficient buffer, idle capital can take care of losses in one sys. 1/n
While some results may be generated from the other system. The risk from this comes in form of systems becoming highly correlated and leading to more than perceived DD from back tests. The traders can be better off if they perform following: 2/n
1- Understand if your returns are coming from different aspects of markets. This could be cross asset class or from different style (Trend/Mean rev/Vol selling etc) 3/n
Read 7 tweets
Ankit Garg Profile picture
May 23, 2021
A brief history of #BTC crashes. As a #BTC HODLer, I've been mockingly asked the ques of - how is your portfolio doing several times in the past during BTC crashes. What is happening this month is no diff 4m several other instances in the past. 🧵 on 2 such past events: 1/n
#BTC went from sub $100 to making a top at $1163 in Oct'13. Over the next 14 months it retraced and fell around 87% to make a bottom at $152.4 in Jan'15. I did not have any long term exposure during this period.  BTC at $250-350 was considered "EXPENSIVE" for a long period. 2/n
Over the next 3 years it went to a high of $19666 in Dec'17. A 129x increase in price from the bottom and 17x from previous top. Previous "Crash" was a blip on chart and $250-$350 entrants were considered lucky now. 3/n
Read 6 tweets
Ankit Garg Profile picture
May 22, 2021
Weekend learning session with @alok_dharia and @VohiCapital. Muchas Gracias 🙏
Had an opportunity to discuss a wide range of topics from vol trading to global macro. Learnt handful of new things and got reinforced on some others.
A brief summary of our discussion: 1/n
1. All of their and our systems are automated. It is not only important to get confidence on our edge via backtesting, but also opens up possibilities to explore more opportunities as current algos/models trade Live.
2. Volatility Trading has more to do with understanding the dynamics of volatility itself, rather than rampant/random volatility selling. While later may work in high vol environments such as 2020, to get long term performance, spend time on modeling/understanding vol features
Read 7 tweets

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